Efficient Statistical Clustering Techniques for Optimizing Cluster Size in Wireless Sensor Network

Abstract

Mobility of sensor node in Wireless Sensor Network (WSN) is one of the key advantages of wireless over fixed communication system. In heterogeneous system, generally power consumption is more then homogeneous system. The information or data message passing process must be well architecture to save the limited energy resources of the sensors. Clustering of sensors into different groups, so that sensors communicate information to the other cluster and then the cluster communicate the true information to the processing center which may save energy. So the coordination in distributed sensor network the implementation of clustering is an important technique and clusters of bounded size which is the total number of nodes in a specific cluster, is an important parameter in clustering algorithms which are very much effective in reducing energy consumption by minimizing the neighborhood of a node. Communication cost is also an important parameter for computation in a large area. Clustering techniques is Wireless Sensor Networks (WSNs) compare to random selection techniques is less costly due to the saving of time in journeys, reduction in number of transmissions and receptions at each node, identification, contacts etc. Which are valuable for increasing the overall network life, scalability of WSNs. Clustering sensor nodes is an effective and efficient technique for achieving all the requirement. In this paper, we propose a distributed, randomized clustering techniques to find optimum cluster size and cost to organize the sensors in a wireless sensor network within clusters.