An Efficient Charger Planning Mechanism of WRSN Using Simulated Annealing Algorithm

The limited energy of sensor can be regarded as an optimization problem aimed at finding some useful deployment strategies for a set of chargers, but it typically might spend a lot of computation costs. In order to provide a good solution for reducing a large number of chargers caused by all the sensor nodes need to be covered, add the motor to some particular chargers is an alternative solution. That is why some recent studies attempted to develop the movable charger based algorithms to enhance transmission range. However, most movable charger-based algorithms are the greedy or rule-based algorithms, they will easy fall into local optimum at early iteration and consequently the end results will far away to global optimum. That is why it still has rooms for improvement. This paper will present a simulated annealing-based algorithm to improve the deployment result of wireless sensor network. The simulation results show that the proposed method can reduce the number of chargers significantly for full coverage.