Wireless Sensor Network coverage optimization based on Yin-Yang pigeon-inspired optimization algorithm for Internet of Things

Jianghao Yin, Na Deng, Jindan Zhang

Abstract: As an important technology of Internet of Things (IoT), wireless sensor network (WSN) has the problem of low coverage caused by uneven nodes distribution. Aiming at the problem, a WSN coverage optimization method based on the Yin–Yang pigeon-inspired optimization algorithm (Yin–YangPIO) is proposed. Firstly, the good point set is introduced into initialization phase which makes pigeon population more evenly distributed in the solution space; then, Yin–Yang-pair optimization algorithm (YYPO) and pigeon-inspired optimization algorithm (PIO) are combined, and different strategies are used in the map and compass operator and the landmark operator to improve the optimization ability; later on, the opposition-based learning is added to PIO to expand the search range; finally, several functions are selected to prove the optimization ability of the Yin–YangPIO. Through three sets of WSN coverage optimization experiments with different parameters, the effectiveness of the proposed method in WSN coverage optimization is demonstrated.