Enhancing Energy Level and Network Lifetime for Asynchronous Duty Cycled WSN with Expectation-Maximization Algorithm

Abstract

Generally in Asynchronous duty cycled Wireless Sensor Network (WSN), the energy level and the network life time will be considered as the most important factors which decides the performance of the network. If the delays in the network are more, then accordingly the energy level and the life time will gets degraded. To compensate the delays between the senders and to decrease the variety of duplicate packets here we are proposing an algorithm named as Expectation-Maximization (EM) Algorithm. The algorithm consists of two stages. First and foremost, each node characterizes an applicant region using a standard mathematical form of four corners. Bundles generated by the node will be channeled through any route in the area. As applicants, local nodes may be chosen. The texture of the activist group determines the size of the Candidate Zone (CZ). Second, rising stars within the Candidate Zone (CZ) are favored due to the Opportunistic Routing (OR) metric, which is a replication of four mixtures: directional conveyance, transmission distance circulation, opposite distance dissemination, and energy appropriation. The Expectation-Maximization Algorithm is used in this cycle. Resource management in wireless sensor networks is one of the fundamental issues that should be considered to work on the life expectancy of sensor organizations. In general, execution assessment and recreation of enormous scope situation shows that our conventional method performs better with OR-EM. The objective of the proposed work is done by calculating most significant energy dispersed by a node in the path aside fixing the sink node to the destination node. The experimental results prove that our proposed method using Expectation-Maximization algorithm has improved in terms of energy level by 13.5% while comparing without Expectation-Maximization algorithm.