Energy Efficient Markov Prediction Based Opportunistic Routing (Eempor) For Wireless Sensor Networks

Abstract

Wireless Sensor Network (WSN) is the foundation of recent popular technologies such as Internet of Things (IoT), Cloud computing, etc., Energy efficient routing is one of the main concerns in WSN, due to the very scarce battery life in sensor nodes. opportunistic Routing(OR) provides energy efficient routing because of packet broadcast process, when compared to traditional routing in WSN. opportunistic Routing initially broadcasts the packets to the neighbor nodes and select one node among several neighbor nodes as a packet forwarder. Next hop selection process continues until the packet reached to destination. In this work, Energy Efficient Markov Prediction based opportunistic Routing (EEMPOR) is proposed to achieve better network lifetime. Based on the predicted metrics like number of transactions in the node and residual energy of the node, EEMPOR selects Potential Forwarder Set (PFS), prioritizes the nodes and forwards the packet. It utilizes Markov prediction based method to predict the number of transactions of each neighbor node of the source node for select and prioritize the potential forwarder set. Nodes with less number of transactions and high residual energy is selected and prioritized to provide energy efficient routing. EEMPOR scheme provides better energy efficiency among the nodes and increases network lifetime when compared to existing opportunistic routing protocols like EXOR, EEOR, EAOR and ENS-OR.