Journal.2012.pdf - RMK ENGINEERING COLLEGE

ISSN : 0974-9535

RSM International Journal

of

Engineering, Technology & Management

Chief Editor

Dr. Elwin Chandra Monie

R.M.K. ENGINEERING COLLEGE (ISO 9001:2000 Certified Institution)

RSM Nagar, Kavaraipettai – 601 206

Gummidipoondi Taluk, Thiruvallur, Tamil Nadu, India

Chief Editor


Co-ordinating Editor

Dr. K. A. Mohamed Junaid

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RSM Nagar, Tamil Nadu, India.

Dr. A. Jagadeesh

Professor



Dr. Raj Gururajan

Associate Dean

University of Southern Queensland, Australia

Dr. Binu Sukumar, M.Tech.,Ph.D.

Head / CE



Dr. Shunmuganathan K L, M.E,M.S,F.I.E.,Ph.D. Head / CSE



Dr. Geetha Ramdas , M.E, Ph.D.,

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Dr. Sivakumar R , M.E., Ph.D.

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Dr. Mohamed Junaid K A , M.E,Ph.D.

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Dr. Sekar S, M.E.,Ph.D.

Professor / Mech



Dr.Suresh T, M.E.,Ph.D.

Professor / ECE



Dr. Mohamed Junaid K A , M.E,Ph.D.

Co-ordinating Editor, Vice Principal



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Contents

1. Delimitation Studies in Drilling of Particleboard (PB) Wood Composite Panels Using Taguchi Method T.N. Valarmathi K. Palanikumar S. Sekar 7

2. Material Aspects of High Performance Concrete

M R L Sastry Dr K Srinivasa Rao Dr P Subba Rao 12

3. Comparative Study on Securfe Routing Protocols in MANETs C Geetha M Ramakrishnan R Jagadeesh Kannan 22

4. A Novel Quasi-Orthogonal STBC for 4 Transmit Antennas using Lattice Decoding

G Kanimozhi K Senthilkumar 32

5. A Novel Method of MRI Brain Image Segmentation K S Arun pandian G Babu 39

6. Survey of Architectures and Mobility Model for Ubiquitous Underwater Acoustic

Sensor Networks G Shalini 43

RSM International Journal of Engineering, Technology & Management |7

DELAMINATION STUDIES IN DRILLING OF PARTICLEBOARD (PB)

WOOD COMPOSITE PANELS USING TAGUCHI METHOD

T.N.Valarmathi1,*

, K.Palanikumar2, S.Sekar

3

1Research Scholar, Department of Mechanical & Production Engineering,

Sathyabama University, Chennai-600 119, India

Email: [email protected]

* Corresponding Author 2Principal, Sri Sai Ram Institute of Technology, Chennai-600 044, India

Email: [email protected] 3Research Scholar, Department of Mechanical Engineering,

R.M.K. Engineering College, Kavaraipet- 601 206, India


Abstract

Wood based composites are preferred over

solid wood because of their aesthetic

appearance and favorable properties.

Drilling process is extensively used in

furniture products assembly. Cutting forces

like thrust force developed during drilling

affecst the surface quality of drilled hole and

also causes delamination damages. The aim

of this study is to find out the influence of

drilling parameters on delamination.

Taguchi design of experiments is used to

perform the drilling experiments. From the

experimental results it is revealed that high

spindle speed, low feed rate and smaller

diameter mnimizes the tendency of

delamination.

Keywords: Wood based composites,

Particleboard (PB), drilling, delamination,

Taguchi method.

I. Introduction

Wood based composites are available as

plywood, particleboard, Fiberboard and

hardboard, etc. Wood composite products

are because of their special mechanical and

physical properties [1]. Particleboard panels

are manufactured using waste wood

particles and saw dust. The manufacturing

and assembly of wood composite products

needs machining process like drilling. The

cutting force developed in drilling depends

upon the machining conditions. Dippon et al

[2] expressed the cutting forces as functions

of cutting constants, tool geometry and

uncut chip area. They developed a

mathematical model to predict the cutting

forces when machining wood panels. Nemli

et al [3] observed that board density, raw

material type, pressure and shelling ratio

have great influence on the surface

roughness of Particleboard. Porankiewicz

[4] developed a method to determine the

effect of chemical properties of

particleboard on cemented carbide tool

material. Davim et al [5, 6 and 7] observed

that high cutting speeds minimize the

delamination tendency in drilling of wood

composite panels. Gaitonde et al [8, 9]

found that the cutting speed and feed rate

have influence on delamination in drilling of

MDF panels. Palanikumar et al [10]

performed drilling experiments on MDF and

revealed that the low feed rates minimize the

delamination tendency. In this study the

influence of input process parameters are

studied to minimize the delamination in

drilling of particleboard panels using

Taguchi technique.




Delamination Studies In Drilling Of Particleboard (Pb) Wood Composite Panels Using Taguchi Method


II. Experimental details

Particleboard (PB) is manufactured in sheet

form using waste wood particles glued

together with synthetic adhesives. The

drilling experiments were performed on

laminated PB of 12mm thickness with high

speed steel (HSS) twist drills on CNC

vertical machining center at dry condition.

The CNC vertical machining center used for

this experiment is shown in Figure 1. The

twist drills used in the experiment and the

drilled particleboard are shown in Figure 2

nand 3 respectively. The experiments were

planned based on Taguchi‟s orthogonal

array. The cutting forces developed in

drilling cause the delamination damage

which in turn affects the performance and

the apperance of final product. The

delamination damage in drilling is shown in

Figure 4. The amount of delamination can

be minimized by the application of proper

cutting conditions. The relation given in Eq.

(1) is used to determine the delamination

factor.

(1)

where Dmax = maximum diameter of the

damage zone and D = hole diameter.

Figure 1 CNC vertical machining center

Figure 2 Twist drills used

Figure 3 Drilled particleboard

Figure 4 Delamination in drilling

The properties of PB composite panels

tested are presented in Table 1. The control

factors and their levels are presented in

Table 2.

Table 1 Properties of PB composites tested

Tensile

strength

N/mm2

Modulus

of

Rupture

N/mm2

Moistu

re

Conten

t

%

Density

Kg/mm3

0.3 11 5-15 500-

900



Table 2 Control factors and their levels

III. Method of analysis

Taguchi Technique

Taguchi method combines the statistical and

engineering methods to improve the quality

and reduce the cost of experimentation using

“Orthogonal Array (OA)” of experiments.

The effect of various control parameters on

the response variable can be determined

using the main effects plot and interaction

plot for means. The signal to noise (S/N)

ratio is used to measure the quality

characteristics. In this investigation the

Taguchi L27 orthogonal array as presented in

the Table 3 and the quadratic loss function

relation the smaller - the - better given in

Eq.2 is used for the analysis.

(2)

where, y = the observed data and n = the

number of observations.

IV. Results and discussion

Particleboard composite panels are finding

applications in the furniture manufacturing,

in flooring, etc. The appropriate selection of

cutting parameters reduces the rejection of

products due to drilling damages. In this

study drilling experiments were performed

using Taguchi design of experiments to find

out the influence of drill diameter on

delamination with three control factors at

three different levels. The delamination of

the drilled holes was measured to determine

the delamination factors (Fd) for all the

experimental trials.

Figure 5 Main effects plot for means for

Diameter

The main effects plot for means for drill

diameter is shown in Figure 5. From main

effects plot for means it is observed that the

value of delamination factor is gradually

increased when the drill diameter is

increased and it is less for smaller diameter.

From main effects plots it is revealed that

drill diameter has influence on delamination.

The interaction plot for means for spindle

speed versus drill diameter and feed rate

versus drill diameter are shown in Figure 6

and 7 respectively. From interaction plot for

means it is observed that the values of

delamination factor are less at low drill

diameter and high speed, low feed rate and

low drill diameter combinations. From main

effects plots and interaction plots it is

observed that the increase in drill diameter,

feed rate increases and increase in spindle

speed decreases the amount of delamination.

Hence it is revealed that the tendency of

delamination can be reduced by the proper

selection of spindle speed, feed rate and drill

Parameters Levels

1 2 3

Spindle speed

(N) [rpm]

150

0

300

0

450

0

Feed (f)

[mm/min] 100 200 300

Drill

diameter(d)[m

m]

6 8 10



diameter combinations in drilling of

particleboard panels.

Figure 6 Interaction plot for means for

Speed vs Diameter

Figure 7 Interaction plot for means for Feed

vs Diameter

V. Conclusion

The drilling tests were performed using

Taguchi design of experiments. The

delamination factor for all the trials were

determined to analyze the influence of

drilling parameters on delamination.

Based on the experimental results, main

effects plot and the interaction plots

following conclusions were drawn.

The delamination is increased when

the drill diameter is increased.

The delamination is increased when

the spindle speed is decreased and feed

rate is increased.

From main effects plots and interaction

plots it is observed that the drill

diameter has significant influence on

delamination.

From the interaction plots it is noticed

that the spindle speed and feed rate

have influence on delamination.

From the experimental results, it is

revealed that low feed rate, high

spindle speed and smaller drill

diameter combination is the preferred

cutting condition for reducing the

tendency of delamination in drilling of

PB wood composite panels.

VI. References

[1] Berglund.L and Rowell.R.M, “Wood

Composites-Handbook of Wood

Chemistry and Wood Composites”,

Chapter 10, (2005) CRC press USA

[2] Dippon.J, Ren. H., Amara.F.B. and

Altintas.Y,“Orthogonal cutting

mechanics of medium density fibre

boards”, Forest Products Journal,

(2000), Vol .50, No. 7/8, pp 25-30.

[3] Nemli.G, Ozturk.I and Aydin.I, “Some

of the parameters influencing surface

roughness of Particleboard”, Building

and Environment, 40, (2005), 1337-

1340.

[4] Porankiewicz.B, “A method to

evaluate the chemical properties of

particleboard to anticipate and

minimize cutting tool wear”, Wood Sci

Technol ,37, (2003) 47–58.



[5] Davim.J.P, Clemente.V.C and Silva.S,

“Evaluation of delamination in drilling

medium density fibreboard”,

Proceedings of the Institution of

Mechanical Engineers, Part B: Journal

of Engineering Manufacture, 221,

(2007a) 655-658.

[6] Davim.J.P, Clemente.V.C and Silva.S,

“Drilling investigation of MDF

(medium density fibreboard)”, Journal

of Materials Processing Technology,

20, (2008b), 537–541.

[7] Davim.J.P, Gaitonde.V.N and Karnik.

S.R, “An investigative study of

delamination in drilling of medium

density fiberboard (MDF) using

response surface models”, Int J Adv

Manuf Technol, 37, (2008c), 49–57.

[8] Gaitonde V.N., Karnik S.R., Davim.

J.P, “Prediction and minimization of

delamination in drilling of medium-

density fiberboard (MDF) using

response surface methodology and

Taguchi design”, Materials and

Manufacturing Processes, 23, (2008a),

377–384.

[9] Gaitonde V.N., Karnik S.R., Davim.

J.P, “Taguchi multiple-performance

characteristics optimization in drilling

of medium density fiberboard (MDF)

to minimize delamination using utility

concept”, Journal of Materials

Processing Technology, 196, (2008b),

73–78.

[10] Palanikumar.K, Prakash.S and

Manoharan.N, “Experimental

investigation and analysis on

delamination in drilling of wood

composite medium density

fiberboards”, Materials and

Manufacturing Processes, Volume 24,

Issue 12, (2009), Pages 1341-1348.


Material Aspects Of High Performance Concrete

M R L Sastry *, Dr K Srinivasa Rao **, Dr P Subba Rao ***

* Assistant professor,

Department of Civil Engineering,

Chaitanya Engineering College,

Visakhapatnam – 530 048, India. E-mail:

[email protected], Mobile: 9951452459

** Associate Professor, Department of

Civil Engineering, Andhra University,

Visakhapatnam-530 003, India. E-

mail: [email protected], Mobile:

9866037087

*** Professor, Department of Civil Engineering,

J.N.T. University, Kakinada – 533 003, India.

E-mail: [email protected], Mobile: 9959026889

Abstract

Performance of concrete is improved by

limiting nominal maximum size of coarse

aggregate; using fine aggregate having

high fineness modulus; using mineral

admixtures like silica fume, fly ash,

ground granulated blast furnace slag

(GGBS); limiting water binder ratio;

increasing packing density of aggregates

and also cementing materials; improving

bond between coarse aggregate and

cement matrix; using optimum quantities

of different materials along with suitable

type of high range water reducer (HRWR);

and by adopting proper placing,

compaction and curing procedures.

Physical and chemical properties of

various constituent materials play a vital

role in improving the performance

characteristics. Addition of super

plasticizer is inevitable to achieve good

workability. Air entraining admixture is

meant for freeze-thaw durability.

Shrinkage-reducing admixture reduces the

driving force for cracking. Porosity and

pore structure characterize the materials of

high performance concrete (HPC) in

connection with mixture optimization.

Water-cement ratio significantly

influences the brittleness of the concrete.

Keywords: Aggregate, mineral additives,

packing density, interfacial bond, crack

growth, curing.

