An Energy Efficient Approach for Clustering in WSN using Fuzzy Logic

Lifetime augmentation has always been an interesting subject of vital significance in wireless sensor networks. Excess extent of energy is dissipated during data transmission to the base station (sink) from normal sensor nodes. Clustering is an efficacious way of augmenting the life span by optimizing (reducing) the energy dissipation of WSNs. Many numbers of researchers have employed fuzzy logic based solution for election of cluster- head in the earlier past. In our proposed scheme two strong parameters; energy and centrality have been considered for cluster head decision. In this work we assumed both the parameters simultaneously to elect cluster head which makes this approach energy efficient and more feasible. Simulation results are contrasted with the former approaches of cluster-head election. Simulation results exhibits that the proposed scheme minimizes energy consumption and thereby enhances life span of wireless sensor network by a significant amount.

[1]  Fatos Xhafa,et al.  Performance evaluation of two fuzzy-based cluster head selection systems for wireless sensor networks , 2008, Mob. Inf. Syst..

[2]  Qilian Liang,et al.  Clusterhead election for mobile ad hoc wireless network , 2003, 14th IEEE Proceedings on Personal, Indoor and Mobile Radio Communications, 2003. PIMRC 2003..

[3]  Seon-Ho Park,et al.  CHEF: Cluster Head Election mechanism using Fuzzy logic in Wireless Sensor Networks , 2008, 2008 10th International Conference on Advanced Communication Technology.

[4]  Nasrin Abazari Torghabeh,et al.  Cluster head selection using a two-level fuzzy logic in wireless sensor networks , 2010, 2010 2nd International Conference on Computer Engineering and Technology.

[5]  A. Manjeshwar,et al.  TEEN: a routing protocol for enhanced efficiency in wireless sensor networks , 2001, Proceedings 15th International Parallel and Distributed Processing Symposium. IPDPS 2001.

[6]  Sang-Ho Lee,et al.  A Lifetime Extended Routing Protocol Based on Data Threshold in Wireless Sensor Networks , 2010, 2010 10th IEEE International Conference on Computer and Information Technology.

[7]  Fatos Xhafa,et al.  An Intelligent Fuzzy-Based Cluster Head Selection System for WSNs and Its Performance Evaluation for D3N Parameter , 2010, 2010 International Conference on Broadband, Wireless Computing, Communication and Applications.

[8]  A.T. Haghighat,et al.  Energy Conservation Strategy in Cluster-Based Wireless Sensor Networks , 2008, 2008 International Conference on Advanced Computer Theory and Engineering.

[9]  Rong Ding,et al.  Soft Threshold Based Cluster-Head Selection Algorithm for Wireless Sensor Networks , 2009, 2009 Third International Conference on Sensor Technologies and Applications.

[10]  Xiao Fu,et al.  A Reliable and Efficient Clustering Algorithm for Wireless Sensor Networks Using Fuzzy Petri Nets , 2010, 2010 6th International Conference on Wireless Communications Networking and Mobile Computing (WiCOM).

[11]  Indranil Gupta,et al.  Cluster-head election using fuzzy logic for wireless sensor networks , 2005, 3rd Annual Communication Networks and Services Research Conference (CNSR'05).

[12]  Fatos Xhafa,et al.  An Intelligent Fuzzy-Based Cluster Head Selection System for Wireless Sensor Networks and Its Performance Evaluation , 2010, 2010 13th International Conference on Network-Based Information Systems.