Grid based cluster head selection mechanism for wireless sensor network

Wireless sensor network (WSN) consists of hundred to thousands sensor nodes to gathered the information from physical environment. Different clustering based algorithms have been proposed to improve network lifetime and energy efficiency. Practically it is not feasible to recharge the battery of sensor nodes when they are sensing the data. In such situation energy is crucial resource and it should be improved for life span of WSN. Cluster head (CH) has an important role in hierarchical energy efficient routing protocols because it receives data from nodes and sends towards base station (BS) or sink node. This paper presents a grid based cluster head selection (GBCHS) mechanism by dividing the network field into MXN uniform size partitions that aims to minimize the energy dissipation of sensor nodes and enhancing network lifetime. Simulation experiments have been performed in network simulator (NS2) that show our proposed GBCHS approach outperformed than standard clustering hierarchy LEACH protocol.

[1]  Wendi Heinzelman,et al.  Energy-efficient communication protocol for wireless microsensor networks , 2000, Proceedings of the 33rd Annual Hawaii International Conference on System Sciences.

[2]  Anantha P. Chandrakasan,et al.  An application-specific protocol architecture for wireless microsensor networks , 2002, IEEE Trans. Wirel. Commun..

[3]  Cauligi S. Raghavendra,et al.  PEGASIS: Power-efficient gathering in sensor information systems , 2002, Proceedings, IEEE Aerospace Conference.

[4]  Catherine Rosenberg,et al.  Design guidelines for wireless sensor networks: communication, clustering and aggregation , 2004, Ad Hoc Networks.

[5]  Ossama Younis,et al.  HEED: a hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks , 2004, IEEE Transactions on Mobile Computing.

[6]  Wei Zhang,et al.  GROUP: A Grid-Clustering Routing Protocol for Wireless Sensor Networks. , 2006, 2006 International Conference on Wireless Communications, Networking and Mobile Computing.

[7]  Wu Jie,et al.  EECS:an energy-efficient clustering scheme in wireless sensor networks , 2007 .

[8]  Choon-Sung Nam,et al.  The Adaptive Cluster Head Selection in Wireless Sensor Networks , 2008, 2008 IEEE International Workshop on Semantic Computing and Applications.

[9]  Teerawat Issariyakul,et al.  Introduction to Network Simulator NS2 , 2008 .

[10]  Elizabeth Chang,et al.  Wireless Sensor Networks: A Survey , 2009, 2009 International Conference on Advanced Information Networking and Applications Workshops.

[11]  Aries Kusdaryono,et al.  CBERP: cluster based energy efficient routing protocol for wireless sensor network , 2010, ICN 2010.

[12]  Hamed Yousefi,et al.  An efficient distributed cluster-head election technique for load balancing in wireless sensor networks , 2010, 2010 Sixth International Conference on Intelligent Sensors, Sensor Networks and Information Processing.

[13]  Chalermpol Charnsripinyo,et al.  An Energy-aware Clustering Technique for Wireless Sensor Networks , 2010 .

[14]  Nileshsingh V. Thakur,et al.  Load Balancing Algorithms in Wireless Sensor Network : A Survey , 2012 .

[15]  G. Radhamani,et al.  Clustering schemes for mobile adhoc networks: A review , 2012, 2012 International Conference on Computer Communication and Informatics.

[16]  Hee Yong Youn,et al.  A Novel Cluster Head Selection Method based on K-Means Algorithm for Energy Efficient Wireless Sensor Network , 2013, 2013 27th International Conference on Advanced Information Networking and Applications Workshops.

[17]  Jin Shan,et al.  Research on an Improved Wireless Sensor Networks Clustering Protocol , 2013 .

[18]  Wei Lei,et al.  A New Routing Protocol for Efficient and Secure Wireless Sensor Networks , 2013 .

[19]  Yao Xiao,et al.  A Clustering Protocol for Wireless Sensor Networks Based on Energy Potential Field , 2013, TheScientificWorldJournal.