[IEEE Sixth International Conference on Networking (ICN'07) - Sainte-Luce, Martinique, France (2007.04.22-2007.04.28)] Sixth International Conference on Networking (ICN'07) - A-sLEACH:

A-sLEACH : An Advanced Solar Aware Leach Protocol for Energy Efficient Routing in Wireless Sensor Networks

Md. Junayed Islam, Md. Muhidul Islam, Md. Nazrul Islam Department of Computer Science &Engineering Khulna University of Engineering & Technology

Khulna-920300, Bangladesh Email: [email protected], [email protected], [email protected]

Abstract

Energy consumption plays a crucial role in Wireless Sensor Networks as these networks are designed to be placed in hostile and non-accessible areas. While battery-driven sensors will run out of battery sooner or later, the use of renewable energy sources such as solar power extends the lifetime of a sensor network. We propose a solar-aware, scheduled clustered routing protocol A-sLEACH which is an extension to sLEACH for routing and MTE for radio model. Simulation results of applying such scheme shows better performance compared to MTE and sLEACH. Keywords: sLEACH, Cluster Head, CSMA/CA, Wireless Sensor Networks. 1. Introduction

Routing in Wireless Sensor Network is a topic that arises in any network as soon as it is large enough to require multiple hops. Energy efficiency in routing has utmost importance; while many researchers assumed that sensor networks are mostly battery driven. But it is much more attractive to let nodes driven by other energy sources, such as gravitation or solar power. We proposed a new solar-aware scheduled MAC protocol named A-sLEACH (Advanced Solar-aware Low Energy Adaptive Clustering Hierarchy), a clustering based protocol which introduces an improved idea of sensor radio model, a new approach for randomization of local cluster base-stations (cluster-heads), enhanced data aggregation by FIFO priority scheme and collision minimized non-persistant Carrier Sense Multiple Access (CSMA). A-sLEACH provides significant benefits in scenarios mentioned above. The paper outlined is as follows. Section 2 mentions some related works. In section 3 we have explained our proposed scheme/protocol in details. Section 4 shows the simulation results compared to sLEACH [1]. Section 5 specifies the evaluation of proposed protocol.

Finally, conclusion and outline of future works are explained in section 6. 2. Related Works Several works and studies had been performed regarding energy-efficient routing in wireless sensor networks. Among them the most well known protocol-LEACH (Low Energy Adaptive Clustering Hierarchy) [2], proposed by Heinzelman et al. is an example of utilizing TDMA in wireless sensor networks. To extend the life-time of sensor networks another cluster based protocol had been introduced by Theimo Voigt et. al. whose name is sLEACH (Solar-aware Low Energy Adaptive Clustering Hierarchy)[1] protocol. In sLEACH all nodes are considered as solar powered having battery power as backup, where cluster-heads initially selected by base station, chooses the next cluster-heads after a certain time called round. For radio model, a minimum-energy routing protocol named MTE (Minimum Transmission Energy) is considered [2]. In this protocol, nodes route data destined ultimately for the base station through intermediate nodes. Thus nodes act as routers for other nodes data in addition to sensing the environment. 3. Proposed A- sLEACH : Our power consumption reduced scheduled routing scheme includes the following features: The base station is fixed and located far from the solar aware sensor nodes. The cluster head will be chosen by the base station using a proposed scanning technique, considering the cluster nodes as the points of a convex hull. In the next stage, a cluster head will choose a solar-powered node using the previous strategy after current round (the time a node remains the cluster head) and declare it as the cluster head.