1. Introduction

American Concrete Institute (ACI) defines

HPC as, “Concrete meeting special

combinations of performance and

uniformity requirements that cannot

always be achieved routinely using

conventional constituents and normal

mixing, placing and curing practices”.

Durability problems of existing concrete

infrastructures, and the increasing use of

concrete in hostile environments-such as

seawater and industrial effluent exposure-

are making new demands in the

development of HPC.

Because of this, HPC is likely to be the

construction industry workhorse in the 21st

century [1]. Chemical and mineral

admixtures are often added to enhance or

to control the properties like strength,

workability, setting time etc. A common

characteristic of HPC is a low water to

cement ratio. As the water-cement ratio is

decreased, paste capillary porosity

decreases, and strength and impermeability

increase. Sometimes, permeability is one

of the deciding factors to check the quality

of HPC. The production of HPC needs

more stringent control on selection of

materials than ordinary concrete to

consistently meet the performance criteria

for workability, strength, durability,


mailto:[email protected],%20Mobile



RSM International Journal of Engineering, Technology and Management |13

cracking behavior etc. The materials for

HPC should be of good quality because the

performance of HPC both in fresh and

hardened states depends on the properties

of the constituent materials and the roles

they play when combined [2].

The constituent materials of ordinary

concrete may not be sufficient in case of

HPC. Definite sizes of ingredients, mineral

and chemical admixtures are necessary for

the production of HPC. The suitability of a

material to produce HPC must be judged

based on its effect to reach maximum

strength, durability and other desired

properties [3].

Performance of concrete is not only

measured by mechanical properties but by

failure behaviour. The fracture properties

of concrete which are closely related to

mechanical properties are influenced by its

chemical constituents and micro-, mezo-

and macrostructures. Interaction and

fracture parameters influence the design of

HPC [4]. Number, location and extent of

pre-existing cracks depend mainly on type

of cement, mineralogical nature of

aggregate, water-cement ratio and curing

conditions. Evolution of pre-existing

cracks under loading depends mainly on

aggregate-matrix stiffness ratio, type of

matrix-aggregate bond and percentage of

voids in the matrix [5].

2. Cement

Cement is a basic constituent in HPC. Out

of many types of cements, Ordinary

Portland Cement (OPC) is the widely used

type of cement. OPC is a hydraulic cement

produced by pulverizing the clinker

consisting of hydraulic calcium silicates

and usually containing one or more of the

forms of calcium sulphate as an

interground addition. Proper selection of

the type and source of cement needs

attention in the production of HPC.

2.1 Properties

Specific gravity of cement is around 3.15.

Specific surface is 22-40 m2/N. Soundness

with Le Chatelier apparatus as per IS

269:1989 should not be more than 10 mm.

Bulk density is 11000-13000 N/m3. Loss

on ignition is less then 5%. If the cement is

too fine, heat of hydration is too high.

Therefore, a consistent cement with a low

C3A content and high C2S content should

be used.

2.2 Content

Variation in quality of cement affect more

on the concrete compressive strength, than

the variation in the quality of any other

material. There is also an optimum cement

content beyond which little or no

additional increase in strength is achieved

by increasing the cement content.

As per IS 456:2000, cement content ranges

from 3200-4500 N/m3. The specifications

of ACI 211.4R-2008 do not set a minimum

for cement content, but its maximum

content is set as 5900 N/m3. As per British

DOE method, cement content ranges from

3000-4500 N/m3.

3. Supplementary Cementitious

Materials

Cement is the principal cementitious

material. To enhance the properties of

HPC, it is necessary to include

supplementary cementitious materials such

as silica fume, fly ash, GGBS. GGBS, fly

ash, rice husk ash and metakoiline are

pozzolanic materials; these materials

impart higher strengths slowly upto 91

days [6].

Mineral additives save and conserve

energy. Primary benefit of using these

materials is the technical aspects regarding

strength and performance properties. The

secondary benefit is economic and

environmental aspects [7].

Silica fume greatly reduces or even

eliminates bleeding. Inclusion of fly ash to

a lesser extent in the mix has physical

effect of modifying the flocculation of

cement, with a resulting reduction in the

water demand. With the use of these

materials, permeability will be lowered



due to the reason of filling up of the pores [8]. Typical Percentages of Oxide of various

cementitious materials are shown in Table 1.

Table1. Oxide composition of various cementitious materials.

Material

Oxide Composition by weight, per cent as per IS 3812-1981

CaO SiO2 Al2O3 Fe2O3 MgO SO3 Alkalis

Na2O+K2O

OPC 60–67 17–25 3–8 0.5–6 0.1–4 1.3–3 0.4–1.3

Silica fume

(SF) 0.1–0.5 90–96 0.5–3.0 0.2–0.8 0.5–1.5 0.1–0.4 0.6–1.7

Fly ash (FA) 1–7 30–60 10–30 4–10 0.2–5 1.5–2.5 0.4–2.6

GGBS 30–45 25–38 15–32 0.5–2 4–17 - -

Content of cementitious materials (cement

+ silica fume +fly ash/blast furnace slag) is

in the range of 5000-6500 N/m3 of

concrete [9].

3.1 SILICA FUME

Use of silica fume(SF) has been widely

accepted as an efficient admixture for

getting high strengths. It can be used as a

cement replacing material because of fine

spherical particles of silicon dioxide and a

higher relative surface area to particle

weight ratio. It increases strength and

reduces permeability. Fine particles of

silica fume improve pore refinement and

consistency.

SF is a by product of the manufacture of

silicon metal and ferro-silicon alloys.It is a

very fine powder consisting mainly of

spherical particles of mean diameter about

0.15 microns, with a very high specific

surface area of 1500-2500 m2/N. Size of

particle is 100 times smaller than cement

grain. SF reacts chemically with Ca(OH)2

of the Portland cement to form calcium

silicate hydrates (C-S-H) which bind the

concrete together. SF increases

cohesiveness of the fresh concrete, which

can lead to improved handling

characteristics. The dense microstructure

of concrete containing SF leads to major

improvements in mechanical properties

and resistance to chemicals such as acids,

fuel oil, chlorides and sulphates. SF is

generally used as a partial cement

replacement (5-10% by mass of cement) to

maintain at lower cement content (with

associated environmental benefits) while

reducing the heat of hydration, and

improving durability. Low water-cement

ratio concretes (cement +SF+GGBS or fly

ash) are increasingly produced for

applications in aggressive environments.

SF gives higher early strength. Slower

reacting GGBS or fly ash reduces the peak

heat of hydration [10].

3.1.2 PROPERTIES

Average size of silica fume particles is less

than one micron, 100 times smaller than

cement-particle. Specific surface area is

1500-2500 m2/N. Specific gravity is about

2.20. Bulk density varies from 2000-2500

N/m3.

3.1.3 CONTENT

Silica fume can be used in concrete in two

ways: (a) as an addition (8-15% by mass

of cement) to enhance properties of the

fresh and/ or hardened concrete, (b) as a

partial replacement of cement (5-10% by

mass of cement).

3.2 FLY ASH

Pulverized Fuel Ash (PFA) is produced

from combustion of pulverized coal in coal

fired power stations. Raw PFA is taken out

of the furnace from the hot air stream by

means of electrostatic precipitation.



Particle sizes of fly ash vary from under

1μm to typically under 20μm. A simple

and inexpensive way of reducing the

cement content is to replace part of cement

by PFA. Reduction in OPC results a

reduction in heat generation, thus

shrinkage and thermal cracking during

hardening can also be reduced.

The particles are generally finer than

cement. Thus they can fill up intergranular

spaces between cement particles. PFA

contains about 65% of silica, which reacts

with lime during hydration of cement to

produce more gel products to fill up

capillary pores. This filling effect reduces

pore sizes and thus permeability of

hardened concrete.

3.2.1 PROPERTIES

Specific gravity is 2.15-2.45. Specific

surface is 35-70 m2/N. Loss on ignition is

1-2%. Bulk density is 6000-9000 N/m3.

3.2.2 CONTENT

Optimum content of fly ash as a

replacement of cement ranges 20-40%.

3.3 GROUND GRANULATED

BLAST FURNACE SLAG (GGBS)

GGBS is a by-product in the production of

pig-iron. Chemically, it is a mixture of

lime, silica, alumina and magnesia,

i.e.,same as portland cement but in

different proportions. GGBS is used in the

areas of high sulphate conditions.

Hydration of blended cement produces

more C-S-H gel and the resulting

microstructure of the hydrated cement

paste is dense. Initial hydration of GGBS

is very slow. There is a long term gain in

strength. Peak temperature of concrete

caused by hydration of cement is reduced.

Greater fineness leads to a better strength

development. Similar grade concrete

containing GGBS generates less heat than

OPC mix during the hydration process,

and this results in reducing thermal and

shrinkage strain. GGBS-concrete requires

less water than the corresponding OPC-

concrete due to low water absorption of

the GGBS for concrete with the same

workability. A reduction of upto 5% of

mixing water can be expected.

GGBS improves different properties of

concrete especially in terms of various

durability aspects i.e., sulphate resistance,

chloride diffusion and alkali-silica reaction

etc. Improvement is attributed to the lower

permeability from a denser microstructure

and also the alumina content of the

concrete mix. Slag-concrete can be used in

class 4 sulphate conditions where as fly

ash-concrete can not be used in that

situation.

3.3.1 PROPERTIES

Specific gravity is 2.90. Specific surface is

32.5-60 m2/N.

3.3.2 CONTENT

Incorporation of GGBS is normally 15-

30% of the cement by weight.

4. COARSE AGGREGATE

Aggregate selection is very important in

producing HPC. Use of well graded

combination of fine and coarse aggregates

is essential for improving packing density

of concrete. Packing density has a major

effect on workability of fresh concrete and

porosity, permeability, and strength of

hardened concrete. Size, shape, texture and

mineralogy of aggregate also significantly

affect the microstructure and properties of

hydrated cement paste in the transition

zone. Nominal maximum size of coarse

aggregate for HPC is 10-12 mm.

Equidimensional (cubical), rough-textured,

angular, crushed granite is most suitable.

The guiding principle of mix design is to

pack as much aggregate into the mix as

possible to reduce the required paste

volume. The less paste that a mix has, the

less shrinkage potential it has [11].

Aggregate strength is important in case of

HPC. A substantial reduction in water

requirement can be achieved with a well-

graded aggregate [12]. Good quality

coarse aggregate is necessary to enhance

the workability, strength, aggregate-matrix



bond or interfacial bond and durability of

HPC. Recommended volume of coarse

aggregate per unit volume of concrete is

shown in Table 2.

Table : 2 Recommended volume of

coarse aggregate per unit volume of

concrete as per ACI 211.4R-

2008 [13]

Optimum coarse aggregate contents for

nominal maximum sizes of aggregates to

be

used with sand with fineness modulus of

2.5 to 3.2

Nominal

maximum

size, in.

1

Fractional

volume* of

oven-

dry rodded

coarse

aggregate

0.65 0.68 0.72 0.75

*Volumes are based on aggregates in

oven- dry rodded condition as described in

ASTM C 29 for unit weight of aggregates

4.1 PROPERTIES

Coarse aggregate should be strong, rough-

textured, non-porous, sound, and non-

reactive. It should be washed before use to

remove deleterious substances such as

organic and inorganic impurities for

getting good interfacial bond. It should

have a low absorption value, a suitable

shape coefficient with a minimum number

of flaky and elongated particles. HPC has

higher coarse aggregate-fine aggregate

ratio than that for normal strength

concrete.

4.2 CONTENT

Dimensional stability (one of the

requirements of the concrete durability)

requires a minimum aggregate content of

65% by volume of concrete [14]. Content

of coarse aggregate in HPC mixes depends

on fineness modulus of fine aggregate,

maximum size of coarse aggregate and its

oven-dry rodded condition.

5. FINE AGGREGATE

Aggregate most of which passing 4.75mm

sieve and retaining on 150 micron sieve is

used for the production of concrete. Sand

of relatively coarser size having fineness

modulus of 3.0 is preferred for HPC. Sand

before using should be made free from

clay, silt and other deleterious substances.

Sand with a fineness modulus less than 2.5

may be sticky, resulting in poor

workability, requires high water content

and, hence, should not be used.

Fine aggregate is a very important part of

the concrete mix which affects the

workability during placement. While

designing HPC, a low value of ratio of fine

to coarse aggregate is considered, to

reduce the water demand [15]. BIS has set

the requirements for grading of fine

aggregates as shown in Table 3.

Table 3: Gradation requirements

for fine aggregate as per IS

383:1970[16]

IS Sieve

designation

passing

specification for

zone II sand

4.75 mm 90-100

2.36 mm 75-100

1.18 mm 55-90

600 μ 35-59

300 μ 8-30

150 μ 0-10

Importance must be given not only for

packing of aggregates but also for packing

of cementitious materials [17]. Grading of

fine aggregate influences the properties of

fresh concrete more than that of coarse

aggregate. According to A.M.Neville,



grading of coarse as well as fine aggregate

is of vital importance in the proportioning

of concrete mixes. The extent to which an

aggregate can be compacted to produce a

minimum void content is dependent on the

size distribution and shape of the

aggregate particles.

