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Advancement in MEMS technology, networking and embedded microprocessors have led to the development of a new generation of a Wireless Sensor Network (WSN) that can operate in unattended and harsh environment depending upon application. WSN consist of large number of power-conscious devices called sensor nodes that detect and observe any physical phenomenon and can be used in a wide range of applications. Underlying topology plays an important role in the performance of the Wireless Sensor Network. Depending upon the application, deployment is performed either deterministically or randomly. WSN suffers from a lot of issues that includes energy conservation, scalability, latency, computational resources and communication capabilities. Energy efficiency is critical issue in Wireless Sensor Networks as nodes are equipped with limited power supply and nodes that bypass most of the traffic deplete their energy faster that leads to decreased network lifetime. Incorporating clustering in the network improves scalability, increase energy efficiency and reduces redundancy. A new clustering approach for WSN has been discussed that includes load balancing and improves energy efficiency by precise selection of CH's. Analysis and simulation results demonstrate the effectiveness of the proposed approach.

Energy Efficiency Optimization in Wireless Sensor Network Using Proposed Load Balancing Approach