Two Fuzzy Virtual Force Algorithms to Improve Sensor Deployment in Wireless Sensor Networks

Maximizing area coverage is an important issue in the placement of wireless network sensors, the realization of which helps to improve the network monitoring power. In many applications, the sensors are first randomly distributed in the sensing filed and then their placement is modified. The virtual force algorithm (VFA) tries to achieve a more desirable deployment from an initial sensing deployment by considering repulsive and attractive forces between the sensors. In this paper, the combination of Takashi-Sugeno fuzzy system with VFA is used to achieve a better redeployment of the sensors. To adaptively adjust optimal distance value of the sensors, two fuzzy methods are proposed in this paper and their role in improving performance of the virtual force algorithm is analyzed. Comparison of the performance of the proposed methods with the state-of-the-art reveals that intelligent and adaptive adjustment of the optimal distance using a fuzzy system leads to higher final coverage ratio over traditional virtual force algorithm (VFA), improved virtual force algorithm (IVFA), fuzzy redeployment algorithm (FRED), and two metaheuristics GA, and PSO. On the other hand, the proposed VF-based methods require much less time to solve the problem than GA and PSO metaheuristic methods.