5.1 PROPERTIES

Fine aggregate should be sound, surface

dry, low or non-absorbent. Angular fine

aggregate improves the bond between

coarse aggregate and cement matrix.

Rounded and smooth-textured fine

aggregate requires comparatively less

mixing water.

5.2 CONTENT

Sand conforming to zone-II of IS

383:1970 is preferred for HPC. Content

depends upon the fineness modulus of fine

aggregate, and the quantity of coarse

aggregate. Content should be adequate to

improve the cohesiveness of fresh concrete

mixture with high workability. Content

also depends upon the surface moisture

present if any.

6. WATER

Water is the most important component of

the concrete. Water used for mixing and

curing of concrete must be free from

harmful ingredients. Potable water should

be used for mixing and curing. A part of

mixing water is utilized in the hydration of

cement, and the remaining part of mixing

water serves as a lubricant between the

fine and coarse aggregates and makes the

concrete workable. Water also participates

in pozzolanic reactions to produce

secondary hydration products. Too much

quantity of water reduces the strength of

the concrete.

Mixing water should not contain excessive

solids, chlorides, alkalis, carbonates,

bicarbonates, sulphates, and other salts.

Typical limits of impurities in water are

shown is Table 4.

Table 4: Maximum permissible limits

of Impurities in mixing and curing

water as per IS 456:2000[18]

Solids

Maximum

permissible

limits (mg/l)

Organic 200

Inorganic 3000

Sulphates (as SO3) 400

Chlorides (as Cl) for

plain concrete

for

reinforce concrete

2000

500

Suspended matter 2000

6.1 PROPERTIES

Water with a pH of 6.0 to 8.0 and silt

content below 2000 ppm is suitable for use

in concretes.

6.2 CONTENT

Water content of concrete is influenced by

a number of factors: aggregate size, shape

and texture, slump, water to cementing

materials ratio, air content, cementing

materials type and content, admixtures,

and exposure conditions [19]. Total

surface area of the constituents and

particle shape have a profound effect on

the water demand. Sand has the greatest

impact on the water demand of a concrete

mix, this is because the total surface area

of sand particles is substantially greater

than the other mix constituents(except for

the cementitious products which go into

solution). A sand with a fineness modulus

of 2.5 will have a significantly greater

water demand than a similar sand with a

fineness modulus of 3.2. Dust around the

crushed aggregates has a tendency to

increase water demand and impairs the

ultimate bonding between the cement paste

and the aggregate particle. Maximum

water content per cubic metre of concrete



for nominal maximum size of a aggregate is selected from Table 5.

Table 5: Maximum Water Content per Cubic Metre of Concrete for Nominal

Maximum Size of Aggregate as per IS 10262:2009[20]

Sl.No Nominal Maximum Size of Aggregate, mm Maximum Water Content*, N

i 10 2080

ii 20 1860

iii 40 1650

NOTE: - These quantities of mixing water are for use in computing cementitious

material contents for trial batches.

*Water content corresponding to saturated surface dry aggregate.

Quantity of mixing water should be

sufficient to complete the chemical

reactions with cement or binder and to fill

up the gel-pores. It has been estimated that

23% water by weight of cement is required

for chemical reactions and 15% water is

necessary to occupy the space within gel-

pores. Therefore, at least 38% water by

weight of cement is essential for full

hydration in the concrete. However, this

amount can be reduced to 20% and even to

16% using high-range water reducers

(pliskin, 1994). In general, 20 to 40%

water by weight of binder is used for HPC

(Aϊtcin, 1997 b).

Durability is improved when less water is

used in the concrete. But workability may

be a problem. For most concretes

especially those containing finely ground

cements and fine mineral admixtures such

as silica fume, it is not possible to achieve

high workability at water-cement ratios

lower than 0.35 unless a superplasticizer is

used.

7. WATER-CEMENT RATIO

The single most important variable in

achieving HSC is the water-cement ratio.

Strength of concrete is dependent largely

on the capillary porosity or gel/space ratio.

Capillary porosity of a properly compacted

concrete is controlled by the water-cement

ratio and degree of hydration. At a given

degree of cement hydration, a lower water-

cement-ratio-paste has a lower capillary

porosity and thus a lower permeability.

Decreasing the water-cement ratio below

0.30 produces a dramatic increase in

strength and reduction in the coefficient of

permeability of concrete. This is due to

major changes in the characteristics of the

transition zone. Direct control on the

maximum allowable water content, instead

of on the water-cement ratio, is essential.

The key to properly designing high

strength concrete mixes is successfully

lowering the water-cement ratio while still

maintaining workable and placeable

concrete. There are two ways to lower the

water-cement ratio: (i) reducing the

amount of water, (ii) increasing the

amount of cementitious material.

Depending on the magnitude of strength

being called for, it is often necessary to do

both. Lowering the water content can be

accomplished by two primary techniques:

(i) reducing the inherent water demand of

the mix and, (ii) replacing some of the

water with water reducers and

superplasticizer (Bryce Simons, 1995).

8. HIGH-RANGE WATER

REDUCER

High Range Water Reducer

(Superplasticizer) is an essential

component material for HPC, to ensure

adequate workability while achieving a

low water-cementitious material ratio.



Optimum dosage of superplasticizer is

determined by trial mixtures using varying

amounts of each additive as well as with

cement. It is also important to be sure that

the superplasticizer is compatible when

used in combination. Specific gravity of

high range water reducer is nearer to that

of water and therefore it can be easily

dispersed with water. Naphthalene and

melamine-based high-range water reducers

are mostly used in the production of HPC.

8.1 DOSAGE

Dosage of liquid high-range water reducer

for HPC generally varies from 5-20 lit/m3

(Aϊtcin et al., 1994). Dosage of 0.8 to 2%

by weight of cementitious material is

normally used for achieving required

workability. By using a polycarboxylate

based superplasticizer, water content in the

case of high strength concrete can be

reduced to about 130 to 140 lit/m3

of

concrete.

9. CURING

Proper curing regime of concrete should

be adopted to overcome the problems

associated with usual adoption of very low

water content and high cement content in

HPC mixes. Moisture loss from HPC is

maximum during the first 24 hours after

placement. Critical time to start forming of

plastic shrinkage cracks is around the

initial setting time. Therefore, HPC should

be cured at an early stage without applying

water directly on the exposed surface of

fresh concrete. Thus curing of HPC is

generally done in two-stages--initial curing

and wet curing. Water is not used directly

during the initial curing. Objective of

initial curing is to prevent moisture loss

from fresh concrete till the time wet curing

is started. An efficient method of initial

curing is to cover the fresh HPC by plastic

sheet. Wet curing ie., final curing is

adopted as for conventional concrete by

ponding water on the exposed surface [21].

10. CONCLUSIONS

Structures in aggressive marine

environments, harmful sub-soil conditions,

highly polluted industrial and urban areas

and other hostile environments require

HPC. Constituent materials greatly

influence various rheological, mechanical,

performance and fracture properties. Good

quality and specified materials should be

selected for optimum performance to

achieve the purpose. Based on the

technical review made in the present study,

the following conclusions are drawn.

(a) HPC needs more stringent control

on materials selection than

ordinary concrete to consistently

meet the performance criteria for

workability, strength, durability

and fracture properties.

(b) HPC requires materials of highest

quality and their optimum

proportions.

(c) Supplementary cementitious

materials which enhance the

properties of concrete by hydraulic

and pozzolanic activities are

essential from appropriate sources.

(d) Aggregates which occupy nearly

75% of the volume of concrete

must be properly taken care of.

Strong, sound, clean and well-

graded aggregate is essential.

(e) Water content, and its ratio with

cement play a major role in

achieveing the required properties.

(f) Microcracking at the interface

between the paste and aggregate is

fundamentally responsible for

reducing the long-term durability

of concrete. Bond between the

paste and aggregate can be

improved by dispersing the coarse

aggregate in the cement before

mixing with all other ingredients.

(g) HRWR can reduce the water

content without loss of workability.

It is necessary for high strength



concretes for producing flowing

concrete. It permits low water-

cement ratio and consequently

strength is increased.

(h) Not only the selection of proper

materials and mix proportioning

but mixing, placing and curing

practices determine the

performance of the product.

REFERENCES

[1] P.Kumar Mehta, “High

performance concrete durability affected

by many

factors”, 2001, PP.1-3.

[2] P.Kumar Mehta and P.C.Aitcin,

“Principles under laying the production of

High performance concrete”,

ASTM Cement, Concrete and

Aggregates, 1990, Vol.12, No.2,

PP.70-78.

[3] Md.Safinddin, M.N.Islam,

M.F.M.Zain and H.B.Mahmud,

“Materials aspects for High

strength and high performance

concrete”, International Journal of

Mechanical and Materials

Engineering, 2009, Vol.4, No.1,

PP.7-9.

[4] Surendra P Shaw, Stuart E Swartz,

and Chengsheng Ouyang,“Fracture

mechanics of concrete”, John wiley

& Sons, Inc., 1995.

[5] DiTommaso A, Evaluation of

concrete failure, In A.Carpinteri

and A.R.Ingraffea, editors,

“Fracture mechanics of concrete”,

Martinus Nijhoff Publishers,

Boston, 1984.

[6] M.R.L.Sastry, “Modified reactive

powder concrete”, 2009, PP.6-8.

[7] Raymond W M Chan, Peter N L

Ho & Eric P W Chan, “Report on

concrete admixtures for

waterproofing construction”,

Structural Engineering Branch –

Architectural Services Department,

December 1999, PP.16-20.

[8] A.R.Santhakumar, “Concrete

Technology”, 1st Edition-3

rd Impression

2009,

Oxford University Press, New

Delhi, India, PP.294.-297.

[9] A.M.Neville, “Properties of

Concrete”, 4th and final edition,

John Wiley & Sons, New York,

USA, Third Indian Reprint, 2004,

PP.86-89.

[10] M.L.Gambhir, “Concrete

Technology”, 3rd

Edition,1984,

Dhanpat Rai & Co.

(Pvt)Ltd.,Delhi, India, PP.450-474.

[11] Concrete Products, ”High

performance concrete mix

proportions”, 2004, PP.1-2.

[12] Dr.R.B.Khadiranaikar, “High

performance concrete”, 2001, PP.8-13.

[13] -----Guide for selecting proportions

for high strength concrete using

portland cement and other

cementitious materials, ACI

211.4R-2008, American Concrete

Institute, Farmington Hills,

Michigan, 2008.

[14] M.S.Shetty, “Concrete

Technology: Theory and Practice”, Reprint

2009,

S.Chand & Company Ltd,. New

Delhi, India, PP.323-330.

[15] V.S.Ramachandran, “Concrete

admixtures handbook : properties, science,

and technology”, Noyes Publishers,

2006, PP.63-65.

[16] -----Specification for coarse and

fine aggregates from natural

sources for concrete, IS 383:1970,

Bureau of Indian Standards, New

Delhi, India.



[17] Henry H C Wong and Albert K H

Kwan, “Packing density : a key concept

for

mix design of high performance

concrete”, 2004, PP.5-9.

[18] -----Code of practice for plain and

reinforced concrete, IS 456:2000, Bureau

of

Indian Standards, New Delhi,

India.

[19] Johan Magnusson, Mattias

Unosson, Anders Carlberg, “High

performance

concrete “, 2001, PP.9-10.

[20] -----Indian standard recommended

guidelines for concrete mix

proportioning (First Revision), IS

10262:2009, Bureau of Indian

Standards, New Delhi, India.

[21] Sai Prasad and Kamlesh Jha, “High

performance concrete”, 2005, PP.5-6.


Comparative Study on Secure Routing Protocols in MANETs

Ms. C. Geetha1 Dr. M. Ramakrishnan

2

1Associate Professor

Department of Computer Science & Engineering

R.M.K. Engineering College, Kavaraipettai, Chennai

[email protected]

2Professor & Head

Department of Information Technology

Velammal Engineering College, Surapet, Chennai

[email protected]

Abstract

Mobile Ad-Hoc Network is a set of mobile

nodes without any well defined

infrastructure and central authority to

control or monitor the functioning of mobile

nodes. Because of this nature, nodes can join

and leave whenever they want. Thus it forms

a dynamic topology. Nodes itself makes the

decision regarding the routing and packet

forwarding. Routing and packet forwarding

is a basic function of the MANETs. We

have a lot of protocols which are used to

perform this function. Security is a

significant aspect to be considered in the

MANET. A number of protocols which

implements security are also developed.

This paper presents a comparative study on

the security routing protocols with respect to

various parameters and security mechanisms

used.

Key Words: infrastructure, Routing, Packet

forwarding, dynamic topology, security

mechanisms.

1. Introduction

Nowadays more research is going on in the

area of secured routing in MANETs.

Routing protocols in MANETs are classified

into proactive (Table-driven) and reactive

(On-demand). In the former, frequently or in

the fixed time intervals the routing

information is exchanged. AODV, DSR,

TORA, ABR and SSR fall in this category.

In the latter, routing information are

exchanged when there is a need to a route or

when there is a link breakage. In this till the

end of the communication the route is

maintained. DSDV, OLSR and TBRPF fall

in this category. A third class of routing

protocol is hybrid that combines the

advantages of reactive and proactive.

