Multi-hop Routing SEP (MR-SEP) for clustering in …ijetmas.com/admin/resources/project/paper/f...SEP Protocol. Keywords: Wireless Sensor Networks (WSN), Cluster Head (CH), Multi-hop

International Journal of Engineering Technology, Management and Applied Sciences

www.ijetmas.com August 2014, Volume 2 Issue 3, ISSN 2349-4476

54 HarpreetKaur , Sukhwinder Sharma , Manu Goyal

Multi-hop Routing SEP (MR-SEP) for clustering in wireless sensor

Network

HarpreetKaur Sukhwinder Sharma Manu Goyal

CSE/IT&MCA Deptt. CSE/IT&MCA Deptt. CSE/IT&MCA Deptt.

BBSBEC BBSBEC BBSBEC

Fatehgarh Sahib, India Fatehgarh Sahib, India Fatehgarh Sahib, India

ABSTRACT

Wireless sensors nodes are made up of small electronic devices which are capable of sensing,

computing and transmitting data from harsh physical environments like a surveillance field. These

sensor nodes majorly depend on batteries for energy, which get depleted at a faster rate because of the

computation and communication operations they have to perform. Communication protocols can be

designed to make efficient utilization of energy resources this paper, In order to prolong the lifetime

of Wireless Sensor Network (WSN), the proposed algorithm would be implemented as Multi-hop

Routing with Stable Election Protocol (MR-SEP). MR-SEP partitions the network into different

layers of clusters. Cluster heads in each layer collaborates with the adjacent layers to transmit

sensor’s data to the base station. Ordinary sensor nodes can join cluster heads of their respective

fields as according to distance. The transmission of nodes is controlled by a Base Station (BS) that

selects the upper layers cluster heads to act as super cluster heads for lower layer cluster heads. Thus,

MR-SEP follows multi-hop routing from cluster-heads to a base station to conserve energy, unlike the

SEP Protocol.

Keywords: Wireless Sensor Networks (WSN), Cluster Head (CH), Multi-hop Routing SEP (MR-SEP),

Routing Protocol, Layered Sensor Network, Lifetime, Residual Energy.

I. INTRODUCTION

Wireless Sensor Networks (WSNs) [4] are a special kind of Ad hoc networks that became one of the

most interesting areas for researchers. Routing techniques are the most important issue for networks where

resources are limited [6]. WSNs technology‟s growth in the computation capacity requires these sensor

nodes to be increasingly equipped to handle more complex functions. Each sensor is mostly limited in their

energy level, processing power and sensing ability. Thus, a network of these sensors gives rise to a more

robust, reliable and accurate network. Lots of studies on WSNs have been carried out showing that this

technology is continuously finding new application in various areas [3], like remote and hostile regions as

seen in the military for battle field surveillance, monitoring the enemy territory, detection of attacks and

security etiquette. Other applications of these sensors are in the health sectors where patients can wear small

sensors for physiological data and in deployment in disaster prone areas for environmental monitoring. It is

noted that, to maintain a reliable information delivery, data aggregation and information fusion that is

necessary for efficient and effective communication between these sensor nodes [5]. Only processed and

concise information should be delivered to the sinks to reduce communications energy, prolonging the

effective network life-time with optimal data delivery [7]. An inefficient use of the available energy leads to

poor performance and short life cycle of the network. To this end, energy in these sensors is a scarce

resource and must be managed in an efficient manner.




Hierarchical routing protocols have been proved more energy efficient routing protocols. Several

protocols are designed for homogeneous networks. LEACH [1] is one of the first clustered based routing

protocols for homogeneous network. LEACH assigns same probability for all nodes to become cluster head.

However, LEACH does not perform well in heterogeneous environment. Heterogeneity of nodes with

respect to their energy level has also proved extra lifespan for WSNs. To improve efficiency of WSNs, SEP

[2] was proposed. SEP is a two level heterogeneous protocol. SEP assigns different probability (to become

cluster head) for nodes on the basis of their energy level. However, SEP does not use extra energy of higher

level nodes efficiently. To send messages from nodes to base station we require minimum dissipation of

energy. For such purpose a need of better routing protocol arises which should efficiently utilize energy.

