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A Co-Operative Based Inter-Cluster Communication to Optimize Network Life Time in WSN


  • Visvesvaraya Technological University Research Scholar, Bangalore, Karnataka –560091, India
  • Bangalore Institute of Technology, KR Road, V V Puram, Bengaluru, Karnataka –560004, India


Wireless Sensor Networks (WSNs) consist of a large number of low-cost, low-power and intelligent sensor nodes and one or more sinks or base stations. Those nodes are small in size and can perform many important functions, including event sensing, information processing, and data communication. WSNs can be employed in wide military applications and civilian scenarios. Sensing the signal and transmission of those signal require lots of energy which reduces the life time of sensor node, which affects the overall network life time. So for saving the energy a better mechanism is required which can improve the overall network life time. Many research works are going in this field for improving the network life time. For Energy saving a large network is divided in to some cluster from one hop to another hop, where a hop contains a Cluster Head (CH) which is chosen by the Base Station (BS) and a Cluster Member (CM), which can communicate with CH. Clusters, can save the energy due to less distance communication factor. CH communicates with BS. LEACH (Low Energy Adaptive Clustering Hierarchy) is very popular clustering mechanism, but it also has some draw backs. So a better mechanism for energy saving and to improve the life time of network is needed. Here author proposed a new idea called Mutual relay node clustering protocol. Here author analyses the network life time in terms of number of rounds and overall energy consumption and compare with currently existing Leach protocol.


Inter-Cluster, Intra-Cluster, Mutual, Rounds.

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  • Cheng CT, Tse CK, Lau FCM. An energy-aware scheduling scheme for WSN, in IEEE Transactions on Vehicular Technology. 2010 Sep; 59(7):3427–44.
  • Vaidya R, Dandekar DR. Comparison of SPAN and LEACH protocol for topology control in WSN, Signal Processing Image Processing and Pattern Recognition (ICSIPR), 2013 International Conference on, Coimbatore; 2013. p.20–3.
  • Jianyin L.Simulation of improved routing protocols LEACH of WSN, Computer Science and Education (ICCSE), 7th International Conference on, Melbourne, VIC; 2012.p.662–6.
  • Choe J, Kim K. EADD: EADD for WSN, parallel and distributed processing with applications, ISPA ‘08. International Symposium on, Sydney, NSW; 2008. p.779–83.
  • Sharma V, Saini DS. Performance investigation of advanced multi-hop and single-hop energy efficient LEACH protocol with heterogeneous nodes in WSN, Advances in Computing and Communication Engineering (ICACCE), Second International Conference on, Dehradun; 2015. p.192–7
  • Zeb A, Islam AKMM, Komaki S, Baharun S. Multi-nodes joining for dynamic cluster-based WSN, Informatics, Electronics and Vision (ICIEV), International Conference on, Dhaka; 2014. p.1–6.
  • Sharma V, Saini DS. Performance investigation of advanced multi-hop and single-hop energy efficient LEACH protocol with heterogeneous nodes in WSNs, Advances in Computing and Communication Engineering (ICACCE), 2015 Second International Conference on, Dehradun; 2015. p.192–7.
  • Zuniga M, Krishnamachari B. Analyzing the transitional region in low power wireless links, sensor and ad hoc communications and networks. IEEE SECOND. First Annual IEEE Communications Society Conference on; 2004.p.517–26
  • Paulraj A, Nabar R, Gore D. Introduction to space-time wireless communications, cambridge, U.K.: Cambridge University; 2003.
  • Cui S, Goldsmith AJ, Bahai A. Energy-efficiency of MIMO and cooperative MIMO techniques in sensor networks, IEEE Journal on Selected Areas in Communications. 2003 Aug; 22(6):1089–98.
  • Laneman JN, Wornell GW. Distributed space-time codedprotocols for exploiting cooperative diversity in wireless networks, IEEE Transactions on Information Theory. 2003 Oct; 49(10):2415–25.
  • Sirkeci-Mergen B, Scaglione A. “Randomized distributed space-time coding for cooperative communication in self organized networks,” in Proceedings of IEEE Signal Processing Advances in Wireless Communications; 2005 Jun. p.500–4.
  • Proakis JG. Digital communications. New York: McGrawHill; 2000.
  • Cardei M, Thai MT, Li Y, Wu W. Energy-Efficient Target Coveragenin WSNs. IEEE INFOCOM; 2005.
  • Boyinbode O, Le H, Mbogho A, Takizawa M, Poliah R. A survey on clustering algorithms for WSNs. In Proceedings of 2010 13th International Conference on Network-Based Information Systems, Takayama, Japan;2010 Sep 14–16.p. 358–64.
  • Latiff NMA, Tsemenidis CC, Sheriff BS. Energy-aware clustering for WSNs using particle swarm optimization, The 18th Annual IEEE International Symposium on Personal.Indoor and Mobile Radio Communications, Athens, Greece; 2007 Sep 3–7. p.1–5.


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