Example is ZRP. Due to the limited power,

limited bandwidth, and resources, absence

of infrastructure dynamic topology, node

failure and link breakages, security is very

difficult in MANETs. While sending

messages between two nodes, the nodes in

MANETs are more vulnerable to any type of

attacks than the wired networks. The

remaining part of the paper is organized as

follows. Section 2 discusses about the

various security attacks. Section 3 presents

the various secured routing protocols.

Section 4 describes the summary report of

these protocols with respect to various

parameters and security mechanisms used.

Section 5 presents the conclusion.




2. Security Attacks

The attacks are of two types. Passive and

Active. Passive attacks are too difficult to

identify because they will not affect the

functioning of the network. It attempts only

to discover the information like IP address,

location of nodes etc. But active attacks

modify the data to be transmitted and also

affect the functioning of the network. It is

easy to recognize these type attacks.

Impersonation, DoS and Disclosure fall

under this.

Impersonation: nodes may be able to send

false routing information and acting as some

other trusted node. Black hole attack and

worm hole attacks are examples. A

malicious node uses the routing protocol to

advertise itself as having the shortest path is

black hole attack. Creation of a tunnel in the

network between two malicious nodes is

worm hole attack.

Denial of Service: routing table overflow

and sleep deprivation attacks are examples.

In the former, attacker creates to non-

existent nodes and makes the tables

overflow. In the later, attacker consumes the

batteries of other nodes by requesting routes

or by forwarding unnecessary packets.

Disclosure: In MANETs communication

between two nodes are taken place directly

if they are in the same frequency range;

otherwise intermediate nodes (hops)

involved in forwarding the packets. A node

that does not cooperate is called a

misbehaving node. Routing–forwarding

misbehaviors can be caused by nodes that

are malicious or selfish. A malicious node

does not cooperate because it wants to

intentionally damage network functioning

by dropping packets. On the other hand, a

selfish node does not intend to directly

damage other nodes, but is unwilling to

spend battery life, CPU cycles, or available

network bandwidth to forward packets not

of direct interest to it, even though it expects

others to forward packets on its behalf. Such

a node uses the network but does not

cooperate.

To cope with these problems, there is a need

for mechanisms that encourage/enforce

users to behave as „„good citizens‟‟, letting

their device relay packets for the benefit of

others, making their data available, and / or

lending support to the other computations.

In order to overcome these problems a

secure routing protocol is expected to meet

the following requirements.

Confidentiality: Only the intended receivers

should be able to interpret the transmitted

data.

Integrity: Data should not change during the

transmission process, i.e., data integrity

must be ensured.

Availability: Network services should be

available all the time and it should be

possible to correct failures to keep the

connection stable.

Authentication: Every transmitting or

receiving node has its own signature. Nodes

must be able to authenticate that the data has

been sent by the legitimate node.

Non-repudiation: Sender of a message shall

not be able to later deny sending the

message and that the recipients shall not be

able to deny the receipt after receiving the

message.

3. Secure Routing Protocols

Cryptographic systems are classified into

symmetric key and public key. In the

former, same key is used for both encryption



and decryption. But in later, one key is used

for encryption and one key is used for

decryption. Some of the protocols use the

symmetric key cryptography and some uses

the public key cryptography. There are some

protocols which uses the certificates and/or

digital signatures.

3. 1 ARAN – Authenticated Routing for Ad-

Hoc Networks. It uses public key

cryptography to defeat the attacks. It is an

on-demand routing protocol and consists of

a preliminary certification process followed

by a route instantiation process that

guarantees end-to-end authentication. The

protocol is simple compared to most non-

secured ad hoc routing protocols, and does

not include routing optimizations. Route

discovery in ARAN is accomplished by a

broadcast route discovery message. The

routing messages are authenticated end-to-

end and only authorized nodes participate at

each hop between source and destination.

ARAN uses trusted certificate server (T),

whose public key is known to all valid

nodes.

When a node enter into the network, it get a

certificate from T, which contains the IP

address of the node, its public key, a

timestamp of when the certificate was

created and a time at which the certificate

expires along with the signature by T.

T A: certA = [IPA, KA+,t,e]KT-

The source node begins route instantiation to

destination by broadcasting to its neighbors

a route discovery packet (RDP).

ABroadcast: [RDP,IPX, NA,] KA-,certA

The RDP includes a packet type identifier

(“RDP”), the IP address of the destination‟s

certificate, and a nonce, all signed with its

private key. Hop count is not included with

the message.

The receiving node uses public key, which it

extracts from A‟s certificate, to validate the

signature and verify that A‟s certificate has

not expired. The receiving node also checks

the (NA, IPA) tuple to verify that it has not

already processed this RDP. The receiving

node signs the contents of the message,

appends its own certificate, and forward

broadcasts the message to each of its

neighbors. The signature prevents spoofing

attacks that may alter the route or form

loops.

Let B be a neighbor that has received from

A the RDP broadcast, which it subsequently

rebroadcasts.

BBroadcast:[[RDP,IPX, NA,] KA-]KB-,

certA ,certB.

Upon receiving the RDP, B‟s neighbor C

validates the signatures for both, the RDP

initiator, and B, the neighbor it received the

RDP from, using the certificates in the RDP.

Then C removes B‟s certificate and

signature, records B as its predecessor, signs

the contents of the message originally

broadcast by A and appends its own

certificate. C then rebroadcasts the RDP.

CBroadcast:[[RDP,IPX, NA,] KA-]KC-,

certA,certC.

Since the messages are signed at each hop,

malicious nodes have no opportunity to

redirect traffic. Link failures and inactive

routes are intimated through ERR messages.

All ERR messages must be signed. A node

that transmits a large number of ERR

messages should be avoided. The nodes can

easily exchange the session keys using the

certificates and share a symmetric key

generated with their own private key and the

public key of this will reduce the

computational overhead and power

consumption. ARAN specifies that all fields

of RDP and REP packets remain unchanged



between source and destination. Thus,

modification attacks are prevented.

In ARAN, when a certificate needs to be

revoked, the trusted certificate server T

sends a broadcast message to the ad hoc

group that announces the revocation. Any

node receiving this message re-broadcast it

to its neighbors. Revocation notices need to

be stored until the revoked certificate would

have expired normally. Any neighbor of the

node with the revoked certificate needs to

reform routing as necessary to avoid

transmission through the now un-trusted

node.

The disadvantage of this protocol is that the

malicious nodes also have the opportunity in

ARAN to lengthen the measured time of a

path by delaying REPs as they propagate, in

the worse case by dropping REPs, as well as

delaying routing after path instantiation.

ARAN suffers from larger control overhead

due to certificates and signatures stored in

packets. The cryptographic operations cause

additional delays at each hop, and so the

route acquisition latency increases. ARAN

is not immune to the wormhole attack.

3.2 ARIADNE – It is an on-demand secure

ad hoc routing protocol based on DSR. It

relies on symmetric cryptography. It uses

MACs (Message Authentication Code)

derived from shared secret keys to verify the

integrity of the original message. They also

excluded any kind of physical layer or

application layer attacks.

The source sends an 8 tuple to find the path.

All intermediate nodes receive the request

and verify the shared key for that particular

interval specified in the request. This checks

the freshness of the request. Every node

finds a hash using the shared key and

attaches it with the request. Upon arrival at

the destination, the target determines the

validity of the request by checking, that the

keys for the time interval have not yet been

disclosed and that the hash chain field is

consistent. If the request is valid a RREP is

sent to the initiator. When the initiator

receives the RREP, he verifies the validity

of each key in the key list, the target MAC

and of each MAC in the MAC list. If all

tests succeed the RREP is accepted, if not

the packet is discarded.

ARIADNE copes with attacks performed by

malicious nodes that modify and fabricate

routing information, with attacks using

impersonation. The advanced version, using

an extension called TIK (TESLA with

Instant Key disclosure) that requires tight

clock synchronization between the nodes,

overcomes the wormhole attack. Selfish

nodes are not taken into account. Ariadne

does not strive to achieve privacy

3.3 CONFIDANT - CoOperation of Nodes,

Fairness In Dynamic Ad-hoc NeTworks. It

is an extension of DSR. It detects malicious

nodes by means of combined monitoring

and reporting and establishing routes by

avoiding misbehaving nodes. CONFIDANT

consists of the following components, The

Monitor, the Reputation System, the Path

Manager, and the Trust Manager. The

components are present in every node.

Each node monitors the behavior of its next-

hop neighbors. If a suspicious event is

detected, the information is given to the

reputation system. If the event is significant

for the node, it is checked whether it has

occurred more often than a predefined

threshold. If the occurrence threshold is

exceeded, the reputation system updates the

rating of the node that caused the event. If

the rating turns out to be intolerable, the

information is relayed to the path manager,

which proceeds to delete all routes

containing the intolerable node from the

path cache. An ALARM message is sent by

the trust manager component. This message

contains the type of protocol violation, the



number of occurrences observed, whether

the message was self-originated by the

sender, the address of the reporting node, the

address of the observed node, and the

destination address (mostly the source).

When the monitor component of a node

receives such an ALARM message, it passes

it on to the trust manager, where the source

of the message is evaluated. If the source is

at least partially trusted, the table containing

the ALARMs is updated. If there is

sufficient evidence that the node reported in

the ALARM is malicious, the information is

sent to the reputation system where it is

again evaluated for significance, number of

occurrences, and accumulated reputation of

the node.

The limitations of CONFIDANT lie in the

assumptions for detection-based reputation

systems. Events have to be observable and

classifiable for detection, and reputation can

only be meaningful if the identity of each

node is persistent, otherwise it is vulnerable

to spoofing attacks.

3.4 CORE – A Collaborative Reputation

Mechanism to enforce node cooperation in

Mobile Adhoc Networks. It uses the DSR

routing protocol. CORE is suggested as a

generic mechanism that can be integrated

with any network function like packet

forwarding, route discovery, network

management, and location management.

Each network entity in CORE keeps track of

other entities collaboration using a technique

called reputation. The reputation metric is

computed based on data monitored by the

local entity and some information provided

by other nodes involved in each operation.

Each node of the network monitors the

behavior of its neighbors with respect to a

requested function and collects observations

about the execution of that function. From

the collected observations each node

determines a reputation value for all its

neighbors. The trusted nodes have positive

reputation value and malicious nodes have

negative reputation value. Reputation table

is used to store these values. Each row

consists of four entries: the unique identifier

of the entity, a collection of recent

subjective observations made on that entity's

behavior, a list of the recent indirect

reputation values provided by other entities

and the value of the reputation evaluated.

CORE considered only selfishness as a

specific issue to address: selfish nodes do

not intend to directly damage other nodes

while the misbehavior is due to their need to

save battery life for their own

communications. It detects the misbehavior

nodes at the forwarding level.

CORE suffers from the spoofing attack.

Misbehaving nodes are not prevented.

Furthermore, no simulation results prove the

robustness of the protocol. It is an original

approach based on game theory.

3.5 COSR – It is based on DSR. It uses

route reputation to choose the best route

path. Nodes reputation depends on the

information from physical layer, MAC layer

and network layer and it can be computed by

nodes capability of forwarding, history

action etc. COSR can be divided into

monitor, statistics, reputation model,

reputation protocol and routing protocol.

The monitor includes three modules:

Neighbor monitor works with MAC layer

and it monitors neighbors in its radio range

and maintain neighbor list. Data relay

monitor is placed in the network layer. It

could check whether the next hop had

transmitted its packets. CoF would collect

information about capability of forwarding

from physical layer and MAC layer and it

includes node‟s bandwidth, interface state,

mobility status and power. Statistics is

responsible for providing statistics data

about neighbor‟s history behavior.

Reputation model used to evaluate node‟s

reputation. Reputation protocol with routing



protocol and uses routing protocol to

pigback reputation control message and

data. Routing protocol choose the best route

path.

It deals with blackhole, selfish and DoS. The

COSR uses a novel reputation model to

detect malicious and selfish nodes and make

all nodes more cooperative. Further,

reputation is not only used to evaluate the

trustworthiness of any node, but also to

describe its CoF. Due to such design, COSR

can protect network against the primary

routing attacks and balance load on all

secure route paths to avoid hotpoint and

enlarge throughput of whole network

consequently.

3.6 RAODV – Reliable Ad hoc On-demand

Distance Vector. It is an extension of

AODV. It protects the network against

attacks by selfish nodes and malicious nodes

exhibiting black hole attack and replay

attack. In addition to the RouteRequest and

RouteReply used by AODV, RAODV uses

two types of control packets: Reliable Route

Discovery Unit (RRDU) and RRDU Reply

(RRDU_REP). No node other than the

destination can generate RRDU_REP on

behalf of the destination. A field Reliability

List (RL), a triplet (Source address, FDPC,

RRDU-ID) is added in the routing table

entry. Path discovery in RAODV can be

thought of as consisting of two phases.

Phase I is same as that in AODV. In Phase

II, source sends the RRDU to all the nodes

from which it receives the RREPs. Only the

destination will reply. To maintain the

reliability of the path we have introduced the

field FDPC in the routing table. This count

is used to find the selfish nodes.