Classical approaches were insufficient to fulfill this demand. We present a novel protocol which is an

extension of the SEP [2], to properly distribute energy and ensure maximum network life time. Our

simulation result shows an improvement in effective network life time and increased robustness of

performance in the presence of energy heterogeneity.

LEACH [1] is a hierarchical clustering algorithm for judicious usage of energy in the network.

LEACH uses randomized rotation of the local cluster head. LEACH performs well in homogeneous

environment. In LEACH every node has same probability to become a cluster head. However, LEACH is

not well suited for heterogeneous environment. SEP is a two level heterogeneous protocol introducing two

types of nodes, normal nodes and advance nodes. Advance nodes have more energy than normal nodes. In

SEP both nodes (normal and advance nodes) have weighted probability to become cluster head. Advance

nodes have more chances to become cluster head than normal nodes. SEP does not guarantee efficient

deployment of nodes. Enhanced Stable Election Protocol (E-SEP) [17] was proposed for three level

hierarchies. E-SEP introduced an intermediate node whose energy lies between normal node and advance

node. Nodes elect themselves as cluster head on the basis of their energy level. The drawback of E-SEP is

same as in SEP. Distributed Energy-Efficient Clustering Protocol (DEEC) [18] shows multilevel

heterogeneity. In DEEC the cluster head formation is based on residual energy of node and average energy

of the network. In DEEC the high energy node has more chance to become cluster head than low energy

node. TEEN [10] is reactive protocol for time critical applications. TEEN was proposed for homogeneous

network. In TEEN the criteria for selection of cluster head is same as in LEACH, TEEN introduces hard and

soft threshold to minimize the number of transmissions thus saving the energy of nodes. In this way the life

span and stability period of the network increases.

In this research, we design a Multi-hop Routing Algorithm with Stable Election Protocol (MR-

SEP).The motivation behind this work is to reduce the energy consumption of sensor nodes by adaptively

increasing the clustering hierarchy. In order to create the equal number of clusters, BS assists in defining the

clustering hierarchy and issuesa TDMA schedule for each layer of cluster heads. Based on this schedule,

each cluster head issues its own TDMA schedule formember nodes. In MR-SEP, cluster heads not only

collect data from their member nodes but also act as relying nodes for cluster heads at lower layers in-order

to route data to the base station. Thus, cluster heads form a tree rooted at the base station,where the

intermediate nodes are only the cluster-heads and leaves are the member nodes. This scheme yields longer

network life time since transmission is based on multi-hop routing from lower-layers towards higher-layers.

Similar, to the SEP protocol, it operates in rounds and a new cluster head is selectedin each round based on

available energy of sensor nodes.The remainder of the paper is organized as follows. Section II presents

related work and motivation for this research is given. Section III elaborates the network and radio model

used for MR-SEP. In Section IV, we provide the details of MR-SEP.




Theoretical performance evaluation of MR-SEP with other stateof the art routing protocols is give in

Section V. Finally, this research is concluded in Section VI.

II. RELATED WORK AND MOTIVATION

Clustering techniques have been employed to deal with energy management in WSNs. Low Energy

Adaptive Clustering Hierarchy (LEACH), a clustering based protocol that utilizes randomized rotation of

local cluster base station (cluster-heads) to evenly distribute the energy load among the sensors in the

network was proposed in Ref. [1]. These sensors organize themselves into clusters using a probabilistic

approach to randomly elect themselves as heads in an epoch. However, LEACH protocol is not

heterogeneity-aware, in the sense that when there is an energy imbalance between these nodes in the

network, the sensors die out faster than they normally should have if they were to maintain their energy

uniformly. In real life situation it is difficult for the sensors to maintain their energy uniformly, thus,

introducing energy imbalances. LEACH assumes that the energy usage of each node with respect to the

overall energy of the system or network is homogeneous. Conventional protocols such as Minimum

Transmission Energy (MTE) and Direct Transmission (DT) [3] do not also assure a balanced and uniformly

use of the sensor‟s respective energies as the network evolves.

