Markov-chain based optimization algorithm for efficient routing in wireless sensor networks

Wireless sensor networks (WSN) have been framed by sensor nodes randomly dispersed in a wireless environment for performing a specific task. Every sensor node is utilized the battery energy. There are several parameters of the sensor node for communication, storage and sensing of data within restricted capacity. An effective algorithm is needed to increase the lifetime of the sensor nodes. The data compression related algorithms are implemented to diminish the data transmission by efficient way to extend the lifetime of the network. The identification of adjacent nodes according to the localization and energy optimization could be achieved by segregating the nodes into clusters at the central region. The energy consumption is maintained with optimal algorithm within the sensor nodes. The Markov-chain model is proposed to identify the adjacent nodes with improved energy efficiency. The optimized routing path is identified through the sink node for delivering the data packets with adjacent sensor nodes. The proposed methodology is measured in performance metrics of energy consumption, delay, residual energy. The simulation results shows better performance compared to the other methods. © 2021, Bharati Vidyapeeth's Institute of Computer Applications and Management.