When a malicious node send RREP to the

source even it does not have the route to the

destination, the source send the RRDU to

this node. Since no one other than the

destination can generate RRDU_REP, the

malicious node can‟t generate the reply and

hence the route through the malicious node

is not selected.

3.7 SAODV - Secure Ad hoc On-Demand

Distance Vector Routing. SAODV is an

extension of the AODV routing protocol that

can be used to protect the route discovery

mechanism providing security features like

integrity, authentication and non-

repudiation.

SAODV assumes that each ad hoc node has

a signature key pair from a suitable

asymmetric cryptosystem. Further, each ad

hoc node is capable of securely verifying the

association between the address of a given

ad hoc node and the public key of that node.

Achieving this is the job of the key

management scheme.

Two mechanisms are used to secure the

AODV messages: Digital signatures to

authenticate the non-mutable fields of the

messages, and hash chains to secure the hop

count information. Every node (generating

or forwarding a route error message) uses

digital signatures to sign the whole message

and that any neighbor that receives verifies

the signature.

3.8 SEAD - Secure Efficient Ad hoc

Distance Vector routing protocol is based on

DSDV and hence consumes network

bandwidth in exchanging routing tables

among nodes. SEAD handles malicious

node but not selfish node. Replay attacks are

also taken into account. SEAD uses efficient

one-way hash chains and Merkle hash trees

and not asymmetric cryptographic

operations. It authenticates the sequence

number and metric of a routing table update

message using hash chains elements. A node

cannot advertise a route better than those for

which it has received an advertisement,

since the metric in an existing route cannot

be decreased due to the on-way nature of the

hash chain.



The source of each routing update message

in SEAD must also be authenticated, since

otherwise, an attacker may be able to create

routing loops through the impersonation

attack.

It uses two schemes: TESLA and MAC

assuming a shared secret key between each

pair of nodes

SEAD does not cope with wormhole attacks.

3.9 SLSP - Secure Link State Routing

Protocol. It based on Link-state protocol and

provides correct (i.e., factual), up-to-date,

and authentic link state information, robust

against Byzantine behavior and failures of

individual nodes.

SLSP protects link state update (LSU)

packets from malicious alteration. Nodes

periodically broadcast their certified key, so

that the receiving nodes validate their

subsequent link state updates. SLSP defines

a secure neighbor discovery that binds each

node to its Medium Access Control (MAC)

address and its IP address, and allows all

other nodes within transmission range.

3.10 SRP – Secure Routing Protocol. SRP is

an extension compatible with a variety of

existing reactive routing protocols. SRP

relies on the availability of a security

association (SA) between the source node

(S) and the destination node (T). The SA

could be established using a hybrid key

distribution based on the public keys of the

communicating parties. SRP copes with

non-colluding malicious nodes that are able

to modify (corrupt), replay and fabricate

routing packets.

The basic version of SRP suffers from the

route cache poisoning attack. Route error

packets are not verified. The neighbor

discovery mechanism maintains information

on the binding of the medium access control

and the IP addresses of nodes, SRP is

proven to be essentially immune to IP

spoofing. SRP is not immune to the

wormhole attack: two colluding malicious

nodes can misroute the routing packets on a

private network connection and alter the

perception of the network topology by

legitimate nodes.

4. Summary of secure Routing Protocols

We summarize the secure routing protocols

explained in the section 3. Each protocol

deals with different types of attacks, uses

different security mechanisms, and solves

one or more attacks and produce efficient

routing and forwarding of packets. Each one

has its own advantages and disadvantages.

The Table 1 summarizes base protocol used,

type of cryptography used, and the security

requirements satisfied by these protocols.

Table 2 gives the various attacks prevented

and detected by these protocols.



Table 1

Table 2 Secure Routing

Protocols

Attacks Deals with Targeted Layer Assumptions Essential Requirements

ARAN Routing Attacks,

Impersonation and

Repudiation

Network,

Application and

Multi-layer

Trusted certificate

server

Online trusted certification

authority

ARIADNE Routing, DoS Network, Multi-

layer

Nodes have loosely

synchronized clocks

TESLA

CONFIDANT Detecting &

isolating

misbehaving nodes

Network, Multi-

layer

Network layer is

based on DSR

Trust calculation

CORE Selfish nodes, DoS Network Bidirectional

communication links

COSR Malicious & selfish

nodes, Routing

attacks

Network Bidirectional

communication

links, Nodes work in promiscuous mode

promiscuous mode

RAODV Malicious & selfish

nodes, Routing

attacks, black hole

and replay attacks

Network A node can‟t

impersonate -

SAODV Black hole attack Network Network should

have distributing

system

Online key management

scheme

SEAD Routing, DoS and

Resource

consumption

Network and Multi-

layer

Secure way of

delivering initial

secrete key, KN

Clock synchronization

SLSP DoS Network Single network

interface per node

TTP

SRP Location disclosure Network Secure way of

delivering Security

Association

Security association between

source and destination

Secure

Routing

Protocols

Base

Protocol

Cryptography Scheme

Used

Security Requirements

confidentiality integrity authentication non-

repudiation ARAN AODV Cryptographic Certificates - Yes Yes Yes

ARIADNE DSR TESLA & MAC - Yes Yes -

CONFIDANT DSR Reputation values - Yes Yes Yes

CORE DSR Reputation values - Yes - -

COSR DSR Reputation values - - - -

RAODV AODV Control Packets & Packet

count - - - -

SAODV AODV Symmetric/asymmetric &

hash link - Yes Yes Yes

SEAD DSDV One way hash function - - Yes -

SLSP Hybrid Digital signature & One

way hash chain - - Yes -

SRP Many on-

demand

protocols

Security association

between nodes - Yes Yes -



5. Conclusion

Security is a major issue in Mobile AdHoc

Networks. A lot of protocols have been

developed to solve the basic requirements

of security like integrity, confidentiality,

authentication and non-repudiation. All the

protocols are distinct and they have their

own mechanisms, advantages and

disadvantages. Each protocol improves the

efficiency of the security measures

(parameters) like the routing delay, end-to-

end delay, path length, throughput (packet

delivery ratio) and overhead on its own

way. In this paper we have analyzed ten

different secure routing protocols and the

mechanisms used and summarize all the

details.

6. References

[1] C. Siva Ram Murthy and B. S. Manoj,

“Ad Hoc Wireless Networks,

Architectures and Protocols,” first Indian

reprint 2005,pearson publication. ISBN

81-297-0945-7

[2] Yih-Chun Hu ,David B. Johnson ,

Adrian Perrig “SEAD: secure efficient

distance vector routing for mobile wireless

ad hoc networks”, 1570-8705/$ 2003

Published by Elsevier B.V.

doi:10.1016/S1570-8705(03)00019-2

[3] Manel Guerrero Zapata:"Secure Ad

hoc On-Demand Distance Vector

(SAODV) Routing" INTERNET-DRAFT

draft-guerrero-manetsaodv - 06.txt.

September 2006.

[4] Sonja Buchegger, JeanYves Le

Boudec,

“Performance Analysis of the

CONFIDANT

Protocol (Cooperation Of Nodes: Fairness

In

Dynamic Adhoc NeTworks)”,

MOBIHOC’02,June 911, 2002, EPFL

Lausanne, Switzerland.Copyright 2002

ACM 1581135017/ 02/0006.

[5] Hu, Yih-Chun, Adrian Perrig, and

Dave Johnson. "Ariadne: A Secure On-

Demand Routing Protocol for Ad Hoc

Networks." In Proceedings of the Eighth

Annual International Conference on

Mobile Computing and Networking (ACM

Mobicom), Atlanta, Georgia, September

23 - 28, 2002

[6] Kimaya Sanzgiri, Daniel LaFlamme,

Bridget Dahill, Brian Neil Levine, Clay

Shields and Elizabeth M. Belding-Royer

“Authenticated Routing for Ad Hoc

Networks” In IEEE JOURNAL ON

SELECTED AREAS IN

COMMUNICATIONS, VOL. 23, NO. 3,

MARCH 2005

[7] Pietro Michiardi – Refik Molva

“CORE: A Collaborative Reputation

Mechanism to enforce node cooperation in

Mobile Adhoc Networks” Institut

Eurécom 2229 Route des Crêtes - BP 193

06904 Sophia-Antipolis, France,

December 2001

[8] FeiWang, FurongWang, Benxiong

Huang and Laurence T. Yang “COSR: A

Reputation-Based Secure Route Protocol

in MANET” EURASIP Journal on

Wireless Communications and Networking

Volume 2010, Article ID 258935, 10

pages doi:10.1155/2010/258935

[9] Sandhya Khurana, Neelima Gupta,

Nagender Aneja, “Reliable Ad-hoc On-

demand Distance Vector Routing

Protocol” Proceedings of the Fifth

International Conference on Networking

(ICN 2006), The International Conference

on Systems (ICONS 2006), and The First

International Conference on Mobile

Communications and Learning (MCL

2006) 0-7695-2522-2/06 $20.00 © 2006

IEEE

[10] Panagiotis Papadimitratos, Zygmunt

J. Haas “Secure Link State Routing for

Mobile Ad Hoc Networks”

[11] Panagiotis Papadimitratos and

Zygmunt J. Haas “Secure Routing for

Mobile Ad hoc Networks” In Proceedings

of the SCS Communication Networks and

Distributed Systems Modeling and

Simulation Conference (CNDS 2002),

San Antonio, TX, January 27-31, 2002

[12] UMANG SINGH, “Secure Routing

Protocols In Mobile Adhoc Networks-A

Survey And Taxanomy” International



Journal of Reviews in Computing 30th

September 2011. Vol. 7

[13] Rajender Nath, Pankaj Kumar Sehgal

“A Review of Secure Routing Protocol in

Mobile Ad Hoc Network” In International

Journal of Computer Science & Emerging

Technologies (E-ISSN: 2044-6004)

Volume 1, Issue 4, December 2010

[14] Loay Abusalah, Ashfaq Khokhar, and

Mohsen Guizani “A Survey of Secure

Mobile Ad Hoc Routing Protocols” IEEE

Communications Surveys & Tutorials,

Vol. 10, No. 4, Fourth Quarter 2008

[15]L.Ertaul, D.Ibrahim, “Evaluation of

Secure Routing Protocols in Mobile Ad Hoc

Networks (MANETs)”

[16] Sonia Boora1, Yogesh Kumar2,

Bhawna Kochar, “A Survey on Security

Issues in Mobile Ad-hoc Networks”

IJCSMS International Journal of Computer

Science and Management Studies, Vol. 11,

Issue 02, Aug 2011ISSN (Online): 2231-

5268

A Novel Quasi-Orthogonal Stbc For 4 Transmit Antennas Using Lattice Decoding


A NOVEL QUASI-ORTHOGONAL STBC FOR 4 TRANSMIT

ANTENNAS USING LATTICE DECODING G.KANIMOZHI

1 AND K.SENTHIL KUMAR

2

Department of Electronics and Communication Engineering

Rajalakshmi Engineering College, Chennai - 602105

E-mail 1 : [email protected]

E-mail 2: [email protected]

Abstract— This paper presents a novel

Quasi Orthogonal Space Time Block Code

(QOSTBC) for four transmit antennas

using lattice decoding. Quasi Orthogonal

Space Time Block Code (QOSTBC)

belong to the class of Non- Orthogonal

Space Time Block Code (NOSTBC) and

have been extensive area of research. It

achieves full diversity for more than 2

antennas using rotated constellation. A

novel method of extending QOSTBC

constructed for 4 transmit antennas to a

closed-loop scheme is proposed. By

multiplying the entries of QOSTBC code

words by the appropriate phase factors

which depend on the channel information,

the transmit diversity of the proposed

scheme with one bit feedback is improved.

The proposed system uses lattice decoding

algorithm to obtain better bit error rate

compared to the existing methods and

reduced the computational complexity.

Index Terms— QOSTBC, closed loop,

lattice decoding, feedback, wireless

communication, Bit error rate.

I. INTRODUCTION

Multiple-Input and Multiple-Output

(MIMO), is the use of multiple antennas

at both the transmitter and receiver to

improve the performance of the

communication system. For an arbitrary

complex constellation such as PSK and

QAM, space–time block codes are

designed that achieve 1/2 of the maximum

possible transmission rate for any number

of transmit antennas. It is proved that a

complex orthogonal design and the

corresponding space–time block code

which provides full diversity and full

transmission rate is not possible for more

than two antennas[2]. Various QOSTBC

have been proposed to achieve full rate for

more than 2 antennas at the expense of

losing the diversity gain and increased

decoding complexity [3]. Although a lot of

partial feedback method can be adopted to

improve the closed loop system , the major

problem is high cost and high complexity

[6], [8]. For open-loop communication

systems, the optimum constellation

rotation proposed for QOSTBC with

different modulation schemes is the one of

good diversity improvement approaches.

With the quasi-orthogonal structure, the

quasi-orthogonal STBCs still have a fast

ML decoding, but do not have the full

diversity [2], [4]. The code can guarantee

full diversity but the upper bound is

achieved only for four transmit

antennas[9]. Recently lot of researches

have been put into designing the Space

Time Block Code (STBC) with full rate

and full diversity for four transmit

antennas.