Stable Election Protocol (SEP), was proposed in [2], a heterogeneous aware protocol, based on

weighted election probabilities of each node to become cluster head according to their respective energy.

This approach ensures that the cluster head election is randomly selected and distributed based on the

fraction of energy of each node assuring a uniform use of the nodes energy. In the SEP, two types of nodes

(two tier in-clustering) and two level hierarchies were considered.Another emerging approach for routing in

WSN is multi-hop routing with unequal clustering. In this approach variable number of intermediate nodes

will forward data to the base station,depending on the location of the sensed data. This approach has

following shortcomings.

1. Since, there are unequal clusters inside the same network hence; scheduling becomes a difficult task. In

some cases we may need to use Carrier Sense Multiple Access(CSMA), which is rather expensive compared

with TDMAschedule.

2. Decision of joining upper level cluster head lies with the lower level cluster head this can result in hot

spots.

In this research, our main aim is to develop a multi-hop routing algorithm for WSN with equal clustering to

achieve the following objectives.

1. Reduce the average distance of each cluster head from it supper level cluster head so that in reaching the

base station, the energy consumption is distributed among different cluster heads that will eventually result

in longer network lifetime.

2. Selection of cluster heads at second and above level will be made by the base station thus; computational

cost at sensor nodes will be reduced.

3. Equal number of clustering level will be used, this will enable us to use global TDM schedule hence;

problem associated with multi-hop routing with unequal clustering will be alleviated.

TERMINOLOGIES USED

Some basic terminologies we used in the paper are:




• Stability Period: Time interval from the start of the network to the death of the first sensor node.

• Instability Period: Time interval from the death of the first node to the death of the last sensor node.

• Throughput: The total rate of data sent over the network, the rate of data sent from cluster heads to base

station as well as the rate of data sent from the nodes to base station.

• Network Lifetime: Time interval from the start of the network to the death of the last alive node.

• Epoch: Number of rounds after which a node becomes eligible for cluster head.

• Data Aggregation: Data collected in sensors are derived from common phenomena so nodes in a close area

usually share similar information. A way to reduce energy consumption is data aggregation. Aggregation

consists of suppressing redundancy in different data messages. When the suppression is achieved by some

signal processing techniques, this operation is called data fusion.

3. PROPOSED MR-SEP

In this section we present our proposed protocol. Our protocol is extension of SEP. It follows hybrid

approach i.e. direct transmission and transmission via cluster head. Further we discuss in detail the

functioning of our protocol.

3.1 Network Model

In this research, we assume that set of sensor nodes are randomly deployed in the square field to

continuously monitor the phenomenon under inspection. We assume that sensor network possess following

properties.

1. Once deployed all sensor nodes and BS are stationary.

2. Base Station can be placed anywhere inside the sensing field or away from it.

3. Nodes use power control to tune the amount of send power according to the transmission distance.

Fig. 1 Network Phase




3.2Radio Model

Our radio model is similar to the one presented in [5]. Discussion of radio model is essential because

assumptions about the radio characteristics including energy dissipation in transmit and receive mode will

have an impact on the performance of a particular routing protocol. We further assume that path loss

exponential is d2 power loss in free space provided; transmitter and receivers are within certain threshold

distance d0 otherwise it is d4. If a node wants to transmit „k‟ bits of data over a distance „d‟ then following

equation will give us transmission energy requirements.

