An efficient coverage and connectivity algorithm based on mobile robots for wireless sensor networks

Connectivity and area coverage are two essential criteria for improving the Quality of Service (QoS) in Wireless Sensor Networks (WSNs). These criteria strongly affect lifetime and performance of the WSNs. Furthermore, connectivity and full area coverage between the sensors ensure that the collected data will be transferred to the base station. In this paper, a new algorithm is proposed to improve the connectivity and full area coverage by utilizing some of the mobile robots to change the initial topology and the position of the sensors. Therefore, a grid-based model is first used to divide the environment into several cells and megacells. In order to change the position of the sensors by mobile robots, the robot path planning algorithm is also introduced in two steps. In the local phase, the Analytic Hierarchy Process (AHP) is utilized to determine the source point and destination point. An improved evolutionary programming algorithm is then used to find the optimal path between the source point and destination point, thereby changing the position of the sensors which cover the environment. In the global phase, the A* algorithm is used to cover the part of the environment which is not covered in the local phase. Finally, we perform comprehensive experiments to validate the performance of the proposed method. Compared with existing approaches, the proposed algorithm demonstrates clear improvements in the connectivity and area coverage, showing the superiority of our model.