Proceedings of the Sixth International Conference on Networking (ICN'07)0-7695-2805-8/07 $20.00 2007

The Base Station (BS) broadcasts a message containing the cluster head ID for each node; known as Advertisement Message. The cluster head will send the aggregated data to the BS using a non-persistent CSMA protocol where to avoid collision or minimizing the waiting state, a contention slot will be chosen randomly. Scheduling of nodes will be performed using the TDMA scheme by the cluster head and data aggregation will be performed by the enhanced FIFO priority technique. 3.1 Radio Model For A-sLEACH We assume a simple model where the radio dissipates transmitter or receiver electronics E elec = 50 nJ/bit to run the transmitter or receiver circuitry and transmit amplifier amp = 100 pJ/bit/m2 for the transmit amplifier to achieve an acceptable signal to noise ratio E b /N b (Figure-1) . We also assume an r

2 energy loss due to channel transmission. Thus, to transmit a k-bit message a distance d using our radio model, The radio expends, E Tx (k,d) =E elecTx (k)+ E ampTx (k,d)

E Tx (k,d) = E elec *k+ amp *k*d2

and to receive this message, the radio expends: E Rx (k)= E elecRx (k)

E Rx (k)= E elec *k For these parameter values, receiving a message is not a low cost operation; the protocols should thus try to minimize not only the transmission distances but also the number of transmit and receive operations for each message.It was assumed that the radio channel is symmetric such that the energy required to transmit a message from node A to node B is the same as the energy required to transmit a message from node B to node A for a given SNR. For our experiments, we also assume that all sensors are sensing the environment at a fixed rate and thus always have data to be sent to the end-user. 3.1.1 Energy Analysis Using Radio Model We examine a protocol namely minimum-energy multi-hop routing against our proposed routing protocol using radio model. The conventional approach we consider is a minimum-energy routing protocol. Here nodes act as routers for other nodes data in addition to sensing the environment. In this case, the intermediate nodes are chosen such that the transmit

Figure 1. Proposed Radio Model amplifier energy (e.g. E Tx (k,d) = amp *k*d

2 , is minimized; thus node A would transmit to node C through node B if and only if:

E ampTx (k,d=d AB )+E ampTx (k,d=d BC )<

E ampTx (k,d=d AC ) However, for this minimum-transmission-energy (MTE) [2] routing protocol, rather than just one (high-energy) transmit of the data, each data message must go through n (low- energy) transmits and n receives. Depending on the relative costs of the transmit amplifier and the radio electronics, the total energy expended in the system is very high in MTE routing .In MTE routing, each node sends a message to the closest node on the way to the base station. Thus the node located distance nr from the base station would require n transmits a distance r and ( n -1) receives- E MTE = n * E Tx (k,d = r) + ( n -1) * E Rx (k) = n (E elec *k+ amp * k * r

2 )+( n -1)*E elec *k(1) And in our proposed clustering based protocol A-sLEACH, which introduces a FIFO prority scheme (which is described later) in which ties are broken arbitrarily needs, E FIFO = ( n -1)* E Tx (k,d = r) + n * E Rx (k) =( n -)*(E elec *k+ amp *k*r

2 )+ n *E elec *k(2) We simulated transmission of data from every node to base station (located 100 m from the closest sensor node) and considering each node has a 2000 bits data packet to send to the base station. Using equation (1) & (2), figure 2 shows the simulation. It is clear that in MTE routing, the nodes closest to the base station will be used to route a large number of data messages to the base station. Thus a cascading effect occurs that will shorten system lifetime. Where using FIFO priority scheme gives a energy efficient way and increases system lifetime. Considering a linear network, needs


( n -1) transmits a distance r and n receives, in figure 3, shows our simulation .

0

50

100

150

200

250

1 2 3 4 5 6 7 8 9 10

No of Nodes

Ener

gy (m

j)

MTEA-sLEACH

Figure 3: FIFO Based Data Gathering. 3.2 Proposed Technique for Cluster-Setup and Cluster -Head Selection Every cluster having a set of nodes forms a convex hull (Figure 4) containing the maximum number of nodes. Two variants are there of the convex hull like cluster forming: It is desired to check whether a node lies in the

interior of a cluster like convex polygon having n ..........21 nodes. The node may be in the

cluster if a straight line A intersects with some of the nodes of , then it lies in the cluster.