𝐸Tₓ 𝑘,𝑑 = 𝑘.𝐸𝑒𝑙𝑒𝑐 + 𝑘. 𝜀𝑓𝑠 .𝑑2 𝑖𝑓 𝑑 < 𝑑0

𝑘.𝐸𝑒𝑙𝑒𝑐 + 𝑘. 𝜀𝑎𝑚𝑝 .𝑑4 𝑖𝑓 𝑑 ≥ 𝑑0

(1)

𝐸Rₓ 𝑘 = 𝑘.𝐸𝑒𝑙𝑒𝑐

(2)

In above equation 𝐸𝑒𝑙𝑒𝑐 is the per bit energy dissipations for transmission.We also use the free-space and

two-ray models according to the distance between the transmitter and receiver.

d0is a threshold transmission distance and d0= 𝜀𝑓𝑠

𝜀𝑎𝑚𝑝 . If d0<d , the free-space model will be employed;

otherwise, the two-ray model will be employed. 𝜀𝑓𝑠and𝜀𝑎𝑚𝑝 are the amplifier parameters of transmission

corresponding to the free-space and the two-ray models respectively.

Fig 2. Radio Model

3.3 No. Of Optimal Cluster-heads

In hierarchical routing protocols, the number of cluster-headsis a key factor that affects performance

of routingprotocols. If the number of cluster-heads is less, each cluster-headneed to cover larger region that

will lead to some clustermembers are far from their cluster-heads and consume muchmore energy. As the

communication between cluster-heads andthe base station needs much more energy than common nodes,the

excessive number of cluster-heads will increase the energyconsumption of the whole network and shorten

the networklifetime. Therefore, it is necessary to select optimal cluster-headnumber to make the energy

consumption minimum.

Assume that there are N nodes distributed uniformly in an 2×R×Rregion. If there are k clusters, there are on

averageN / k nodes per cluster (one cluster-head and (N / k) −1regular nodes). Each cluster-head dissipates

energy receivingsignals from the nodes, aggregating the signals, andtransmitting the aggregate signal to the

BS. Since the BS is farfrom the nodes, presumably the energy dissipation follows thetwo-ray model.

Therefore, the energy dissipated in the cluster-headduring a single frame ECHis:




𝐸𝐶𝐻 = 𝑙 ∗𝑁

𝑘∗ 𝐸𝑒𝑙𝑒𝑐 + 𝐸𝐷𝐴 + 𝑙 ∗ 𝜀𝑎𝑚𝑝 ∗ 𝑑𝑡𝑜𝐵𝑆

4

(3)

wherelis the number of bits in each data message, dtoBSis the distance from the cluster-head to the BS, EDAis

theenergy consumption of one byte in data aggregation.

Each regular node only needs to transmit its data to thecluster-head once during a frame. Presumably the

distance tothe cluster-head is small, so the energy dissipation follows thefree-space model. Thus, the energy

used in each noncluster-head node is:

𝐸𝑛−𝐶𝐻 = 𝑙 ∗ 𝐸𝑒𝑙𝑒𝑐 + 𝑙 ∗ 𝜀𝑓𝑠 ∗ 𝑑𝑡𝑜𝐶𝐻2

(4)

WheredtoCHis the distance from the node to the clusterhead.

Hypothesize the probability density of all the nodes in thearea is ρ(x, y), and cluster-heads are in the center

of thecluster, The expected squared distance from the nodes to thecluster-head can be:

𝐸 𝑑𝑡𝑜𝐶𝐻2 = 𝑥2 + 𝑦2 𝜌 𝑥,𝑦 𝑑𝑥𝑑𝑦

(5)

𝐸 𝑑𝑡𝑜𝐶𝐻2 = 𝑟2 𝜌(𝑟,𝜃)𝑟𝑑𝑟𝑑𝜃

(6)

Assume this area is a circle with radius R = M / 𝜋𝑘,and ρ (r,θ ) is constant for r and θ , If the density of

nodes is uniform throughout the cluster area, then ρ = k / M2 and: (6) simplifies to:

𝐸 𝑑𝑡𝑜𝐶𝐻2 =

𝑀2

2𝜋𝑘

(7)

The energy dissipated in a cluster during the frame is:

𝐸𝑐𝑙𝑢𝑠𝑡𝑒𝑟 = 𝐸𝐶𝐻 + (𝑁

𝑘− 1)𝐸𝑛−𝐶𝐻 ≈ 𝐸𝐶𝐻 +

𝑁

𝑘𝐸𝑛−𝐶𝐻

(8)

and the total energy for the frame is ET= kEcluster, We canfind the optimum number of clusters by setting the

derivativeof ETwith respect to k to zero.

