2014 IEEE Students’ Conference on Electrical, Electronics and Computer Science

Optimal Load Distribution of Cluster Head in Fault-TolerantWireless Sensor Network

Moumita Samanta, Indrajit BanerjeeDepartment of Information Technology

Bengal Engineering and Science University, Shibpur, Howrah, India.Email: moumita.samanta1@gmail.com, ibanerjee@it.becs.ac.in

Abstract—Wireless sensor network (WSN) is undoubtedly anarea of sophisticated research work. The credibility of thisastonishing system may be affected by faults due to harsh andhazardous natural calamities from time to time. A WSN that isnot ready to deal with such challenging situations may suffer areduction in overall lifetime or may lead to dire consequences incritical application context. So fault tolerance technique is one ofthe most vital approach to renew the default condition. In thispaper we propose a method to support fault tolerant by functiondistribution. Initially, the entire network is considered as a set ofclusters. One cluster head is selected from each cluster and latersome of its functions are distributed between its two neighbours.This is achieved in such a way that the energy consumption of thenetwork gets minimised. Through simulation we have establishedthat our proposed schema reduces the cluster head load andprolong the network life span.KEYWORDS: Wireless sensor network (WSN), Cluster head,Base station (BS), Load distribution.

I. INTRODUCTION

Wireless sensor network (WSN) has recently attracted sig-nificant research attention due to its wide range of appli-cations. WSNs are composed of hundreds to thousands ofsmall wireless sensors that can be mobile or static which aredistributed in a large area according to the requirements ofthe application [1]. The principal function of these sensors isto sense the event occurring in the area and route the senseddata to the base station. Recently, the use of WSNs to monitorstorage, regulations of hazardous materials in chemical plantwas investigated in [1]. In this critical industrial environment ahigh degree of dependability is required. So the characteristicof WSNs should be reliability, availability and maintainability.A careful resource management is also required as each sensornode depends on energy for its activities [2]. A fault is anykind of defect that leads to an error. An error correspondsto an incorrect system state. Such a state may lead to afailure. A failure is the manifestation of an error, which occurswhen the system deviates from its specification and cannotdeliver its intended functionality. Failure of one node due toits limited battery lifetime, hardware break- down, softwaremalfunctioning, communication error or malicious attacks canaffect the entire network. So, the network should be designedsuch a way to provide fault tolerance.The technical core of this paper is to focus on fault toleranceof cluster head. Cluster is formed and one node is chosen ascluster head in each cluster. We also underline the advantage ofdistribution of cluster head’s responsibility to its neighbouring

nodes. Authentication of nodes in individual cluster is per-formed for secure transmission. Then data is aggregated andtransmitted to base station. Reducing the function of clusterhead, node authentication and secure data transmission helpin fault tolerant network design and efficient data routing.The rest of the paper is organized as follows: Section IIdiscusses the related surveys done so far in this area. TheSection III describes about the problem formulation of ourproposed model followed by section IV where we discussabout our proposed method and in section V certain relatedmathematical analysis is done. A brief discussion on the pro-posed algorithm is given in Section VI. Section VII evaluatesthe performance of the proposed model. Finally,in section VIIIa brief conclusion and future scopes for the work are discussed.

II. LITERATURE SURVEY

Wireless sensor nodes are usually deployed in those inacces-sible areas where it is important to reduce the fault of sensornodes to prolong the network lifetime. Many techniques havebeen proposed for fault detection, fault tolerance and repair insensor networks [2,3,4,5]. A survey on fault tolerant routingtechniques in Wireless Sensor networks is found in [6]. In[7] they have studied LEACH protocol, some of its modifiedversions and finally have put forward a new version of LEACHcalled Energy Efficient Extended LEACH (EEE LEACH)protocol. This new version of LEACH protocol establishesmultilevel clustering approach to minimize communicationdistance between nodes and introduce Master Cluster Headsalong with Cluster heads.

Fault tolerance based on network availability and perfor-mance has been discussed in [3]. Hierarchical and cluster-based approaches for fault detection and repair have also beendealt with in [8]. In [9], a cluster-based energy- efficient faulttolerant protocol is proposed and a novel mechanism for errordetection and fault recovery to recover cluster-heads efficientlyhas been discussed.[10]discusses a method where every faultynode is replaced with another node declared as redundant.But if the number of redundant nodes is less than those offaulty nodes, then this procedure does not work properly.Inmost of the previous articles[11][12][13], it has been proposedthat the different essential functions like authentication, datareceiving & aggregation, data transmission can be carried outby a single cluster head only. The main drawback is that allthe aforementioned functions can not be implemented overa single cluster head in unison. In some cluster-based fault978-1-4799-2526-1/14/$31.00 c© 2014 IEEE

