A Genetic Algorithm Based Strategy for Mobile Sinks in Wireless Sensor Networks

摘要

Sink mobility has been developed to extend network lifetime in wireless sensor network. One problem of sink mobility is next-round position selection, in which networks aims at periodic data-gathering applications, each period of data gathering is referred to as a round and how to select optimal position for next round is challenging. Next-round position selection problem has not been widely discussed. In this paper, we have proposed a novel moving strategy which is based on genetic algorithm (GA) to handle next-round position selection problem. In detail, each individual of GA corresponds to a position in network area and the fitness function is designed to reflect degree of balance of energy-consumption. Using the GA based strategy, the sink selects the optimal moving position for next round to achieve balance of energy consumption among sensor nodes thereby prolongs network lifetime. We compare the GA based strategy with traditional strategies for mobile sinks by simulations. The results show that the GA based strategy extends network lifetime notably.