A Multi-objective optimized node deployment algorithm for Wireless Sensor Networks Based on the Improved ABC

Abstract

In the Internet of Things(IoT) for smart fire applications, sensors are deployed at different places and collect multiple types of data during their work time. Since the coverage of a sensor is limited, how to deploy sensors is important to reduce the number of sensors and improve the quality of wireless sensor networks(WSNs) service. The service quality and network lifetime of wireless sensor networks also are dramatically varied across different coverage and node deployment strategies. There are two crucial problems in WSNs, i.e. node deployment with lowest cost, and coverage optimization with maximum coverage rate, need to be solved. In this research, we focus on the problem of coverage optimization and node deployment. Based on the binary coverage probability model, we develop the joint binary coverage probability model and Improved Artificial Bee Colony(IABC) algorithm. The result of simulation shows that our proposed deployment algorithm have a greater coverage ratio in the case of fewer iterations when the volume of deployed sensors is the same compared with the standard ABC algorithm.