tolerant protocols[13], all the functions present in the originalcluster head are transferred to another alternate head whenthe former becomes prone to failure. The transfer results inadditional load over the new head. This is a major drawbackof this algorithm. In[14] a distributed, randomized clusteringalgorithm for WSN is proposed to organize the sensors intoclusters. Then the algorithm is extended to generate a hierarchyof cluster-heads and it has been observed that the energysavings increase with the number of levels in the hierarchy.Main drawback of this paper is that if the number of forcedcluster-heads is increased then energy consumption is more.This is because forced cluster-heads consist of only one nodeand thus it invariably cannot form a cluster.In the next section we discuss about our problem formulation.

III. PROBLEM FORMULATION

In our proposal, fault tolerance of network can be achievedthrough the load distribution of cluster head. Load distributionreduces the overhead of cluster head. Due to reduction ofthis overhead, the fault occurrence diminishes. Fault tolerancecan also be enhanced by node authentication and securetransmission of data. If authentication is not performed, thensome unknown sources may generate a bulk amount of datawhich if received by the cluster head, probability of systemfailure will be on the rise.Cluster formation and Cluster head detection: Cluster isformed according to the co-ordinate values of the sensor nodesas shown in Fig 1(for uniform distribution) and Fig 2 (for non-uniform distribution). The cluster head is selected in the centerof the cluster for both uniform and non-uniform deploymentof nodes. In case of non-uniform deployment, if there is nonode in the center, then choose nearest node from the centeras cluster head.After the selection of cluster head, the load of cluster head isdistributed among its two neighbouring nodes.

Cluster head

Member node

X axis

Y axis

cluster 3 cluster 4

cluster 1 cluster 2

Fig. 1. Cluster formation for uniform distribution of nodes.

Fault tolerant data transmission : One neighbouring node ofcluster head performs authentication and another one transmitsdata. Through cluster head and transmission head only theauthenticated nodes are allowed to transmit data to the basestation .

Member node

Cluster head

Y axis

X axis

cluster 2

cluster 3 cluster 4

cluster 1

Fig. 2. Cluster formation for uniform deployment.

IV. PROPOSED METHOD

In this paper we will mainly concentrate on the distributionof the load of a cluster head to its neighbouring nodes. Thefunctions of the cluster head are as follows:-a. Data receiving and Data aggregation: Cluster head collectsdata from its member nodes which are within the respectivecluster and then aggregates the received data.b. Authentication: Authentication is required to prevent clusterhead from malicious attacks if in case they receive unautho-rized data from unknown source.c. Data transmission: Cluster head transmits the aggregateddata to the base station.d. Routing: For those cluster heads which reside far from thebase station and cannot directly send data to it, require routing.They send data to another cluster head which is within thetransmission range of the former and also nearer to the basestation.

Cluster head

Member node

Base Station

Transmission and routing head

Non-uniform distribution of nodes Uniform distribution of nodes

Authentication head

Fig. 3. Cluster head and its neighbouring nodes position in a cluster.

The node lying in the centre position of a network is eventuallyselected as the cluster head as shown in Fig 3. This isbased on the evaluation of the proposed theorem 1. Thecluster head performs the most important role of selecting thetransmission & routing head and authentication head amongthe neighbouring nodes and it itself performs data receivingand data aggregation.

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A separate node named authentication head is selected amongthe neighbouring nodes of the cluster head which has min-imum distance from cluster head as shown in Fig 3. In thesame cluster all the nodes have the same predefined signaturevalue which is only known to the nodes within that cluster.Authentication head performs authentication through sendingrequest for signature value to all nodes within that cluster.After receiving the signature value it checks with its own. Ifthe value matches then only authentication head grants access.The authenticated nodes will only be able to participate in datatransmission.Another individual node, viz. transmission and routing head,is selected among the neighbouring nodes of the cluster headwhich has minimum distance from base station as shown inFig 3. This is again based on the evaluation of the proposedtheorem 1. It chooses the routing path and performs transmis-sion between the cluster head and base station. This selectionof a separate node is performed because a large amount ofenergy is required for this function. So, if the cluster head isassigned to do this task, it will lose energy at a very rapid ratewhich should be avoided.

V. THEOREM

A. Theorem 1 :

In cluster based topological connection, all cluster membernodes transmit their data to cluster head. The suitable positionof the cluster head for data receiving and aggregation is at themiddle of the cluster. Transmission & routing head is selectedamong the neighbouring nodes of the cluster head which hasminimum distance from the base station. For this position ofthe heads, more energy gets saved as compared to the otherposition in the cluster.