A node identity matrix which is denoted by ij , can be presented as follows.

det(A)=

( )

+

+

)det(1.................

............... ) det( - ) det(

1n1

12121111

11

n

By evaluating, if this determinant is found positive then any node is of the left of directed nodes

n ..........21 .Then it is said that

n ..........21 is a left turn. Otherwise it is a right turn. If the determinant is zero then all selected neighboring nodes are collinear.

PROPOSED ALGORITHM( ): 1. Let po be the point in given set with

the minimum y-coordinate or leftmost point.

2. Let be the remaining points in , sorted by polar angle in counterclockwise order with respect to po.

3. TOP [S] = 0 4. PUSH (po, S) 5. PUSH (p1, S) 6. PUSH (p2, S) 7. for i = 3 to m do

a. while {angle between NEXT_TO_TOP[S], TOP[S], and pi makes a nonleft turn} do

b. PUSH (S, pi) 8. return S .

Now for most dense case of cluster construction (Figure 4) deciding whether a node for each round will be the cluster-head or not; Firstly we consider in our proposed protocol A-sLEACH, the lowest y-coordinate valued node miny with the best conserved energy bsw . Such selection proves that the solar-aware nodes are best computed with a greater probability for being the cluster-head of the next round. In Figure 4 view of our implementation is shown implicitly. Now rest of the 1 nodes are being sorted

with their total energy values, y-coordinate values

Base Station

0

0.5

1

1.5

2

2.5

3

0 50 100 150

Time (seconds)

No.

Of W

aitin

g M

essa

ges

Fifo Scheme

Figure 4: Most dense case of cluster construction.

Figure 2. Energy Vs Number of Nodes Curve of MTE routing and our proposed routing.


having the positive x-axis and starts our scan from node

miny considering successive three points. If this scan forms a right turn then the middle 1+n node gets deleted from the current selection array, as it cannot lie on the hull. Otherwise, move to the next node setting the

n equal to its predecessor. According to this strategy in Figure 4. node No: 3 gets deleted which starts from nodes miny ,1 and 2. This process of scanning ends when we get K+3 nodes with the highest remaining energy. We have a Scan Based algorithm mentioned above whose time complexity for choosing cluster-heads is ( )nn log which gives better results than any other scheduled routing protocols. A-sLEACH is also designed for the most dense case of cluster construction (Figure-4) with the assumption that there are a large number of sensor nodes placed randomly, and the network size is -

where is the

horizontal size and

is the vertical size of the sensor network area. 3.3 Data Gathering Technique Consider the packets a,b,c, and d in figure 4. their final destinations are shown in figure 5(g). Let us assume the FIFO priority scheme in which ties are broken arbitrarily. Also let each packet take the shortest path from its origin to its destination. At time step t=1, every packet moves one edge closer to its destination. As a result, packets a and b reach the same node. So, at t=2, one of a and b has to be queued. Since both a and b have reached this node at the same time, there is a tie. This can be broken arbitrarily. Assume that a has won. Also at t=2, the packets c and d move one step closer to their final destinations and hence join b (see figure 5(c)). At t=3, packet b moves out since it has higher priority than c and d. At t=4, packets c and d contend for the same edge. Since both of these have the same priority, the winner is chosen arbitrarily. Let d be the winner. It takes two more steps for c to reach its destination. By then every packet is at its destination. 3.4 Collision Minimized CSMA in A-sLEACH The aggregated data in cluster-head and each nodes information of position, energy status are sent to the base station using a fixed spreading code with CSMA. If sensor nodes simultaneously and independently pick one of l slots at some point in time, then nodes use to randomly choose one of contention slots.