Alamouti proposed one kind of

space time coding scheme which uses two

antennas in transmitting end. This method

could maximize the diversity gain and the

full emission rate by using the simple



maximum likelihood decoding in the

receiving end [1]. The maximum-

likelihood (ML) decoding of QO-STBC

can be performed by searching over pairs

only, instead of the full set, of the possible

transmitted complex symbols.

Subsequently, coordinate interleaved

orthogonal design (CIOD) and asymmetric

CIOD (ACIOD) have been proposed . For

practical interests of the design of the

closed loop transmission scheme, it is

desirable to have features such as limited

amount of feedback , low decoding delay ,

low cost and simple decoding method.

The proposed work aims at designing a

closed loop Quasi Orthogonal Space Time

Block code for four transmit antennas to

yield better bit error rate. Besides the

proposed system has reduced decoding

complexity compared to the existing

decoding methods and also achieves full

diversity. The proposed system overcomes

the limitations mentioned in the existing

systems .

In this paper , Section II provides the

system model , Section III the proposed

scheme , Section IV shows the simulation

results and Section V the conclusion.

II.SYSTEM MODEL

We consider the system which consists of

four transmit antennas and one receive

antenna. For the simplicity purpose one

receive antenna is considered but it can be

applied for M receive antennas. The

encoding is done using N transmit

antennas and Quasi Orthogonal Space

Time Block Code. At one time period Kb

bits arrive at the encoder where K is the

number of variables in the transmission

matrix. We emphasize that all the

transmissions are simultaneous and they

have same time duration.

In this section, a quasi-static flat

fading channel with four transmit antennas

and one receive antenna is considered. The

(4*4) QOSTBC is given by

(1)

where S12 and S34 are the two (2 × 2)

building blocks based on the Alamouti

scheme of two transmit antennas,

and

By substituting S12 and S34 we get,

(2)

The received signal during four successive

time slots is given as

(3)

Where the noise samples and the entries

of HJ are independent samples of a zero-

mean complex Gaussian random variable

of variance 1. By using the circulant

matrix the closed loop scheme can be

obtained . .



After multiplying the SJ by the phase

factors we get

(4)

III. PROPOSED SCHEME

The receiver send some information about

the channel back to the transmitter through

a feedback channel. This is known as

closed loop system .The transmitter can

use the information provided by the

receiver to improve the performance. The

received signal is given as

(5)

The circulant matrix C4 is given as

(6)

The grammian matrix is represented as

(7)

Where Up is the channel gain matrix and

Vp is the interference matrix.

Fig 1 Proposed closed loop QOSTBC for

4 transmit antennas using lattice decoding

The block diagram of the proposed

closed loop QOSTBC scheme for 4

transmit antennas using lattice decoding is

depicted in the fig 1. The input bits are

taken and they are mapped by using

either Quadrature Amplitude Modulation

(QAM) or Quadrature Phase Shift Keying

(QPSK). The mapped symbols are

encoded using the lattice encoder . The

symbols S1,S2,S3,S4 are multiplied by the

corresponding phase factors. After

multiplying by the phase factors the

symbols are transmitted through the

respective transmit antennas Tx1,Tx2,Tx3

and Tx4 . The h1, h2 ,h3.h4 are the

channel gain of the respective antenna.

The channel state checker checks the

condition of F(H) where,

F(H) = Re(h1* h4) .Re(h2 h3* )

Assuming we know the channel

information at the receiver and we adopt

one bit k = 0 or 1 to indicate Re(h1* h4)

.Re(h2 h3* ) >=0 or

Re(h1* h4) .Re(h2 h3* )< 0.Then this

one bit information will be fed back to the

transmitter. Supposing the system channel

is quasi-static flat fading channel, at the

transmitter we first judge the value of k



K α β θ γ

Re(h1

*h4).Re(h2h3*)

>=0

0 Π 0 0 Π

Re(h1

*h4).Re(h2h3*)

< 0

1 0 0 0 Π

Table 1 Channel state checker

The closed loop system helps to improve

the performance of the MIMO system.

The proposed scheme can be applied for

all the types of existing QOSTBC.

A. LATTICE DECODING

Lattice is a regularly spaced array of

points L = {Bx|x∈Zn}, B∈Rn×n called

basis. Lattice decoder is particularly

attractive for bandwidth efficient

modulations, such as M-PAM and M-

QAM, due to its various desirable

properties including:

its decoding complexity is

independent of the modulation

alphabet size M

its performance is nearly optimal,

especially for large M

its average complexity is quadratic,

as the signal-to-noise ratio tends to

infinity.

The applications of lattice decoders have

proliferated in the past decade because of

the growing importance of some linear

channel models, such as intersymbol

interference channels, fading channels,

uncoded and space-time block coded

multiple-antenna channels , multiuser

CDMA channels, dispersive multiple-

antenna channels and their combinations.

The closest (lattice) vector problem (CVP)

(also called the nearest lattice point

problem) is a class of nearest neighbour

searches or closest-point queries, in which

the solution set to be searched consists of

all the points in a lattice. A general

solution for the CVP was proposed by

Kannan and was originally developed for

solving some integer programming

problems. Kannan was mainly interested

in deriving theoretical results on the worst-

case complexity. His algorithm does not

lead to an efficient practical solution to

the CVP. However the underlying ideas

are simple and powerful, consisting of two

steps:

Step 1: For the given lattice, find a short

and fairly Orthogonal basis, called the

reduced basis.

Step 2: Enumerate all lattice points falling

inside a certain sphere centered at the

query point so as to identify the closest

lattice point.

The procedure that transforms a lattice

basis into a reduced one is known as the

basis reduction algorithm, while the one

achieving the second step is called the

enumeration algorithm.

Lattice algorithms related to the CVP have

also been widely applied in cryptoanalysis

applications, where the algorithmic

complexity is of both practical and

theoretical significance. In cryptoanalysis,

it is well-known that choosing a good

lattice basis is important to finding a good

nearby lattice point, which can in turn

speed up the closest lattice point search

significantly. A straightforward method to

find the closest lattice point is to

enumerate all lattice points falling inside a



sphere centered at the query point so as to

identify the closest lattice point in the

Euclidean metric.

One important feature of lattice

codes is that they can be decoded by a

class of efficient decoders known as lattice

decoders. Lattice decoding algorithms

disregard the boundaries of the lattice code

and find the point of the underlying

(infinite) lattice closest (in some sense) to

the received point. If a point outside the

lattice code boundaries is

found, an error is declared. Lattice

decoding allows for significant reductions

in complexity, compared to ML decoding,

since

1) it avoids the need for complicated

boundary control and

2) it allows for using efficient

preprocessing algorithms (e.g.,the

Lenstra–Lenstra–Lovász (LLL)

algorithm )which are known to

offer significant complexity

reduction.

IV. SIMULATION RESULTS

The open loop system for the Quasi

orthogonal Space Time Block Code and

Orthogonal space time block code using

Quadrature Phase Shift Keying were

simulated using MATLAB 7.10.0

(R2010a).The decoding used was

Maximum Likelihood decoding. The

graph obtained is depicted in fig 2

Table 2 : Simulation parameters

Fig 2 BER Performance of QOSTBC and

OSTBC

From the graph it is concluded that

QOSTBC has better BER performance

compared to OSTBC . The QOSTBC has

the BER value of 10-5

for the Eb/No value

of 20 dB.

Fig 3 BER performance closed loop

QOSTBC using lattice decoding and ML

decoding

0 2 4 6 8 10 12 14 16 18 2010

-6

10-5

10-4

10-3

10-2

10-1

100

Eb/No,dB

BE

R

OSTBC

QOSTBC

0 2 4 6 8 10 12 14 16 18 2010

-5

10-4

10-3

10-2

10-1

100

EbNo,dB

BE

R

QOSTBC USING ML DECODING

QOSTBC USING LATTICE DECODING

PARAMETERS TYPES

Modulation

Techniques QPSK

Antennas 4 Tx, 1 Rx

Channel

Rayleigh

Distribution

Noise

AWGN Values(0-

1)



The fig 3 shows that closed loop

QOSTBC using lattice decoding has

better BER performance when compared

to QOSTBC using ML decoding .The

closed loop QOSTBC using lattice

decoding has BER value of 10-5

for the

Eb/No value of 20 dB.

V. CONCLUSION

The open loop system was

simulated using ML decoding for OSTBC

and QOSTBC systems and it was

concluded that QOSTBC has better BER

performance. The BER performance of

closed loop QOSTBC using ML decoding

and lattice decoding was simulated and

the results shows that closed Loop

QOSTBC using lattice decoding has

better BER performance and reduced

decoding complexity.

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April 2010

A Novel Method Of Mri Brain Image Segmentation


A NOVEL METHOD OF MRI BRAIN IMAGE SEGMENTATION

Arun pandiyan ks1, Babu.g2

1M.E (APPLIED ELECTRONICS) 2 ASST PROF (ECE DEPT)

R.M .K ENGINEERING COLLEGE R.M .K ENGINEERING COLLEGE

[email protected] [email protected]

Abstract--- The accurate and effective

algorithm for segmenting image is very

useful in many fields, especially in

medical image. In this paper we introduced

a novel method that focus on segmenting

the brain MR Image that is important for

cancer and neural diseases. Segmentation

of MRI brain images plays a critical role in

medical image processing and analysis

.The research on MRI brain image

segmentation has been an important field

in medical image processing and analysis.

It does great help to early diagnosis and

treatment of neurological diseases. MRI

brain image are theoretically piecewise

constant with a small number of classes.

They can have relatively high contrast

between different tissues. At present, a

variety of approaches and processing

techniques have been proposed for the

MRI images segmentation, such as

watershed method, artificial neuron

network method , methods based on

Markov Random Field model , and

methods based on mathematical

morphology algorithmic method. By

applying the advantage of both EM and

FCM algorithm for decreasing the

influence of the inhomogeneity and

increasing the segmenting accuracy. With

simulate image and the clinical MRI data,

the experiments shown that our proposed

algorithm is effective.

Keywords--- Unsupervised classification,

fuzzy clustering, brain MRI, image

segmentation.

I. INTRODUCTION

Segmentation of MRI brain images

plays a critical role in medical image

processing and analysis the research on

MRI brain image segmentation has been

an important field in medical image

processing and analysis. It does great help

to early diagnosis and treatment of

neurological diseases. MRI brain image

are theoretically piecewise constant with a

small number of classes. They can have

relatively high contrast between different

tissues. At present, a variety of approaches

and processing techniques have been

proposed for the MRI images

segmentation, such as watershed method ,

artificial neuron network method ,

methods based on Markov Random Field

model , and methods based on

mathematical.

In this project we propose MRI

segmentation method for detecting

cancers, tumors .They are various

segmentation method is existing. In this

project we are developing a new

segmentation method by combining the

two different algorithms by taking the

advantage of these algorithms for better

features in image segmentation.

Recently, many people use the MRI data

to research the relation between white

matter development and neural diseases,

especially, [8]the anatomy image is fusing

with those images from diffusion tensor

imaging, and using the white matter to

lead the fibre tack, the accuracy of

segmenting white matter is key problem.

Attention deficit hyperactivity disorder

(ADHD)[6]

is also needed to segment

white matter. In spite of many algorithms

for segmenting MRI of data, such as

watershed algorithm, eSneke algorithm,



generic algorithm. In addition, those

algorithms are based on the homogeneity

of image. [2]In fact, intensity

inhomogeneity is impact on every image

and we have to solve the problem with

new method. Wells

developed a new

statistical approach based on the EM

algorithm, but the results are too

dependent on the initial values, extremely

consuming the time and just looking for

local maximum point. By formulating the

modifying objective function of the

standard FCM algorithm to compensate for

such inhomogeneities.

II. METHODS

2.1 Model of fuzzy c-mean method (FCM)

The standard FCM is an iterative,

unsupervised clustering algorithm, initially

developed by FCM algorithm, introduced

by Bezdek[4]. The following model of

FCM is described by Ahmed[1].

The Observed MRI signal is modeled

as a product of the true signal generated by

the underlying anatomy, and a spatially

varying factor called the gain field

k k kY X G {1,2, , }k N

(1)

groups the values kX , kY and kG are the true

intensity, observed intensity and the gain

field at the kth voxel, respectively. [8] N is

the total number of pixels in the MRI

volume.

The application of a logarithmic

transformation to the intensities allows the

artifact to be modeled as an additive bias

field

k k ky x {1,2, , }k N

(2)

Where kx and ky are the true and

observed log-transformed intensities at the

kth voxel, respectively, and k is the bias

field at the kth voxel. If the gain field is

known, then it is relatively easy to

estimate the tissue class[5] by applying a

conventional intensity-based segmentation

to the corrected data. The following

discussion is based the model of (2) and

estimation of the gain field k .For

clustering. The grey-level histogram of the

sum image S is used as input for clustering

New extension for FCM

In FCM_EN, average image x is

replaced with edge preserving average

image. The extension is named

FCM_ENE[3].Incorporating neighborhood

distance improves the performance of

clustering methods in high level of noise

but due to blurring effect; degrade the

performance of them in

low noise level. In other hand, the

experiment show that in low level of noise

result of FGFCM[11] is better than

ordinary FCM. [10]As result, the variance

of noise is used as a threshold to

automatically trade between use of new

method and FGFCM as follow:

FCM _ ENE = (δ 2 <= .5) * FGFCM + (δ

2 > .5)

III. EXPRIEMENT AND RESULT

FCM and EM are most popular

clustering methods. Traditional clustering

methods just consider intensity

information and have not good results in

presence of noise[9]. Using spatial

information is one solution to overcome

this problem. In this paper, extensions for

FCM and EM are introduced. In

introduced algorithms, neighborhood

information is incorporated in clustering

process.

Our algorithms are applied on simulated

MRI images, with different noise levels.

The performance of FCM-EN, FCMFG

and introduced algorithms are compared

qualitatively. The similarity parameter is

exploited and measured the segmentation

results.



In this proposing method collection of

MRI image from the patient (DICOM)

using GE software .The second step is

conversion of DICOM format into jpeg or

bitcom format using (RADIANT) software

after the conversion develop coding using

the algorithm. After that coding is applied

MATLAB software. Initially we have

developed coding using EM algorithm for

the collected Data.

SIMULATION RESULTS

Step 1

MRI image from the patient (DICOM)

viewed through (GE) Software as shown

in figure1.

Figure. 1 Dcm of MRI brain Image

Step 2

Conversion of MRI Dicom format into

JPEG or BITCOM format Using

(RADIANT) Software shown in figure2.

Figure. 2 converted (JPEG) format MRI

image

Step 3

Image is applied to the MATLAB using

EM algorithm and the intensity

distribution level is calculated in figure3.

Figure3 output image with different

intensity level

IV. CONCULSIONS & FUTURE

WORK

EM is useful for several reasons:

conceptual simplicity, ease of

implementation. The rate of convergence

on the first few steps is typically quite

good, but can become excruciatingly slow

as you approach a local optima. Generally,

EM works best when the fraction of

missing information is small and the

dimensionality of the data is not too large.

EM can require many iterations, and

higher dimensionality.

Expectation-maximization (EM) and

fuzzy c-mean (FCM) are the most popular

fuzzy clustering algorithms. EM algorithm

is used for segmentation of brain MR. EM

algorithm models intensity distribution as

normal distribution of image, which is

untrue, especially for noisy images. FCM

just consider intensity of image and in

noisy images, intensity is not trustful.

Therefore, this algorithm has not good

result in low contrast, in-homogeneity and

noisy images. Many algorithms introduced

to make FCM robust against noise but

nevertheless most of them were and are

flawless to some extent Sometimes, due to

in-homogeneity, low contrast, noise and



inequality of content with semantic,

automatic methods fail to segment image

correctly. Therefore, for these images, it is

necessary to use user help to correct

method‟s error. When the real data are

fuzzy, such as functional MRI brain data,

the use of M-FCM segmentation is always

more effective than the use of the other

one. Further quantitative validation on

more accuracy and stability of the method

is still necessary, using realistic phantoms

and a large number of clinical scans.

The results presented in this paper are

preliminary and further clinical evaluation

is required. There are also need new

methods for preprocessing the original

image, including denoising and enhancing

to increase the SNR. How to combine

segmenting with preprocessing procedure

is our work in future.

REFERENCES

[1] M. N. Ahmed, S. M. Yamany, “A

Modified Fuzzy C-Means Algorithm

for Bias Field Estimation and

Segmentation of MRI Data”, IEEE Trans.

On Medical Imaging, 2002, 21(3):193-

199.

[2] Atam P. Dhawan and Brian

D'Alessandro “Multi- Parameter

Segmentation of Brain Images” of

IEEE(2009)

[3] M.A. Balafar, A. R. Ramli and S.

Mashohor “ Edge-preserving

clusteringalgorithms and their

application for MRI image Segmentation”

proceedings of the multiconference of

engineers and computer scientists Vol I,

IMECS(20103)

[4] J. C. Bezdek, and S. K. Pal, “Fuzzy

Models for Pattern Recognition”, New

York: IEEE Press, 1992.

[5] M.N Bossa and S.Olmos “Multi-object

statistical pose+shape model

segmentation” Zaragoza university,

spain of IEEE(2007)

[6] M.C. Davidson, K. M. Thomas. and B.

J. Casey, “Imaging the developing brain

with fMRI”, Mental Retardation and

developmental disabilities research

reviews, 2003,9 :161-165.

[7] R. C. Gonzalez and R. E. Woods,

Digital Image Processing.

Massachusetts: Addison-Wesley, 1992

[8] Jonathan Bailleul, Su Ruan and Jean-

Mare Constans “Statistical Shape Model-

based Segmentation of brain MRI Images”

on proceedings of the 29th annual

international conference of the IEEE

EMBS Lyon, France IEEE(2007).

[9] Kehong yuan, Lianwen wu chao chen,

qiansheng cheng, shanglian bao, hongjie

“A fuzzy C-means algorithm and its

Application” LM AM, School of

Mathematics Sciences, Peking University,

Beijing 100871, China

[10] Mounir Sayadi, Lotfi Tlig and Farhat

Fnaiech “A New Texture Segmentation

Method Based on the Fuzzy C-Mean

Algorithm and Statistical Features” of

Applied Mathematical Sciences, Vol. 1,

2007, no. 60, 2999 – 3007

[11] Ping Wang HongLei Wang “A

Modified FCM algorithm for MRI brain

image segmentation” International

Seminar on Future BioMedical

Information Engineering of IEEE(2008)

Survey Of Architectures And Mobility Model For Ubiquitous Underwater Acoustic Sensor Networks


SURVEY OF ARCHITECTURES AND MOBILITY MODEL FOR UBIQUITOUS

UNDERWATER ACOUSTIC SENSOR NETWORKS

Shalini.G,

TIFAC-CORE in Pervasive Computing Technologies,

Velammal Engineering College, Anna University.


ABSTRACT

Ubiquitous Underwater Acoustic

Sensor Networks (UU-ASN) targets to

provide a comprehensive study of the

technical issues related to realization of

underwater environments. Technical

issues comprises of fundamental sensor

networking problems such as data

gathering, synchronization, localization,

routing protocols, energy minimization.

In this paper, we have a made a detailed

survey of the architectures and appropriate

mobility models for UU-ASN based on

nodes movement. UU-ASN relies on the

use of simulations to evaluate protocol

performance as real time implementation is

complex. A realistic mobility model that

can capture the physical movement of the

sensor nodes with respect to ocean currents

gives better understanding on the above

problems. We study impact of the model

on the coverage and connectivity of the

network under different scenarios.

Keywords: Underwater acoustic sensor

networks, Architecture, Mobility models,

Deployment, sensing coverage.

1.UNDERWATER NETWORKING

COMPONENTS

Some of the key features needed to

design an efficient UU-ASN are use of

low power underwater sensors,

Optimization of the communication

interfaces according to the medium

characteristics, Optimization of the

network and especially the MAC layer.

The main components that interact in

underwater networks are detailed in the

following:

Underwater Sensors are network

devices in charge of sensing and

communicating oceanographic data of

interest[1].

Unmanned or Autonomous

Underwater Vehicles (UUVs, AUVs)

are mobile nodes equipped that have

more energy than normal underwater

sensor nodes and can move

independently. Once surfaced, these

devices can often communicate

directly to shore via satellites or use

satellite- based services such as GPS;

Underwater Sinks are network

components that relay the data

collected by the sensor nodes from the

sea-bottom to the surface. To

communicate with undersea devices

as well as with surface nodes, the

underwater sinks are equipped with

both a horizontal and a vertical

transceiver

Surface Buoys/Stations are

devices endowed with an acoustic

transceiver designed to handle

multiple communications in parallel

with the deployed under-water

sinks[1][2].

Surface Sinks are further network

components that allow coordinating

different surface stations and thus the

overall underwater network.

Onshore Sinks are additional

network components, placed on the

shore, which can communicate with

the rest of the network via radio or

acoustic links




2. ARCHITECTURE FOR UU-ASN

2.1 Aqua-Net

Aqua-Net follows a layered

structure, which is effective in

accommodating the rapid development of

applications and hardware. Aqua-Net also

has potentials in permitting significant

optimization [7]. It supports cross-layer

design by introducing a translucent

vertical layer that is accessible for all

applications and protocols. Its layered

structure makes easy integration among

implementations of different researchers.

And we define an abstract layer, or

narrow waist, that allow device and

protocol developments to precede a pace

[7]. Aqua-Net is a valuable platform that

will facilitate the process of application

development i.e. it serves as groundwork

for future advances for architectural and

protocol designs.

2.2 Multipath Virtual Sink

Architecture

It aims to achieve robustness and

energy efficiency under harsh underwater

channel conditions. To overcome the long

propagation delay and adverse link

conditions in such environments, we

make use of multipath data delivery.

While conventional multipath routing

tends to lead to contention near the sink,

we avoid this caveat with the virtual sink

design involving a group of spatially

diverse physical sinks. Hence, we are able

to exploit the reliability achieved from

redundancy provided by multipath data

delivery while mitigating the contention

between the nodes.

2.3 Static Architecture

In the stationary UU-ASNs, sensor nodes

are attached to surface buoys or ocean

floor units which have fixed locations or

their movements are negligible. Stationary

UASNs are utilized for monitoring a

certain region, e.g. the harbor entrances[2].

In static architecture the network

topology remains relatively static after

the node deployment. Over a 2D plane

(e.g., the sea-floor), nodes can be

organized according to the same

topologies that we have for terrestrial

networks (e.g., line, tree, grid, clusters);

however, in underwater environments 3D

configurations easily show up, where

moored devices float at different depths.

Figure 1: Static architecture for

stationary Underwater acoustic sensor

network

2.4 Mobile Architecture

According to this architecture, all

nodes in the network can move freely so

that the overall topology is variable over

time. In a UU- ASN with unpropelled

and untethered sensor nodes, the nodes

float freely underwater and drift with the

currents [3]. Devices floating on the sea

surface form the first layer; they are

equipped with wireless transceivers for

data communications and can be

exploited for temporary monitoring

applications [3][4]. Moreover, the surface

layer can communicate with an

underwater layer made of mobile nodes

which can work without cables or remote

control at any desired depth. A mobile

architecture is particularly suitable for

monitoring tasks that entail

reconnaissance missions (especially

when organized in different paths) and/or

tracking of objects (especially those

moving with water currents).



2.5 Hybrid Architecture

Finally, hybrid architecture would

include fixed portions of anchored

devices integrated with mobile nodes as

AUVs[6]. Hybrid architecture has been

employed where a mobile sink node

traverses the network and collects data

from the underwater sensor nodes. A

general three tier architecture leveraging

low cost wireless technology for acoustic

communications between underwater

sensors and standard technologies,

Zigbee and Wireless Fidelity (Wi-Fi), for

water surface communications[9]. Such

architecture is used in undersea

explorations; multimedia distributed

monitoring system, exploiting available

technologies, to evaluate system

performance and to perform complex

tasks such as rapid environmental

assessment or detection and disposal of

undersea mines.

Figure 2: Hybrid architecture for

stationary Underwater acoustic sensor

network

3. MOBILITY MODELS FOR

UU-ASN

When we want to evaluate a

protocol for underwater networks, the

tested solution should be investigated

under accurate models that encompass the

use of realistic mobility patterns. We use

appropriate mobility model to simulate

applications in underwater environments

that require coordination, and therefore

correlation, of the node movements.

Examples :

1. Monitoring a given area or to track a

given object (Pearl / fish monitoring) -

AUVs are required to move in patrols

2. Movement based on a pattern - AUV

be able to move according to precise

patterns as those determined by

communication cables deployed on the

sea-floor or submarine oil-pipes.

The following mobility models

can be used when we need to simulate

an underwater scenario.

3.1 Meandering Current

Mobility with Surface Effect (MCM-

SE) Model

The MCM was first suggested by

physical oceanographers as a simple

model for lagrangian studies of western

boundary currents and it is applied to

underwater sensor networks[5]. The

MCM considers sensors moving by the

effect of meandering sub-surface currents,

jet-like current meandering around

recirculating vortices. The domain model

is representative of a large coastal

environment spanning several kilometers.

In this model the surface mobility with a

stochastic process is superimposed to

the MCM. In this case, deployment of

the network with sensors uniformly

distributed over this large domain would

be unrealistic. Instead, we consider an

initial deployment of nodes in a small

subarea where they are released and

thereafter move according to the mobility

model. This scenario is more realistic

for underwater mobile sensor networks

applications, especially in monitoring the

dynamics of the oceans.



Figure 3: Meandering mobility model

for mobile Underwater acoustic sensor

network

3.2 Random Walk Mobility Model

It is of special interest because

the MN randomly chooses its direction

and speed between pre-defined ranges. In

this model an MN may change direction

after traveling a specified distance or even

a specified time. The Random Walk

model is a memory less mobility process

where the information about the previous

status is not used for the future decision.

That is to say, the current velocity is

independent with its previous velocity

and the future velocity is also

independent with its current velocity.

Therefore, during time interval t,

the node moves with the velocity vector:

(v(t) cosθ(t), v(t)sinθ(t)). This

characteristic may generate unrealistic

movements such as sudden stops and

sharp turns. However, we observe that is

not the case of mobile nodes in many real

life applications. As an example, this

algorithm can easily simulate the

oscillating behavior of moored nodes by

setting either t or d to sufficiently small

values.

