Game Theory and Coverage Optimization Based Multihop Routing Protocol for Network Lifetime in Wireless Sensor Networks

Wireless sensor networks (WSNs) are self-organizing monitoring networks with a large number of randomly deployed micro sensor nodes to collect various physical information so as to realize tasks such as intelligent perception, efficient control and decision-making. However, WSNs nodes are powered by batteries, so they will run out of energy after a certain time. This energy limitation will greatly constrain the network performance like network lifetime and energy efficiency. In this study, for the purpose of prolonging network lifetime, we proposed a multi-hop routing protocol based on game theory and coverage optimization (MRP-GTCO). Briefly, in the stage of setup, two innovational strategies including clustering game with penalty function and cluster head coverage set were designed to realize the uniformity of cluster head distribution and improve the rationality of cluster head election. In the data transmission stage, we firstly derived the applicable conditions theorem of inter-cluster multi-hop routing. Based on this, a novel multi-hop path selection algorithm related to residual energy and node degree was proposed to provide an energy-efficient data transmission path. The simulation results showed that MRP-GTCO protocol can effectively reduce the network energy consumption and extend the network lifetime 159.22%, 50.76% and 16.46% compared with LGCA, RLEACH and ECAGT protocols.

I. Introduction

Wireless sensor networks have brought a new revolution to information sensing [1] because of its advantages such as convenient deployment, strong anti-destructive ability and low cost, and have been widely applied in intelligent agriculture [2], environmental monitoring [3] and military monitoring [4], etc. It is a self-organizing network composed of low-power micro sensor nodes, which can perform wireless communication, data sensing, processing and storage for IoT applications. However, sensor nodes are usually powered by batteries with limited capacity [5] and deployed in harsh natural environments [6], which makes it difficult to charge, let alone replace batteries. Once the node dies because of energy exhaustion, it will bring irreparable disasters to the whole network such as incomplete monitoring data and great changes of network topology will lead to decision delay or error. Generally, network lifetime is reflected by the round of dead nodes and the most popular definitions are the rounds of the first dead node (FDN), half dead nodes (HDN) and last dead node (LDN) [7], [8]. Network energy consumption determines the death rate of nodes, and then affects the network lifetime. Therefore, it is of great significance to reduce the energy consumption of nodes and prolong the network lifetime.