Abstract

Large number of small sensor nodes exists in WSN’s for sensing and collecting information from the environment. In today’s time, these sensor nodes were applied in under water, military area, health care, earthquake sensing and in dedicated areas with recent technologies. Sensor nodes have limited life time and have supplementary network life. Network lifecycle depends on many factors such as connectivity, residual energy, topology types, single hop, multi hop, distance from base station, distance to cluster heads and much more. Among the various solutions given, clustering is considered to be good solution and optimal cluster head selection leads to efficient energy consumption. This paper proposes fuzzy based multi-attributes clustering that balances load among sensor nodes and also gives energy efficient clustering. Here we have used some attributes such as delay, residual energy, distance to CH, standard deviation to average network lifetime and standard deviation to residual energy. Results and experimental analysis validates that the proposed methods outperforms other compared algorithms.

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