Proof: 1) In cluster based node management system, clusterheads are selected between cluster member nodes.

(a,b)

(x1, y1)

(x2, y2)

cluster head positionmember nodes position

A

B

Fig. 4. Cluster head node position in a cluster.

Let us consider the cluster head position of the cluster tobe (a,b) and cluster member nodes position is (xi, yi) where1 ≤ i ≤ n and n is the total number of nodes in a cluster (Fig4). Then energy loss of the cluster member nodes for datatransmission to cluster head is (from [16])

Ei = (α1 + α2((xi − a)2 + (yi − b)2))× β (1)

The data packet size is β. The energy consumed in thetransmitter circuit is α1 and energy consumed in the am-

plifier circuit is α2. Length of the diagonal of a grid ist. Coordinates of node A and B are(x1, y1) and (x2, y2)respectively. Distance between cluster head and node A is t1(√(x1 − a)2 + (y1 − b)2). So the distance between the cluster

head and node B is (t−t1) (√(x2 − a)2 + (y2 − b)2). Energy

loss due to data transmission by these two nodes is

E1+E2 = (α1+(α2×t21)+α1+(α2×(t−t1)2))×β (2)

If we differentiate the equation (2) with respect to distance wegetd

dt1(E1 + E2) = α2 × (4t1 − 2t)× β (3)

d2

dt21(E1+E2) = α2×4×β (4)

From equation (4) we can say the energy consumption isminimum and from equation (3) we can write,

α2× (4t1−2t)×β = 0 (5)

So from equation (5) we get t1 = t/2. We can say that thecluster head position is at the middle of the diagonal whichimplies that it is at the centre of the grid. This is also true forn number of nodes as the grid is a square which is symmetric(proved).

2) Energy loss due to transmission is proportional to squareof the source to destination distance (from [16]).

Etr ∝ distance2 (6)

Let consider distance between cluster head and neighbouring

Base Station

Neighbour Nodes

Cluster Head

A

B

Fig. 5. Transmission and routing head selection in a cluster.

nodes A and B are d1 and d′1 respectively. As both of themare the neighbouring nodes of the cluster head. So,

d1 ' d′1 (7)

As grid size is 2 unit length d1, d′1 ≤ 2. Distance between

the base station and A and B are d2 and d′2 respectively. A isnearer to the base station (Fig 5). So

d2 < d′2 (8)

Energy loss due to data transmission to base station from Aand B are EA and EB respectively. From equation(6) we canwrite,

EA ∝ (d1 + d2)2 (9)

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EB ∝ (d′1 + d′2)2 (10)

From equation (7),(8),(9) and (10) we can write

EA < EB (proved)

So, node A which one is nearest to the base station is selectedas transmission and routing head.

B. Theorem 2 :In case of wide area communication energy consumption

due to multi-hop communication is lesser than the directcommunication.

Proof:In direct communication a node sends data to thebase station. Let the distance between base station and thatnode is d. In case of multi-hop communication node send datato an another node that node sends data to the base station.Let distance between sender node and middle node is d1 anddistance between base station & later node is d2. So we canwrite

d = d1 + d2 (11)

The data packet size is β. The energy consumed in the trans-mitter/receiving circuit is α1 and energy consumed in amplifiercircuit is α2. The η is power index for the channel path lossof the antenna which is usually 2 ≤ η ≤ 4(from [15]).Energy loss due to channel transmission for relatively shortdistance transmissions is proportional to d2 and energy lossdue to channel transmission for long distance transmissions isproportional to dη where η 6= 2(from [15]).In case of direct communication energy consumption by asensor node is

Ed = (α1 + (α2 × dη))× β (12)

In case of multi-hop communication energy consumption bya sensor node due to data transmission is

Et = {α1 + (α2 × d21) + α1 + (α2 × d22)} × β (13)

In case of multi-hop communication energy consumption bya sensor node due to data receiving is

Er = (α1 × β) (14)

From equation (13) and (14) we can write total energyconsumption by a sensor node is

Eh = Et + Er (15)

From equation (12) and (15) we can write

Ed − Eh = β(α2((d1 + d2)η − d21 − d22)− 2× α1)

= 2×β×α1{α2

α1((d1+d2)

η−d21−d22)−1} (16)

For wide area communication

(d1+d2)η >> d21+d

22 ⇒ (d1+d2)

η−d21−d22 >> 0 (17)

From equation (16) and (17) we can say

Ed > Eh (proved)

C. Theorem 3:

In our proposed algorithm we have divided the network intogrids where the nodes are deployed. The energy consumptionof grid based regular network is less than random network.

