Open Access Open Access  Restricted Access Subscription or Fee Access

Relay Node Selection Based Reduced Energy Consumption in Heterogeneous Wireless Sensor Network

Aradhana Tirkey, Deepti Kakkar


Energy conserving optimization is of chief concern while scheming a wireless sensor network (WSN) as most of the sensor nodes are furnished with limited power supply. In this paper, we focus on minimizing energy consumption and maximizing network lifetime in three-tiered network architecture. For this obvious goal, clustering techniques are a boon with a hierarchical arrangement to boost the performance of the network as well as reduce the consumption of energy. For a distantly located base station, a sensor node will require large amount of energy for the single hop communication. As a result eventual exhaustion of node energy and hence, shortened network lifetime and also network failure.  To overcome this unavoidable situation, relay nodes are being used to exploit the benefits of multihop transmission to save the energy. In this work, the proposed method for relaying is based on genetic algorithm (GA) approach in terms of node’s initial energy, residual energy, distance to base station and the probability of getting selected as cluster head. It is designed to assure minimum energy cost as well as save the nodes with comparatively low residual energy. Finally, simulations have been performed to prove the helpfulness of the proposed approach.

Cite this Article Tirkey A, Kakkar D. Relay Node Selection Based Reduced Energy Consumption in Heterogeneous Wireless Sensor Network. Journal of Mobile Computing, Communications & Mobile Networks. 2016; 3(2): 7–14p. 


relay node, heterogeneous environment, clustering algorithm, lifetime

Full Text:



Akyildiz IF, Sankarasubramaniam Y, Cayirci E. Wireless sensor networks: a survey. Computer Networks. 2002; 38: 393–422p.

Heinzelman WB, Chandrakasan AP, Balakrishnan H. An Application-Specific Protocol Architecture for Wireless Micro sensor Networks. IEEE Transactions on Wireless Communications. 2002; 1: 660–70p.

Tuah N, Ismail M, Jumari K. Energy efficient algorithm for heterogeneous wireless sensor network. Proceedings of the 2011 IEEE International Conference on Control System, Computing and Engineering (ICCSCE); 2011 Nov 25–27; Penang, Malaysia. 92–96p.

Tuah N, Ismail M, Jumari K. Extending Lifetime of Heterogenous Wireless Sensor Network using Relay Node Selection. Proceedings of the 2013 IEEE International Conference on International Conference of Information and Communication Technology (ICoICT); 2013 Mar 20–22; Bandung, Indonesia. 17– 21p.

Duo P, Ming-hua C. An Energy Efficient Routing Protocol for Wireless Sensor Network. Proceedings of the 2010 International Conference on Internet Technology and Applications; 2010 Aug 21–23; Wuhan, China. 1–4p.

Alla SB, Ezzati A, Hssane AB, et al. Hierarchical adaptive balanced energy efficient routing protocol (HABRP) for heterogeneous wireless sensor networks. Proceedings of the 2011 International Conference on Multimedia Computing and Systems (ICMCS); 2011 Apr 7–9; Ouarzazate. 1–6p.

Smaragdakis G, Matta I, Bestavros A. SEP: A Stable Election Protocol for Clustered Heterogenous Wireless Sensor Networks. Proceedings of the 2nd International Workshop on Sensor and Actor Network Protocols and Applications; 2004 Aug 22; Boston, Massachusetts. 121–9p.

Kumar D, Aseri TC, Patel RB. EEHC: Energy Efficient Hetergenous Clustered Scheme for Wireless Sensor Networks. Computer Communications. 2009; 32(4): 662–7p.

Qing L, Zhu Q, Wang M. Design of a distributed energy-efficient clustering algorithm for heterogeneous wireless sensor network. Computer Communications. 2006; 29: 2230–7p.

Norouzi A, Zaim AH. Genetic Algorithm Application in Optimization of Wireless Sensor networks. The Scientific World Journal. 2014; 2014: 286575.

Pal V, Yogita, Singh G, et al. Cluster Head Selection Optimization Based on Genetic Algorithm to Prolong Lifetime of Wireless sensor networks. Proceedings of the 3rd International Conference on Recent Trends in Computing; 2015 Mar 12–13; Ghaziabad, India. 1417–23p.

Goldberg DE. Genetic Algorithm in a Search, Optimization and Machine Learning. USA: Addison-Wesley Longman Publishing Co. Inc.; 1989.

Kim JH, Lee MJ. Green IT: Technologies and Applications. Berlin, Germany: Springer; 2011. 20–22p.

Yarvis M, Kushalnagar N, Singh H, et al. Exploiting heterogeneity in sensor networks. Proceedings of the IEEE 24th Annual Joint Conference of the IEEE Computer and Communications Societies; 2005 Mar 13–17; Hyatt Regency Hotel, Miami. 878–90p.

Awada W, Cardei M. Energy-Efficient Data Gathering in Heterogeneous Wireless Sensor Networks. Proceedings of the IEEE International Conference on Wireless and Mobile Computing, Networking and Communications, 2006. (WiMob'2006); 2006 Jun 19–21; Montreal, Canada. 53–60p.


  • There are currently no refbacks.