Abstract
In this paper, a robot assisted maintenance strategy (RAMS) which aims to balance the coverage rate and maintenance cost was proposed. In this strategy, we firstly analyzed the coverage and energy consumption model. And then a network health indicator which considering the coverage rate and residual energy in each node was proposed. Mathematically, the network health indicator is a cost function. So the network maintenance was formulated into cost optimization problem. Since the selection of candidate nodes which to be redeployed is very complexity, so the particle swarm optimal algorithm was employed to reduce the computation complexity. Finally, the robot was employed to repair the networks. Simulation results show that in comparison with random, uniform, and Delaney algorithm, the proposed RAMS can achieve relatively high coverage rate with much longer maintenance period.
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