proof Grid network is a relatively simple sensor network.In a grid sensor network with the fixed transmit radii, asensor node is deployed at each grid point, each node collectsinterested data regularly and transmit them to the cluster headand cluster head sends it to base station. The energy utilizationrate of grid sensor network is(from [17])

η =2(2H + 1)

3H(H + 1)(18)

Generally, the sensor nodes may be spread in a random mannerin the interested surveillance field, thus formulate the randomsensor network. The energy utilization rate of the randomuniform network can be written(from [17])

η′ =(H + 1)(4H − 1)

6H3(19)

In the equation (18) and(19) H denotes the hop count. In ourproposed algorithm maximum hop count is 3.For H=1,2,3 fromequation (18) and (19) we can write

η′ ≤ η (20)

From equation(20) we can write, the random network isconcerned, the energy wasted is much heavier than that inthe grid network.

VI. PROPOSED ALGORITHM

We have proposed the algorithm for both uniform and non-uniform deployment of nodes. We consider the whole networkas a grid. For uniform distribution each grid consists of onenode. But for non-uniform each grid may or may not consistof nodes.In Algorithm 1 (Main Algorithm) cluster head is selected forthe first time. For selection of transmission & routing headand authentication head trans head and authen head functionsare respectively called. Energy loss due to data transmission,data receiving, data aggregation and node authentication iscalculated. When residual energy of cluster head is less thanthe threshold, then we use the cluster head function. If theresidual energy of transmission and routing head is lessthan the threshold then trans head function is called. Theauthen head function is called if the residual energy of theauthentication head is less than that of the threshold. Thiswhole process gets repeated until the first node dies.In Algorithm 2, alternate cluster head is selected when residualenergy of the previous cluster head is less than the thresholdvalue. The new cluster head is selected among the neighbour-ing nodes of first cluster head. Also, those nodes which havenot been previously chosen, can also be considered.In Algorithm 3, transmission & routing head is selectedbetween those nodes which are in the neighbourhood of clusterhead and it has minimum distance from the base station.In Algorithm 4, authentication head is selected out of the

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neighbouring nodes of cluster head and it has minimumdistance from the cluster head.

Algorithm 1 Main AlgorithmInput: Grid graph G and static sensor nodes coordinate

location.Output: Iteration number, Energy consumptionStep 01: FOR each cluster SNStep 02: Insert all nodes of ithcluster in set SNi

Step 03: Select cluster head in set SNi

Step 04: Insert neighbouring nodes of ithcluster head in set Ni

Step 05: Find transmission & routing head in set SNi

Step 06: Call trans head functionStep 07: Find authentication head in set SNi

Step 08: Call authen head functionStep 09: DoStep 10: Calculate energy loss by cluster head for each iterationStep 11: Calculate residual energy of cluster headStep 12: Calculate energy loss by transmission & routing head

for each iterationStep 13: Calculate residual energy of transmission & routing

headStep 14: Calculate energy loss by authentication head for each

iterationStep 15: Calculate residual energy of authentication headStep 16: Calculate total energy loss for each iterationStep 17: Calculate total energy loss for each iterationStep 18: Increase iteration number by oneStep 19: IF residual energy of cluster head less than threshold

THENStep 20: Call cluster head functionStep 21: ELSEStep 22: IF residual energy of transmission & routing head

less than threshold THENStep 23: Call trans head functionStep 24: ELSEStep 25: IF residual energy of authentication head

less than thresholdTHENStep 26: Call authen head functionStep 27: END IFStep 28: END IFStep 29: END IFStep 30: END WHILE(total energy loss greater than threshold)Step 31: END FOR

Algorithm 2 cluster head functionInput: The set Ni and nodes’ coordinate location.Output: Alternate cluster head selectionStep 01: Insert all nodes from set Ni to set Ni except selected headsStep 02: Select the nearest node of center as cluster headStep 03: For selection of transmission & routing headStep 04: Call trans head functionStep 05: For selection of authentication headStep 06: Call authen head functionStep 07: Replace the set Ni with the elements of the set Ni

Algorithm 3 trans head functionInput: The set Ni and nodes’ coordinate location.Output: Transmission & routing head selectionStep 01: Insert all nodes from set N to set Ni except selected headsStep 02: Calculate the residual energy of nodes in set Ni

Step 03: Find the nearest node from the base station in set Ni

step 04: Select the transmission & routing headstep 05: Replace the set Ni with the elements of the set Ni

Algorithm 4 authen head functionInput: The set Ni and nodes’ coordinate location.Output: Authentication head selectionStep 01: Insert all nodes from set N to set Ni except selected headsStep 02: Calculate the residual energy of nodes in set Ni

Step 03: Find the nearest node from cluster head in set Ni

step 04: Select the authentication headstep 05: Replace the set Ni with the elements of the set Ni

VII. SIMULATION RESULTS

Our simulation results show that the proposed algorithm canreduce the overhead of cluster head and provide an energy-efficient mechanism.Different parameters for this simulation are given in Table 1

TABLE IPARAMETERS CONSIDERED FOR SIMULATION

Parameter Values Values(uniform) (non-uniform)

Size of the network 400m2 to10000m2

400m2 to6400m2

Number of nodes 100 to 2500 110 to 2060Size of grid 2m×2m 2m×2mTransmission range ofsensor node 40m 40mData packet size 800 bits 800 bitsInitial energy .5J .5JEnergy loss by transmitterelectronics circuit(α1) 50nJ/bit 50nJ/bitDissipated energy bytransmit op-amp(α2) 10pJ/bit/m2 10pJ/bit/m2

Energy loss due toData aggregation 5nJ

/bit/message5nJ/bit/message

In our proposed algorithm all the nodes are static. All sensornodes are divided into a number of clusters, and each clusterexecutes the algorithm independently. We have assumed thatall the nodes within one cluster are homogeneous. The com-munication environment is contention and error-free; hencesensors do not have to retransmit any data. To evaluate theperformance of our algorithm for both uniform and non-uniform deployment of nodes, simulation is carried out usingC in Linux.

A. Simulation Results for Uniform Sensor Node Distribution

We consider the nodes are distributed uniformly. Eachcluster consists of 25 nodes.

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Fig. 6. Energy loss due to load distribution of cluster head

Figure 6 shows the energy loss by cluster head, authentica-tion head and transmission & routing head in one round fordifferent set of nodes. In the Figure 6 we can observe thatthe energy loss by the transmission & routing gets graduallyincreased with the increasing of number of nodes and sodoes the network size. As a result, the sensor nodes and thetransmission & routing head which are far from the basestation cannot perform direct transmission with the latter.The transmission & routing head transmits their data throughanother transmission & routing head which can directly com-municate with the base station. This process is known as multi-hop communication.

Fig. 7. No of rounds before first node dies

From the result given in Figure 6 we can deduce, if with theincreasing node numbers, energy loss by the transmission &routing head also gets gradually increased. So even beforethe cluster head decays, transmission & routing head dies.To avoid and henceforth to improve this situation, one of theneighbouring nodes is allotted the character of transmission &routing head. It will work until the cluster head dies. If werepeat the process until the first node dies, we get result asthe one shown in Figure 7.

B. Simulation Results for Non-uniform Sensor Node Distribu-tion

We consider the nodes are distributed non-uniformly. Eachcluster consists of 25 grids.As the nodes are distributed non-uniformly, we repeat thesimulation 10 times and take the average result for each setof node numbers shown in Figure 8.

Fig. 8. No of rounds before first node dies

C. Fault Rate Calculation

The system works better if the fault rate is under control. Inour proposed algorithm, the cluster head distributes its workload to the neighbouring nodes. This directly results in lessenergy dissipation leading to the increase in network lifetime.So fault rate gradually decreases with the increasing numberof nodes as shown in Figure 9. Fault rate varies from 13 % to23 %.

Fig. 9. Fault rate calculation

D. Comparison with Other Existing Algorithms

Fig. 10. Energy loss by the cluster heads

Now we compare the energy loss by the cluster head afterthe load distribution. In Figure 10 it is depicted that the energyloss by the cluster head for the proposed technique is almost90 % to 92% less than the existing techniques like LEACH,

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EEE LEACH(Energy Efficient Extended LEACH)(from [7]).We take the energy consumption value by the cluster head upto 5th iteration.

Fig. 11. No of rounds before first node dies

In our proposed algorithm, load is distributed, so energyconsumption is less than the existing techniques (LEACH,EEE LEACH) where cluster head performs all the tasks. Forthis reason, running time of the cluster head as well as thenumber of rounds(i.e. the time when the first node dies)ismuch higher in our method as compared with the existingones (LEACH, EEE LEACH). This is shown in Figure 11.

VIII. CONCLUSIONS AND FUTURE WORKS

Wireless sensor has a wide range of applications. Enhancingenergy-efficiency is primordial in a wireless sensor network.This paper proposes a load distribution technique for large-scale networks. The results obtained by performing a simula-tion of our proposed algorithm give satisfactory performanceas compared to the existing ones. In future we can furtherimplement this algorithm in hardware.

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