Processing of Deployment Using an Adaptive Self-Spreading Algorithm Based on Electrostatic Field for Mobile Sensor

Abstract

The deployment of mobile sensor networks is a hotspot issue. This paper is dedicated to proposing a distributed, adaptive, and scalable mobile sensor network algorithm based on the theory in electrostatic field. In the algorithm, the obstacles and nodes in the deployment region were regarded as the charged particles, which were driven by the Coulomb Force exerted by the other particles and obstacles, and eventually all the nodes were distributed throughout the entire network while repelled by the obstacles and other nodes simultaneously. Based on the classical virtual potential field algorithm, the boundary conditions, the static equilibrium conditions and the controllable coverage rate were expanded in the present algorithm, which are also the primary innovation points and contributions of this paper. The efficiency of the proposed algorithm was evaluated by performing simulations under four frequently-used scenarios, namely, deployment under normal conditions, deployment with obstacles, re-deployment due to unpredicted node failures, and deployment with regions of interest. Moreover, the performance of the algorithm was assessed using coverage and uniformity as the criteria. The simulation results indicate that the algorithm runs well under all these four frequently-used scenarios. In a completely unknown deployment area, the designated goal can also be achieved using the proposed algorithm owing to its adaptivity.