Thus the optimal ratio of cluster-heads is:

𝑃𝑜𝑝𝑡 =𝑘𝑜𝑝𝑡

𝑁

(9)

𝑃𝑜𝑝𝑡 = 𝜀𝑓𝑠

2𝜋𝑁𝜀𝑎𝑚𝑝

𝑀

𝑑𝑡𝑜𝐵𝑆2

(10)




This Poptwill be used in the thresholdTR(n)to decidewhich node is eligible to be a cluster-head.

4. MR-SEP ALGORITHM

The operations that are carried out in the SEP-MR protocol are divided into three stages, which are given

below:

• Cluster Formation at lowest level.

• Cluster Discovery at different levels by Base Station.

• Transmission of aggregated data by cluster heads to Base Station through Multi-hop routing.

4.1 Cluster Formation at lowest level

In the cluster formation phase, all the sensors within a network group themselves into some cluster

regions by communicating with each other through short messages as same of SEP [1]. At a point of time

one sensor in the network acts as a cluster head and sends short messages within the network to all the other

remaining sensors. The sensors choose to join those groups or regions that are formed by the cluster heads,

depending upon the signal strength of the messages sent by the cluster heads. Sensors interested in joining a

particular cluster head or region respond back to the cluster heads by sending a response signal indicating

their acceptance to join.The cluster head can decide the optimal number of cluster members it can handle or

requires. Figure 2 below shows two phases of a sensor in a SEP-MR protocol: all the sensors form as cluster

members to the cluster heads and in the second phase cluster heads perform the transmission of data to the

sink in a multi-hop structure.

Fig. 3 Selection of Cluster-heads

4.2 Cluster Discovery at different levels by Base Station

In this phase, the cluster heads will be divided into the different layers with the help of base station.

Using its broadcast capability base station will discover clusterheads at different levels. We assume that the

BS can reach all nodes in one hop over a common control channel. The BS will broadcast its Identifier (ID)

over the common control channel. All cluster-heads which hear this broadcast will record the BS ID. Cluster

heads which are near to the BS form layer one since they are at single hop distance from the BS i.e. layer

one. Now, BS will broadcast a control packet with all layer one cluster heads ID‟s in it. All cluster heads in




the network will reply to this message at default low power level with their own ID‟s aswell as ID‟s of layer

one cluster heads (Layer one cluster heads will not respond to this message, since their ID‟s are present in

the control packet). Since, nodes will broadcast at lower power level therefore; this reply will not get to the

BS directly. Layer one cluster heads are one hop away from layer two cluster heads therefore; this reply will

get to layer one cluster heads. Layer one cluster heads whose ID‟s are present in the reply message will relay

this message to the BS.

BS will record the ID‟s of cluster heads, level of the cluster head and ID of the forwarding cluster head (at

immediate upper level, of the node) in its internal data structure.Similarly, BS will again broadcast control

message with ID‟s of all cluster heads it has discovered. All undiscovered cluster heads will reply to this

message and the processing will be done as described above. This process continues till no new cluster head

is discovered.

Following figure depicts the whole process:

Fig. 4 Cluster Discovery at different levels

Once the cluster heads at different levels have been discovered, the BS will use the information, i.e., cluster

head ID, Cluster Head Level and immediate Cluster Head ID to form cluster of cluster-heads.

