International Journal of Soft Computing

Year: 2015
Volume: 10
Issue: 2
Page No. 169 - 174

Energy Efficient Cluster Based Transmission Protocol in Wireless Sensor Networks

Authors : E. Mariappan and B. Paramasivan

Abstract: Wireless Sensor Networks (WSNs) consists of distributed autonomous sensors without central base controller to monitor environmental conditions. Scalability, energy efficiency, network lifetime and load balancing are important issues in sensor network applications. Clustering and energy efficient routing is an effective technique for achieving above cited issues. This study proposed an Energy Efficient Cluster based Transmission Protocol (ECTP) which uses the report sensing mechanism through the sink with the help of link aware sensory network to improve network lifetime and energy saving. The report generation can be done with the subsidiary analysis of efficient scaling and dynamic Clustering algorithm. In this study, Broadcast Incremental Power algorithm (BIP) is used to find the minimum power tree from the source node for achieving energy efficient broadcasting in the network. It is a sensible methodology to predict the energy efficient and modulated routing path. The transmitted packet delivery ratio and latency outrages the sequential analysis of the cluster path and route navigations. The qualification of cluster head election predominate the route discovery mechanism. The ECTP protocol determines the optimal path for determining the cluster head and route navigation with best path approaches. The ECTP significantly outperforms the energy aware cluster and LEACH. This approach also compared of various network parameters is done with various clustering protocols. Simulation results have shown that ECTP give better performance than other protocols like LEACH and EC in terms of prolong network lifetime and energy efficiency.

How to cite this article:

E. Mariappan and B. Paramasivan, 2015. Energy Efficient Cluster Based Transmission Protocol in Wireless Sensor Networks. International Journal of Soft Computing, 10: 169-174.

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