Definition 1: We say slot l is silent if no sensor node

Figure 5. Data Gathering Technique chooses that slot. Due to a collision, a contender wins in slot l if and only if It is the only one to choose slot . Definition 2: Let s be a slot number and for contenders; 2. If S ( ) is a recursive function

which is related to the probability of success, when contenders compete . Then for s 2,

S ( ) = 1

1 )(1

s

where, S

lim S ( ) = 1 Suppose there are l slots and each contender independently picks a slot l with probability lp ; we refer to the distribution

lppp ....,.........21, as p .

Definition 3: Let p ( ) be the probability of success when nodes select a contention slot using probability distribution p. Then the probability of

0

0.2

0.4

0.6

0.8

1

1.2

0 100 200 300 400 500 600

Number Of Contenders (N)

Pro

babi

lity

Of S

ucce

ss =1024

=64

=16

l

l

l

Figure 6: The maximum probability of success

p ( ) becomes flat as increases.


success is the sum of the probabilities of success in each slot before slot l .

p ( ) = p 1 (1- p 1 )1 + p 2 (1-p 1 -p 2 )

1 +

..+ p 1 l (1-p1 -.. - p 1 l )1

= =

1

1

l

SSp

1

1

1

=

Sl

lp .

Theorem 1: Suppose 2 . Over all possible distribution p is the distribution that maximizes

p ( ). Proof: If 1=Sp for any s , then all ( 2 ) contenders collide on slot s , so the distribution cannot be optimal. If 0=Sp for some s , then the success probability can be increased by half of Sp from a

neighboring slot s . Figure 6 shows that as increases, p ( ) may drop initially and then becomes almost constant. We see that, for any fixed l , it is possible to maintain the probability of success as number of sensor nodes increases by suitably adjusting the distribution. 3.5 Heuristic Approach for Cluster head selection Let n denotes that the node is a cluster head at time n, then the process { n , n=0,1,2,.} with transitions probabilities

1,........,2,1,1

1

1,1,

00

===

==

+ rrrchrr

NN

Nrprr

This has three classes, namely {0},{1,2,,N r -1}, and

{N r }; the first and third class being recurrent and the second transient state is visited only finitely often, it follows that, after some finite amount of time, the node will either a cluster head or not. Let r , r = 0,1,,N r , denote the probability that, starting with r, the chance of being a cluster head will eventually reach N r . Here r = 0,1.,N r denotes each round .By conditioning on the outcome of the initial of the phase we obtain r = p ch P 1+r +q ch P 1r , r =1,2,.,N r -1 or equivalently, since p ch +q ch =1,

p ch r +q ch r =p ch P 1+r +q ch P 1r

or P 1+r - r = q ch / p ch ( r - 1r ), r=1,2,.,N r -1 Hence, since P 0 = 0, we obtain from the preceding line

11

211

)/(

)(/

=

=

r

rrrr

Nchch

NNchchNN

pq

pq

So, the first r-1 of these equations yields

( ) ( ) ( )[ ]1211 /...// ++= rchchchchchchr pqpqpqor

=

=1/....,.........

1/...))/(1/)/(1( 1

chchr

chchchchr

chch

r

pqrP

pqPpqpq

Now, using the fact that ,1=rN we obtain that

=

=2/1............/1

2/1)....)/(1/)/(1(

1

chr

Nchch

rchch

pN

ppqpq r

and hence

=

2/1............/

2/1)....)/(1/)/(1(

chr

Nchch

rchch

r

pNr

ppqpq r

Note that, as N r

>

2/1............0

2/1....)/(1

ch

chr

chch

r

p

ppq

Thus, if 2/1>chp there is a positive probability that the node will become cluster head increase indefinitely and 0 otherwise. 4. Simulation Results

