Enhancing Lifetime of Wireless Sensor Network with Cluster Technique
|International Journal of Engineering Trends and Technology (IJETT)||
|© 2017 by IJETT Journal|
|Year of Publication : 2017|
|Authors : Ms. Sonal R. Kuche, Prof. R.H. Borhade
|DOI : 10.14445/22315381/IJETT-V47P208|
Ms. Sonal R. Kuche, Prof. R.H. Borhade "Enhancing Lifetime of Wireless Sensor Network with Cluster Technique", International Journal of Engineering Trends and Technology (IJETT), V47(1),56-59 May 2017. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group
Wireless Sensor Networks (WSNs) are made up of hundreds or thousands of sensor nodes which are distributed in a particular area to monitor environmental conditions like temperature, sound, pressure etc. and cooperatively pass their data to the base station. WSN is gradually developing technology. There are large scale applications in WSN like environmental monitoring, battlefield awareness, temperature sensing etc. therefore, there is need of increasing network lifetime in WSN as changing sensors frequently is not possible practically all the time. Assuming these drawbacks the proposed loadbalanced clustering algorithm for WSNs can overcome previous clustering algorithms. In the previous techniques, the clustering of nodes is not balanced and this can make the network energy unbalanced. On the basis of their distance and location, making it essentially different from the Proposed Location Based Clustering Algorithm (LBC) can perform better than exiting LEACH and Rescue Phase to form a cluster. In LBC algorithm the location of each and every present node in the network are calculated with respect to X, Y- coordinates. This can help to avoid random selection of nodes in clusters. It improves the balancing of the network and energy of network can be saved. Proposed Centre Point Detection Clustering Algorithm (CPDC) determines the center of the cluster and nearest node to that point with high energy selected as Cluster Head (CH).
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Wireless sensor networks, energy efficiency, clustering, Cluster Heads, Network lifetime.