Figure 4: Random walk mobility model

for underwater acoustic sensor network

3.3 Random Way-Point Mobility

Model

The Random Waypoint Mobility

Model is the most commonly used

mobility model in the research community

because of its simplicity and wide

availability [10]. In Network Simulator the

implementation of this mobility model is

as follows: at every instant, a node

randomly chooses a destination within the

area A (that can be either 2-

dimensional,e.g.the plane of the sea-

surface, or 3-dimensional,e.g.,the marine

environment from the sea-bottom to the

surface)[10] and moves towards it with a

velocity chosen uniformly and randomly

from pre-defined ranges such as [0,Vmax],

where Vmax is the maximum allowable

velocity for every Mobile Node. The

velocity and direction of a node are

chosen independently of other nodes.

Upon reaching the destination, the node

stops for a duration defined by the

Tpause parameter. After this duration, it

again chooses a random destination and

repeats the whole process again until the

simulation ends.

However this model may create the

clustering of nodes in one part of the

simulation area, also called density

waves. This clustering occurs near the

center of the simulation area and may

reflect on unrealistic simulation.

Figure 4: Random way-point mobility

model for Underwater acoustic sensor

network



3.4 Random Direction

Mobility Model

This model is a further

modification of the Random Walk

Mobility Model, designed to cope with

the so called density wave’s

phenomenon. According to this

algorithm, a node is forced to travel until

the border of the simulation area is

reached; then, it pauses a given amount of

time and, after choosing a new angular

direction, departs again. This model may

be adopted, for instance, to simulate the

monitoring of a given area by means of

randomized paths. Forcing the AUVs to

reach the boundaries of the monitored

area, in fact, guarantees a fair exploration

also of its edges; this is not the case for the

other models presented so far whose

generated traces make the nodes more

likely to be found around the center of the

considered area.

Figure 5: Random direction mobility

model for Underwater acoustic sensor

network

3.5 Probabilistic Random Walk

Mobility Model

This model is based on an

alternative approach to generate

mobility traces which are still

correlated over time. As in the Gauss-

Markov model, the position of a given

object is updated at fixed time

intervals; h e r e , however, we n e e d

to define a probability matrix which

describes the possible transitions to new

positions. The actual shapes of the

mobility traces generated by this method

clearly depend on the definition of the

transition matrix. For underwater

simulations, we can take into

consideration this solution since it can be,

for instance, a handy tool to model the

waving movements typical of objects

floating in the water.

3.6 Trace Based Mobility Model

The TBMM, Trace Based

Mobility Model, captures the history of

the movement patterns of the nodes, and

identifies regularity in these movements.

It is this regularity in movement that is

used to predict the stability of the nodes.

This model as the following assumptions:

o Each node is location aware.

o The network is mapped to a virtual

grid structure. This can be done

based up on the transmission

region and the area network.

A simple algorithm is used to arrive at

the trace representing the regular

movement of the nodes. The information

in the trace consists of both location and

time. The trace collection algorithm is

carried out in each node

3.7 Column Mobility Model

This model allows simulating a

group of mobile nodes moving around an

ideal line that proceeds along some

direction. The idea behind this model is to

mimic soldiers or organized groups of 8

entities marching towards their

destination. The local movement of each

node around the moving line aims to make

the generated traces more realistic by

adding some random displacements. In

underwater scenarios, this model can be

employed to simulate patrols of AUVs

organized for scanning, research or

monitoring purposes.



3.8 Pursue Mobility Model

This model aims to generate

mobility patterns that can be seen as the

result of one or more mobile nodes

pursuing a given target. For each follower,

we compute its updated position as the

vector sum of three terms: 1) the previous

position of the node, 2) the distance

between the target and follower multiplied

by a given acceleration factor, and 3) a

random vector that can be obtained

through one of the entity models above.

The position update steps can be

performed at fixed times or once a given

event occurs (e.g., a sudden movement of

the target). Clearly, in the context of our

interest, this model appears suitable to be

exploited for simulating underwater

tracking applications.

3.9 Reference Point Group Mobility

Model

This model separates the group

movements from those of each individual

node. Group movements are determined by

the path traveled by a “virtual” center.

Whilst nodes in the group update their

reference points according to the virtual

center‟s movements so as to follow it, the

actual position of each node is also

characterized by a further movement that is

chosen independently for each mobile. The

movements of both the virtual center and

the single nodes can be determined via

one of the entity models above. This

model is very general and, depending of its

actual implementation, it can mimic the

behavior of other group mobility models.

Therefore, it is worth to consider also

this model for underwater simulations

since, with slight modifications, it can be

easily adapted to different applications.

3.10 Structured Group Mobility

Model

The main objective of this

model is to refine the previous solution

to generate more realistic traces for

collaborative contexts. In detail, this model

stems from the fact that it is rather difficult

to observe entities moving independently

of each other when they are performing a

collaborative task (e.g., think of a team

of firemen involved in a rescue

mission). Therefore, the Structured Group

Mobility model, differently from the

Reference Point Group Mobility one,

forces nodes in the same group to move

according to precise relationships. In

underwater scenarios, therefore, this model

can be taken into consideration to simulate

patrols of AUVs moving in an actual

coordinated fashion.

3.11 Attraction-based Mobility

Model

This model, as the last two,

separates the movements of the group

(identified now by a leader chosen

among all the nodes composing the group)

from those of the single nodes in the

network. However, in this solution, the

overall group movement is determined by

an “attraction field” existing between the

node leader and every other node. This

model is particularly appealing to

simulate applications that imply a given

hierarchy among nodes. For underwater

scenarios, e.g., we think of a monitoring

application in which patrols of AUVs are

required to converge towards those regions

where one or mode devices notified

something of interest.

4. CONCLUSION

In this paper, we presented an

overview of the state of the art in

underwater acoustic sensor network. We

described the various architectures of

underwater acoustic sensor networks and

the challenges posed by the peculiarities of

the architectures with particular reference

to monitoring applications for the ocean

environment. We discussed characteristics

of various mobility models for the

development of efficient and reliable

underwater acoustic sensor networks. The

ultimate objective of this paper is to

encourage research efforts to lay down

fundamental basis for the development of



effective environment for underwater

communication and networking for

enhanced ocean monitoring and

exploration applications.

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Network Architecture - Design and

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Author Index

A

Arun pandian K S., 39

B

Babu G., 39

G

Geetha C., 22

J

Jagadeesh Kannan R., 22

K

Kanimozhi G., 32

P

Palanikumar K., 7

R

Ramakrishnan M., 22

S

Sastry M R L., 12

Sekar S., 7

Senthilkumar K., 32

Shalini G., 43

Srinivasa Rao K., 12

Subba Rao P., 12

V

Valarmathi T.N., 7

Call for Papers

RSM International Journal of Engineering, Technology & Management

ISSN: 0974-9535

The RSM International Journal on Engineering, Technology & Management is a peer-reviewed,

interdisciplinary international platform for disseminating results of relevant research related to all the disciplines of

engineering, technology & management. The journal aims to cover a wide range of subjects having relevance to the

engineering, technology & management, including but not limited to:

• Automobile Engineering

• Business Management

• Civil Engineering

• Communication Engineering

• Computer Applications

• Computer Science Engineering

• Electrical Engineering

• Electronics Engineering

• Information Technology

• Instrumentation Engineering

• Mechanical Engineering

• Mechatronics Engineering

• Material Science

The journal encourages applied, practical-oriented, problem-solving research having wide relevance. The

Journal seeks contributions in terms of full papers, brief notes, case studies and book reviews for publication in

the journal. Please visit www.rmkec.ac.in for information of the Journal.

Chief Editor:

Principal

R.M.K. Engineering College

RSM Nagar, Kavaraipettai–601 206

Gummidipoondi Taluk, Thiruvallur District

Tamil Nadu, India

Phone: 044-27925338, 339, 102

Fax: 044-27925193

Website: www.rmkec.ac.in

E-mail: [email protected]

Instruction to Author

Authors intending to submit a paper to the journal are available to follow the guidelines.

• Authors are requested to transmit the text and art of the manuscript in electronic form • Each manuscript must also be accompanied by a cover letter, copy right form, and an abstract outlining the

basic findings of the paper and their significance.

• Prior to submitting your paper, please follow the instructions given below.

http://www.rmkec.ac.in/


Types of Contributions

The following types of manuscripts on all topics within the scope of the journal (see separate list) are welcome.

• Full-length papers containing original research work.

• Short Communications giving a complete description of a limited investigation. They should be as completely

documented, both by reference to the literature and by description of the experimental procedures employed, as

a full-length paper. Typically s Short communication will contain no more than four of five figures (graphs or

sets of images) and 2 paper pages.

• Book Reviews by invitation.

• Brief discussion on papers published.

Corresponding Author

Clearly indicate who will handle correspondence at all stages of refereeing and publication, also post

publication. Ensure that telephone and fax numbers (with country and area code) are provided in addition to the

email address and the complete postal address. Full postal addresses must be given for all co-authors.

Length

1. Paper should not exceed 10 pages (including figures, graphs and tables)

2. Review papers may not exceed 15 pages.

Text Area: The following text margins must be used (on size A4 paper; 297X210mm):

Top: 30mm, Bottom: 30mm, Left: 30mm, Right: 20mm

Fonts and line spacing: Use only Times new Roman. Use one-and a half line spacing and justify the text on

both left and right margins. Al body text should be 12 point normal.

Preparation of Manuscripts

1. The language of journal is English. The mode of presentation should be in third person. Poor English can be

reason for rejection of the paper.

2. SI units should be used wherever possible. Other units, if used be given only in parenthesis preceded by SI

units.

3. Mathematical symbols should be types or neatly handwritten, care should be taken to differentiate between

similar characters (e.g. 1 and I), capital and lower case letters and superior and inferior types.

4. Manuscripts should be typed with one and half spacing throughout (including references) on one side of A4

size paper, leaving ample margins; each table should be typed separately. Lengthy mathematical proofs and

extensive test as discouraged.

5. The preferred order of content is:

(a) Title of paper;

(b) Author(s);

(c) Synopsis of not more than 150 words, covering the aim of work, method used, results obtained and

conclusions reached;

(d) Keywords and list of notation, where applicable;

(e) Authors business address as a footnote to the front page;

(f) Body of the paper: Organised into logical sections, with preferably not more than two grades of

subheadings;

(g) Acknowledgement;

(h) References:

References should be listed at the end of the paper and numbered in the order of their appearance in the text.

Authors should ensure that every reference in the text appears in the list of references and vice versa. Numerals

for references should appear in square brackets [ ], and any reference to authors’ names in the text should omit

initials.

A reference to a publication with more than two authors in the text should be to the name the first author et al.,

but in the list of references the names and initials of all authors must be given. In the reference list, periodicals

[1], books [2], and multi-author books [3] should be cited as in the following examples.

1. M.M Benal, I. Finnie, On the size effect in abrasive erosive wear, Mechanical Engg.65(1991)359-373

2. H.K. Shivanand, Engineering Tribology, Oxford University Press, Oxford, 2001, p.468.

3. G.W. Stachowiak, Numerical Characterization of wear particle morphology, in: I.M. Hutchings(Ed.)., New

Directions in Tribology, Mechanical Engineering Publications Ltd., Bury St Edmunds, pp,37–389, 1997.

Tables: These should be numbered consecutively throughout the text and (i) List of captions for the illustrations

which should also be numbered consecutively throughout the text.

Original Material: Submission of an article implies that the work described has not been published previously

(except in the form of an abstract or as part of a published lecture or academic thesis), that it is not under

consideration for publication elsewhere, that its publication is approved by all authors and that, if accepted, it

will not be published elsewhere in the same form, in English or in any other language, without the written

consent of the Publisher.

Illustrations: Original line drawings must neatly be drawn in black Indian ink, on a good quality tracing paper

of A-4 size (210X297). For letters, only mechanical lettering sets (Stencils) should be used. Letterings in the

figure should be large enough such that even the smallest of them would be at least 1.5mm high when the

figures are scanned for printing. Figure captions should be typed out separate list at the end of the manuscript.

Tables: Tables should be numbered consecutively and given suitable caption and each table is laid out with in a

page. No vertical rules should be used. Tables should not duplicate results presented elsewhere in the

manuscript (for example, in graphs). Footnotes to table should be typed below the table and should referred to

by superscript lowercase letters.

Photographs: Photographs should be clear, sharp black and white prints with good contrast in glossy paper.

Again the most suitable size is twice the final size. Cuttings from printed matter of photocopies are unsuitable

for reproduction. Each illustration should be marked with the authors names and the figure number, the top of

each photograph should be indicated. Illustrations will be by authors only if specifically requested for and in the

condition received for the press.

Copyright: Papers are considered for possible publication on the understanding that these have not been

submitted to any other publisher. The copyright of the papers accepted for publication becomes the property of

our journal and reproduction of any part of the paper elsewhere is not allowed without the permission of the

publisher. Contributors are required to sign a declaration to this effect while submitting their papers.

Documents

Journal.2012.pdf - RMK ENGINEERING COLLEGE