We have implemented our proposed protocol algorithm A-sLEACH in OMNET++ and MATLAB. Simulation shows that proposed radio model (fig-1) is much more energy efficient than MTE [2]. We have used the same parameter settings as in sLEACH [1] (sunDuration-200 and frames/round- 10).Using our proposed cluster forming scheme and selection of solar-powered nodes as cluster-head saves energy about 57.78% per node. Number of sunNodes over time in our simulation is higher which keeps the total remaining


energy comparatively more about 14.31%. For example, with 25 sunNodes, 96.56% of all cluster-heads are solar-powered where with 15 sunNodes only 85% of the cluster-heads are solar-powered. 4. Evaluation As the cluster-heads perform the most energy intensive task, we expect that solar-awareness with our proposed advanced routing scheme will increase the lifetime of sensor network compared to the conventional one. We have calculated that our proposed scheme has 19.58% more lifetime than sLEACH [1], which is shown in figure 7,8,9. We measured the improvement of the number of rounds until the first and last nodes have run out of battery compared to MTE and sLEACH. The Table1 shows the evaluation.

6.Conclusion and Future Works In this paper, we have presented a solar aware, energy efficient version of the sLEACH protocol. We introduced here an energy efficient radio model, a FIFO priority scheme in data gathering, a scan based cluster head selection, a heuristic approach to select a cluster head within a cluster and a collision minimized CSMA in our proposed protocol A-sLEACH with simulation. For future work, we have planned to add robust broadcast in our work. We have also desired to add and work upon query processing in our protocol. 7. References: [1] Thiemo Voigt, Hartmut Ritter, Jochen Schiller, Adam Dunkels, and Juan Alonso. Solar-aware Clustering in Wireless Sensor Networks. In Proceedings of the Ninth IEEE Symposium on Computers and Communications, June 2004.

[2] W. R. Heinzelman, A. Chandrakasan, and H. Balakrishnan,, "Energy-Efficient Communication Protocol for Wireless Microsensor Networks," Proc. of the 33rd Annual Hawaii International Conference on System Sciences(HICSS), pp. 3005-3014, Jan. 2000.

[3] C. S. Raghavendra, Krishna M. Sivilingam, Taieb Znati: Wireless Sensor Networks. [4] Anna Hac : Wireless Sensor Networks Design.

Table 1: LifeTimes Using Different amount of initial energy for the sensors. Energy (J/node)

Protocol Round First Node Dies

Round Last Node Dies

MTE 5 221 sLEACH 482.65 814.62

0.25

A-sLEACH 559.71 944.69 MTE 8 429 sLEACH 1141.7 1607.2

0.5

A-sLEACH 1323.99 1863.69 MTE 15 843 sLEACH 2263.8 3194.8

1

A-sLEACH 2625.08 3704.66

Figure 9: Number of Sensors Still Alive over Time

when, =100,

= 1000m1000m.

100

716

60

97 99

76

100

49

60

8

24 26

84

39

100

2738

18

65

100

63

36

95

20

4 12

60

7568

99

-20

0

20

40

60

80

100

120

0 500 1000 1500 2000Time (seconds)

No.

of S

enso

rs S

till A

live

A- sLEACH

sLEACH

412438414700416360458972.32

499900.98

336957343207365690380925

417708

0

100000

200000

300000

400000

500000

600000

0 1000 2000 3000 4000 5000Tim e (seconds)

Tota

l Rem

aini

ng E

nerg

y (J

oule

s)

A - sLEA CH

sLEACH

Figure 8: Total Remaining Energy vs Time when,

=100,

=1000m1000m, bsw =500000 Joules

0.1 0.14858

0.629550.769550.7075

1.5116 1.5079

0.685680.59909

0.1795

1.50161.5647

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

0 1000 2000 3000 4000 5000 6000

Time (seconds)

Ener

gy D

issi

patio

n pe

r N

ode

(Jou

les)

A-sLEACHsLEACH

Figure 7: Energy Dissipation per Node vs Time

when, =100,

= 1000m1000m.


Documents

[IEEE Sixth International Conference on Networking (ICN'07) - Sainte-Luce, Martinique, France (2007.04.22-2007.04.28)] Sixth International Conference on Networking (ICN'07) - A-sLEACH: