S Taruna, Sakshi Shringi / International Journal of Engineering Research and Applications(IJERA) ISSN: 2248-9622 www.ijera.comVol. 3, Issue 3, May-Jun 2013, pp.777-782777 | P a g eZone-Based Clustering Protocol for Heterogeneous WirelessSensor NetworksS Taruna*, Sakshi Shringi***(Department of Computer Science, Banasthali University, India)** (Department of Information Technology, Banasthali University, India)ABSTRACTWireless sensor networks (WSN) consistof hundreds or thousands of sensor nodes each ofwhich is capable of sensing, processing, andtransmitting environmental information. Whilewireless sensor networks (WSN) are increasinglyequipped to handle more complex functions, in-network processing still requires the batterypowered sensors to judiciously use theirconstrained energy so as to prolong the effectivenetwork life time. There are a few protocols usingsensor clusters to coordinate the energyconsumption in a WSN. In this paper, we proposea Zone based Heterogeneous Energy EfficientClustering (ZHEEC) protocol in order to balancethe energy consumption among all nodes. In thisprotocol we have divided the network intovarious equal size zones. We have implementedZHEEC protocol in network simulator:MATLAB. Simulation results show that ourmethod outperforms LEACH in terms of networklifetime.Keywords – Clustering, Sensor Nodes, ResidualEnergy, Wireless Sensor Networks, ZonesI. INTRODUCTIONWireless Sensor Networks are designed bymany small nodes which possess high sensing andwireless communication capabilities. Many routing,power management, and data disseminationprotocols have been specifically designed for WSNswhere energy awareness is an essential design issue.The focus, however, has been given to the routingprotocols which might differ depending on theapplication and network architecture .Routing protocols are one of the coretechnologies in the WSN. Due to its inherentcharacteristics, routing is full of challenge in WSN. Clustering is a well-know and widely usedexploratory data analysis technique, and it isparticularly useful for applications that requirescalability to hundreds or thousands of nodes .For large-scale networks, node clustering has beenproposed for efficient organization of the sensornetwork topology, and prolonging the networklifetime. Among the sources of energy consumptionin a sensor node, wireless data transmission is themost critical.At present, research on wireless sensor networks hasgenerally assumed that nodes are homogeneous. Inreality, homogeneous sensor networks hardly exist.This leads to the research on heterogeneousnetworks where two or more types of nodes areconsidered. However, most researchers prevalentlyassume that nodes are divided into two types withdifferent functionalities, advanced nodes and normalnodes. The powerful nodes have more initial energyand fewer amounts than the normal nodes, and theyact as clustering heads as well as relay nodes inheterogeneous networks. Moreover, they all assumethe normal nodes have identical length data totransmit to the base station. In , we haveresearched a heterogeneous sensor networks withtwo different types of nodes that they have sameinitial energy but different length data to transmit.In this paper, we have proposed a Zonebased Heterogeneous Energy Efficient Clustering(ZHEEC) protocol to balance the energyconsumption among all nodes. The WSN is dividedinto zones of equal size. ZHEEC helps to extend thenetwork lifetime with less consumption of energy inthe heterogeneous network. We have performedsimulations in MATLAB . Further, theperformance analysis of the proposed scheme iscompared with benchmark clustering algorithmLEACH .The remaining paper is organized as follows:Section 2 describes the related work, Section 3 givesdetail of the proposed ZHEEC protocol, Section 4evaluates the performance and simulation results andsection 5 gives the conclusion.II. RELATED WORKThe first and most popular energy efficienthierarchical clustering algorithm for WSNs that wasproposed for reducing power consumption isLEACH . In LEACH, the clustering task isrotated among the nodes, based on duration. Directcommunication is used by each CH to forward thedata to the Base Station (BS). It is an applicationspecific data dissemination protocol that usesclusters to prolong the life of the WSN. LEACH isbased on an aggregation (or fusion) technique thatcombines or aggregates the original data into asmaller size of data that carry only meaningfulinformation to all individual sensors. LEACHdivides the network into several clusters of sensors,
S Taruna, Sakshi Shringi / International Journal of Engineering Research and Applications(IJERA) ISSN: 2248-9622 www.ijera.comVol. 3, Issue 3, May-Jun 2013, pp.777-782778 | P a g ewhich are constructed by using localizedcoordination and control not only to reduce theamount of data that are transmitted to the sink, butalso to make routing and data dissemination morescalable and robust. Based on LEACH protocol,more clustered protocols have been proposed, likePEGASIS , TEEN , HEED  and BCDCP etc, but they all comes under the homogenouscondition.At present, the research to theheterogeneous networks has brought to the attention,and many literatures have obtained someachievements. In , authors proposed aprobability approach for real-time sensor networkapplications to assign and optimize sensor systemsusing heterogeneous functional units withprobabilistic execution time.In , authors examined the impact ofheterogeneous device deployment on lifetimesensing coverage and coverage aging process, andfound an optimal heterogeneous deployment canachieve lifetime sensing coverage by several timesas much as that with homogeneous deploymentconsidering both initial coverage and the duration ofsensing operation as well as the optimum number ofhigh-cost devices in the single-hop communicationmodel that maximizes the lifetime sensing coverageinformation incorporating several factors that affectthe initial sensing coverage and the energyconsumption of nodes.In , authors analyzed the operation of aclustered sensor network with two types of nodes,the powerful nodes and the normal nodes. Thepowerful nodes act as clustering-heads and expendenergy much faster than the normal nodes within itscluster until the cluster enters a homogeneous statewith all nodes having equal energy levels.In , we have examined a heterogeneoussensor network with two different types of nodespossessing same initial energy but sending differentlength data packet. We found that conventionalrouting protocols like LEACH etc. cannot ideallyadapt the network model proposed; therefore, wepropose a cluster based routing protocol to prolongthe network lifetime. The proposed algorithm betterbalances the energy consumption compared withconventional routing protocols and achieves anobvious improvement on the network lifetime.III. THE PROPOSED ZONE-BASEDHETEROGENEOUS ENERGY EFFICIENTCLUSTERING (ZHEEC) PROTOCOLIn this the WSN is divided into various zones ofequal size. Cluster heads for each zone are selectedwith the help of cluster head selection mechanism.We have made various assumptions to implementZHEEC protocol.1. Model Architecture and Basic Assumptions Number of nodes is 500 in the network. The WSN consists of heterogeneoussensor nodes. The BS is located inside WSN. Some sensor nodes have differentinitial energy. All sensor nodes and BS are stationaryafter deployment. All nodes can send data to BS. Data compression is done by CH. Data compression energy is differentfrom transmission and reception. In first round, each node hasprobability p of becoming the clusterhead. A node, which has become clusterhead, shall be eligible to becomecluster head after 1-1/p rounds Energy for transmission and receptionis same for all nodes. Energy of transmission depends on thedistance (source to destination) anddata size.2. Proposed Algorithm.We have considered a heterogeneous network withtwo types of nodes (normal and advanced nodes).Advanced nodes are more powerful and are havinghigher battery power than the normal nodes. Wehave assumed the cluster head selection is based onresidual energy of node.The total initial energy for new heterogeneousnetwork is given by the following equation:n.𝐸0(1-m) + n.m. 𝐸0 (1+𝛼) = n.𝐸0(1+m) (1)Where, n is number of nodes, m is proportion ofadvanced nodes.The probabilities of normal and advanced nodes arerespectively:p1 =𝑝𝑜𝑝𝑡(1+𝑚.𝛼)(2)p2=𝑝𝑜𝑝𝑡1+𝑚.𝛼. (1 + 𝛼) (3)The threshold value for normal nodes, T (s1) can becalculated by the following equation:T (s1) =𝑝11−𝑝1(𝑟.𝑚𝑜𝑑 1/𝑝1) .𝐸 𝑟𝑒𝑠𝐸 𝑚𝑎𝑥if s1 𝜖 G(4)0 OtherwiseSimilarly, threshold for advanced nodes T (s2) isevaluated.The proposed algorithm works in phases as follows: In the set-up phase:1) Network is virtually divided into 9 zones asshown in Fig. 1.
S Taruna, Sakshi Shringi / International Journal of Engineering Research and Applications(IJERA) ISSN: 2248-9622 www.ijera.comVol. 3, Issue 3, May-Jun 2013, pp.777-782779 | P a g eFigure 1: Deployment of heterogeneous WSN2) Each node generates a random probability (p) atthe beginning of round and computes the thresholdvalue (T(n)) with the help of equation (4).3) In case if p<pt, the node will be selected as acluster head.4) Selected CH broadcasts an advertisementmessage to all neighboring nodes.Figure 2: CH sends data to nodes5) The neighbor nodes collects the advertisedmessages during a given time interval and send a“join REQ” message to the nearest CH.6) The CH receives the “join-REQ” messages andbuilds a cluster member and broadcasts them to allneighboring nodes.7) The member node receives and save thismessage for data transfer. In the steady-state phase:1) After the completion of cluster selectionprocess, each member sends its data and residualenergy to the CH.2) The CH maintains residual energyinformation of all the member nodes. In the Pre-setup phase:1) The CH sends BS the maximum residual energyvalue of nodes belonging to its own clusterwhen the last frame of the round completes.2) BS finds the maximum residual energy value,𝐸 𝑚𝑎𝑥 of the network and sends back this valueto CH.3) The CH broadcasts value of 𝐸 𝑚𝑎𝑥 to all clusternodes.4) Each node save the value 𝐸 𝑚𝑎𝑥 for the nextcomputation of T(n) and the current round isterminated.IV. PERFORMED EVALUATIONS ANDRESULTSThe performance analysis of ZHEECprotocol is evaluated with MATLAB. The protocolis then compared to the heterogeneous LEACHalgorithm, in which cluster selection is done byrandomly.1. Energy Consumption ModelWe assume a simple model  for theradio hardware energy dissipation where thetransmitter dissipates energy to run the radioelectronics and the power amplifier, and the receiverdissipates energy to run the radio electronics. For theexperiments described here only the free spacechannel model is used. Thus, to transmit an l-bitmessage a distance d, the radio expends energy:𝐸 𝑇𝑥 (l, d) = ( l 𝐸𝑒𝑙𝑒𝑐 + l 𝐸𝑓𝑠 d2 ) (5)To receive this message, the radio expends energy:𝐸 𝑅𝑥 (l) =l𝐸𝑒𝑙𝑒𝑐 (6)2. Simulation ParametersTable 1: Simulation ParametersParameters ValuesNetwork size 200m * 200mNumber of Nodes 500Node distributionNodes are uniformlydistributedInitial Energy 0.5 JData Packet size 4000bitsBS position 100m * 100mEelec 50nJ/bit𝐸 𝑇𝑥 = 𝐸 𝑅𝑥 50nJ/bit∈ 𝑓𝑠 10 pJ/bits/𝑚2∈ 𝑎𝑚𝑝 0.0013 pJ/bit/𝑚4EDA 5 nJ/bit𝛼 1p 0.5
S Taruna, Sakshi Shringi / International Journal of Engineering Research and Applications(IJERA) ISSN: 2248-9622 www.ijera.comVol. 3, Issue 3, May-Jun 2013, pp.777-782780 | P a g e3. Simulation Results3.1 Network Lifetime: When any node in thenetwork is dead, it is no longer the part of thatnetwork. This implies that if a dead node occurs inearly rounds of algorithm, it will affect the network.This may also lead towards the early dead of all thenodes in the network. In this simulation we haveobserved the first dead node by keeping the basestation position at (100,200) with 4000 packet size.Table 2 shows the values and Fig. 3 concludes thatZHEEC is better compared to LEACH protocol.Table 2: Network Lifetime (First Node Dead)Figure 3: Network Lifetime (First Node Dead) v/sSimulation Runs3.2 Network Lifetime with last node dead:In this we have observed the round number in whichall nodes in the network are dead. If all nodes aredead in the network, the lifespan of a network isover. Less the round number, lesser is the lifetime ofnetwork. The base station is positioned at centrewith 4000 packet size. Table 3 and Fig. 4 shows thedead nodes with number of rounds.Table 3: Network Lifetime (All Nodes Dead)Figure 4: Network Lifetime (All Nodes Dead) v/sSimulation Runs3.3 Network Lifetime (First Node Dead)with varying packet size: Even on varying the packetsize the network lifetime for the proposed ZHEECprotocol remains better than that of LEACH. Table 4and Fig. 5 Shows the comparative results.Table 4: Network Lifetime (First Node Dead) withVarying Packet SizeSimulationRunRound Number when fistnode is deadLEACH ZHEEC1 437 6322 500 6603 461 6374 554 7205 475 6746 452 6357 466 7118 531 6969 520 69410 447 740SimulationRunRound Number when allnodes are deadLEACH ZHEEC1 1810 23122 2142 24543 1985 22204 1865 25315 2135 26526 1852 24317 1863 25628 1921 23209 21 02 242110 1820 2465PacketSizeRound Number when firstnode diesLEACH ZHEEC12000 321 41210000 346 4528000 472 6136000 541 6254000 611 7502000 725 910
S Taruna, Sakshi Shringi / International Journal of Engineering Research and Applications(IJERA) ISSN: 2248-9622 www.ijera.comVol. 3, Issue 3, May-Jun 2013, pp.777-782781 | P a g eFigure 5: Network Lifetime (First Node Dead) withVarying Packet Size3.4 Residual Energy of the Network: Wesimulated the proposed protocol to get the value ofresidual energy left for the network at differentrounds. Table 5 and Fig. 6 shows the results.Table 5: Residual Energy in Joules for differentroundsFigure 6: Residual Energy v/s Round NumberV. CONCLUSIONIn this paper, we have proposed a Zone-Based Heterogeneous Energy Efficient Clustering(ZHEEC) protocol. It is a cluster based routingprotocol that considers energy of nodes to extend thenetwork lifetime. We have compared the results ofproposed ZHEEC protocol with heterogeneousLEACH in aspects of network lifetime. The resultsshow that our protocol clearly makes the networklifetime much longer without other critical overheadand performance degradation.In future we can easily extend our analysisto scenarios in which unreliable nodes are deployedrandomly or along grid points. We can also compareour protocol with other protocols such as HEED,PEGASIS and TEEN.ACKNOWLEDGEMENTSWe take the opportunity to express ourgratitude and thanks toward all the people who havebeen a source of guidance and inspiration to usduring the course of this paper.Last but not the least we would like tothank all our friends, for giving useful suggestionand ideas for improving our performanceREFERENCES Imad Aad, Mohammad Hossein Manshaei,and JeanPierre Hubaux, “ns2 for theimpatient”, EPFL Lausanne, Switzerland,March, 2009. H. W. Kim, H. S. Seo (2010), “Modeling ofEnergy-efficient Applicable RoutingAlgorithm in WSN”, International Journalof Digital Content Technology and itsApplications, vol. 4, no. 5, pp.13-22. W. B. Heinzelman, A. P.Cnandrakasan,(2002) “An application-specific protocol architecture for wirelessmicrosensor networks,” IEEE Transactionson Wireless Communications, vol. 1, no. 4,pp. 660-670. Li, X., Huang, D., Yang, J.: EnergyEfficient Routing Protocol Based onResidual Energy and Energy ConsumptionRate for Heterogeneous Wireless SensorNetworks. In: The 26th Chinese ControlConference, vol. 5, pp. 587–590 (2007) http://www.mathworks.in Wendi Rabiner Heinzelman(2000).“Energy-EfficientCommunication Protocol for WirelessMicrosensor Networks” In Proceedingof the 33rd Hawaii InternationalConference on System Sciences,pp1-10 W.R. Heinzelman, A. Chandrakasan, andH. Balakrishnan, An Application-SpecificProtocol Architecture for WirelessMicrosensor Networks. In IEEETransactions on Wireless Communications(October 2002), vol. 1(4), pp. 660-670 Lindsey, S., Raghavendra, C.S.: PEGASIS:Power-efficient gathering in sensorinformation systems. In: Proc. of the IEEEAerospace Conf. Montana: IEEE Aerospaceand Electronic Systems Society, pp. 1125–1130 (2002)RoundNumberResidual EnergyLEACH ZHEEC500 23.595 35.5671000 15.097 26.1201500 6.2684 17.4752000 3.1902 9.40932500 2.5828 5.87123000 0.5632 4.0321
S Taruna, Sakshi Shringi / International Journal of Engineering Research and Applications(IJERA) ISSN: 2248-9622 www.ijera.comVol. 3, Issue 3, May-Jun 2013, pp.777-782782 | P a g e Manjeshwar, A., Agrawal, D.P.: TEEN: Aprotocol for enhanced efficiency in wirelesssensor networks. In: Int’l Proc. of the 15thParallel and Distributed Processing Symp.,pp. 2009–2015. IEEE Computer Society,San Francisco (2001) Ossama Younis and Sonia Fahmy,Distributed Clustering in Ad-hoc SensorNetworks: A Hybrid, Energy-EfficientApproach., September 2002. Qiu, M., Xue, C., Shao, Z., Zhuge, Q., Liu,M., Sha Edwin, H.M.: Efficent Algorithmof Energy Minimization forHeterogeneous Wireless Sensor Network.In: Sha, E., Han, S.- K., Xu, C.-Z., Kim,M.H., Yang, L.T., Xiao, B. (eds.) EUC2006. LNCS, vol. 4096, pp. 25–34.Springer, Heidelberg (2006) Jae-Joon, L., Bhaskar, K., Kuo, C.C.:Impact of Heterogeneous Deployment onLifetime Sensing Coverage in SensorNetworks. In: First Annual IEEECommunications Society Conference onSenor and Ad Hoc Communications andNetworks, pp. 367–376 (2004) Lee, H.Y., Seah, W.K.G., Sun, P.: EnergyImplications of Clustering inHeterogeneous Wireless Sensor Networks-An Analytical View. In: The 17th AnnualIEEE International Symposium onPersonal, Indoor and Mobile RadioCommunications, pp. 1–5 (2006) Li, X., Huang, D., Yang, J.: EnergyEfficient Routing Protocol Based onResidual Energy and Energy ConsumptionRate for Heterogeneous Wireless SensorNetworks. In: The 26th Chinese ControlConference, vol. 5, pp. 587–590 (2007) Tsai, Y.R., 2007. “Coverage-PreservingRouting Protocols for RandomlyDistributed Wireless SensorNetworks,”IEEE Transactions on WirelessCommunications, vol.6, no. 4, pp. 1240-1245. 56.AuthorsS.Taruna is an active researcher in the field ofcommunication and mobile network, currentlyworking as Associate Professor in Department ofComputer Science at Banasthali University(Rajasthan), India. She has done M.Sc fromRajasthan University and PhD in Computer Sciencefrom Banasthali University (Rajasthan), India. Shehas presented many papers in National andInternational Conferences, published 7 papers invarious journals and reviewer of various journalsand conferences.Sakshi Shringi received B.TECH degree inInformation Technology from Rajasthan TechnicalUniversity, Kota in 2011. She is pursuing herM.TECH degree in Information Technology fromBanasthali University (Rajasthan). She has presentedmany papers in National and InternationalConferences, published 4 papers in various journals.Her research interest includes computer network,wireless sensor and ad-hoc networks andvirtualization.