A Novel Light Reflection-Random Walk for Smart Sensors Relocation

This paper presents a new algorithm for relocating sensors in a Wireless Sensor and Robots Network (WSRN) using a mobile robot. The goal is to repair coverage holes using redundant sensors that are caused by an initial random deployment. The holes are repaired without prior knowledge of their positions or that of the redundant sensors. The existing solutions mainly focus either on how to optimally repair holes by determining to where relocate redundant sensors, or how to build a repair path with assumption that the positions of holes and redundant sensors are known. In both scenarios, the literature lacked the optimization of the robot’s path for its initial exploration to identify both the holes and redundant sensors. Our proposed solution introduces an efficient robot trajectory that utilizes stochastic paths that adhere to the principles of light reflection. This trajectory serves the dual purpose of identifying redundant sensors and detecting as well as repairing coverage holes. We achieve this by incorporating the law of large numbers into the light reflection principal, enabling the robot to move randomly while adhering to the pathways of light reflection to efficiently relocate the redundant sensors. This approach results in a highly efficient and effective sensor relocation process. The effectiveness of the proposed solution is assessed across multiple parameters, including relocation time, the length of the relocation path, the robot average moves, and the total energy consumption required to cover holes with varying carrying capacity, dimensions of region of interest, coverage ratio and exit angles of reflection. Through a series of extensive simulations, we provide compelling evidence that our proposed solution distinctly surpasses the existing state-of-the-art approaches. This notable advantage becomes evident in multiple aspects: from reduced relocation time and shorter relocation path length to minimized total energy consumption. These combined enhancements underscore the effectiveness of our solution in tackling the challenge of sensor relocation.