4.3 Transmission of aggregated data by cluster heads to Base Station through Multi-hop routing.

After forming cluster heads at different levels, member nodes scheduling needs to be done. Time

Division Multiple Access (TDMA) is the preferred scheduling scheme in sensor networks because it saves

lot of energy compared to contemporary medium access techniquesfor wireless networks. One thing must be

notice that whenever a cluster head needs to communicate with its upper cluster heads in the cluster

hierarchy it must use higher powerin-order to guarantee data delivery.

Upper level cluster heads will allocate longer time slots to their member low level cluster heads

because they have more data to send compared to simple members. Hence the communication between the

inter cluster-heads takes place through the multipath routing before the data directly sent to the base station.

First of all communication will take place between the upper level cluster head and lower level cluster head

on the basis of the distance which is clearly illustrated by the fig. 4. According to multipath routing, the

upper level cluster heads will look for the nearest lower level cluster head to conserve energy. Then after

inter cluster-heads communication lower level cluster-head would send the data directly to the base station.




Fig. 5- Illustration of Multi-hop Routing

5. SIMULATION RESULTS

We simulate proposed algorithm and Stable Election Protocol (SEP) clustering algorithm for WSN. Results

from many runs of each algorithm are recorded for random distribution of nodes. The basic parameters used

are listed in Table I

Table 1: Parameter for the MR-SEP algorithm

Parameter Value

Number of Nodes 100

Network Field 200*200

Base Station Position (100,100)

Size of data packet 4000 bits

Initial energy of normal

node

0.5 J

Initial energy of

advanced node

2 J

𝜀𝑓𝑠 10pJ/bit/m2

𝜀𝑎𝑚𝑝 0.0013pJ/bit/m4

Eelec 50nJ/bit

EDA 5nJ/bit/signal

d0 87m




We use following two metrics to analyze and compare the performance of the algorithm MR-SEP and SEP

The stability of networks [9], namely the first node dead round

The networks life time, namely the total energy dissipation and survival round, is the key metric of

evaluation.

B. Stability Period& Network Lifetime

We have calculated the stability period and Network Lifetime for proposed algorithm and SEP algorithm

over the 100 simulation. The table 2 shows the results of Stability period and Table. 3 shows the result of

Network Lifetime for both algorithm

Table 2: Comparison of stability period for SEP and MR-SEP

Stability Period for SEP 882

Stability Period for MR-SEP 1012

Table 3: Comparison of Network Lifetime for SEP and MR-SEP

Network lifetime for SEP 5547

Network lifetime for MR-SEP 5894

Fig. 6. Stability Period & Network Lifetime Result

6. CONCLUSION

In this paper, a multi-hop routing with Stable Election Protocol is proposed to minimize the energy

consumption of sensor nodes. MR-SEP introduces the concept of multi-hop routing in SEP algorithm i.e.,

data from any node that becomes cluster-head irrespective of energy in the top layer will reach the BS with

the help of intermediate cluster-head in the lower layer. Hence multipath model of radio which leads to

major power dissipation in nodes in SEP protocol is not used in this algorithm. Hence with the multi-hop




between the intermediate cluster-heads leads MR-SEP algorithm to better stability period and network

lifetime than original SEP. Performance evaluation section has shown that MR-SEP performs well compared

to similar approaches given that network is divided into optimal number of layers,

REFERENCES

[1] W. R. Heinzelman, A. Chandrakasan, and H. Balakrishnan. "Energy-efficient

communication protocol for wireless microsensor networks", Proceedings of the 33rd

Hawaii International Conference on System Sciences (HICSS-33), (2000)

[2] G. Smaragdakis, I. Matta, A. Bestavros, "SEP: A Stable Election Protocol for clustered

heterogeneous wireless sensor networks", Second International Workshop on Sensor and

Actor Network Protocols and Applications (SANPA 2004), (2004).

[3] W.R. Heinzelman, A.P. Chandrakasan, H. Balakrishnan, "An application- specific protocol

architecture for wireless microsensor networks", IEEE Transactions on Wireless

Communications vol 1, no 4, (2002), pp 660-670.

[4]+ I. Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirci. A survey on sensor networks.

IEEE Communications Magazine, 40(8):102–114, August 2002.

[5] S. Bandyopadhyay and E. J. Coyle. An energy efficient hierarchical clustering algorithm

for wireless sensor networks. In Proceedings ofthe 22nd Annual Joint Conference of the

IEEE Computer and Communications Societies (Infocom 2003), April 2003.

[6]

S. Bandyopadhyay and E. J. Coyle. Minimizing communication costs in hierarchically-

clustered networks of wireless sensors. Computer .Networks, 44(1):1–16, January 2004.

[7] E. J. Duarte-Melo and M. Liu. Analysis of energy consumption and lifetime of

heterogeneous wireless sensor networks. In Proceedings of Global Telecommunications

Conference (GLOBECOM 2002),pp 21–25. IEEE, November 2002.

[8] V. Mhatre and C. Rosenberg. Homogeneous vs. heterogeneous clustered sensor networks:

A comparative study. In Proceedings of2004 IEEE International Conference on

Communications (ICC2004), June 2004.

[9] A. R. Masoum, A. H. Jahangir, Z. Taghikhani, and R. Azarderakhsh, “A new multi level

clustering model to increase lifetime in wireless sensor network”. Second International

Conference on Sensor Technologies and Applications, SENSORCOMM, IEEE Computer

Society, pp. 185-190, August 25 - 31, 2008.

[10] A. Manjeshwar and D. P. Agrawal, “TEEN: A Routing Protocol for Enhanced Efficiency

in Wireless Sensor Networks”. Proc. of 15th International Symposium on Parallel and

Distributed Processing (IPDPS), pp. 2009-2015, April 2001.

[11] D. J. Dechene, A. E. Jardali, M. Luccini, and A. Sauer, “A Survey of Clustering

Algorithms for Wireless Sensor Networks”, The University of Western Ontario,London,




Ontario, Canada.

[12] V. Loscri, G. Morabito, and S. Marano, “A Two Level Hierarchy for Low Energy

Adaptive Clustering Hierarchy (TL_LEACH)” 62nd IEEE Vehicular Technology

Conference (VTC-Fall), pp. 1809 – 1813, 25-28 September, 2008,Dallas.

[13] Gong, B., Li, L., Wang, S., and Zhou, X. “Multihop Routing Protocol withUnequal

Clustering for Wireless Sensor Networks”. Proc. of IEEE CCCM. pp. 552-556, 2008.

[14] Imran, Muhammad, AbasMd Said, and HalabiHasbullah. "A survey of simulators,

emulators and test beds for wireless sensor networks." Information Technology (ITSim),

2010 International Symposium in. Vol. 2. IEEE, 2010 pp. 897 – 902

[15]

[16]

Ali, Q., Abdulmaojod, A., Ahmed, H.," Simulation & Performance Study of Wireless

Sensor Network (WSN) Using MATLAB, IJEEE Journal, 2010.pp.307-314

Jamal N. A1-Karaki Ahmed E. Kamal “Routing techniques in wireless Sensor :A Survey

,wireless communication ,IEEE 2004.

[17] Aderohunmu, Femi A., and Jeremiah D. Deng. "An Enhanced Stable Election Protocol

(SEP) for Clustered Heterogeneous WSN." XH Wu, S. Wang,” Performance comparison

of LEACH and LEACH-C protocols by NS2,” Proceedings of 9th International

Symposium on Distributed Computing and Applications to Business, Engineering and

Science. Hong Kong, China. 2010.

[18] Chamam, Ali, and Samuel Pierre. "A distributed energy-efficient clustering protocol for

wireless sensor networks." Computers & electrical engineering 36.2 (2010): 303-312.

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Multi-hop Routing SEP (MR-SEP) for clustering in …ijetmas.com/admin/resources/project/paper/f...SEP Protocol. Keywords: Wireless Sensor Networks (WSN), Cluster Head (CH), Multi-hop