研究了无线传感器网络在受限移动能力条件下的重新部署问题.针对节点的运动模型为跳跃式移动,提出一种基于遗传算法的重新部署算法.算法以节点的跳跃方向为遗传算法的基因,适用度函数同时考虑了最大化覆盖率和最小化移动总距离.仿真实验表明,在各向同性的感测模型中,此算法优于文献[8]提出的FBSD算法,能实现节点的最优运动规划,并且在有向感测模型中,此算法也能有效提高网络覆盖率.
This paper studies the redeployment scheme for wireless sensor networks when the sensor node is limited mobility and proposes a genetic algorithm based redeployment scheme (GARS) when the motion model for sensor node is a flip. The gene of GARS is the jump direction of sensor node. The fitness function of GARS is taken into account the coverage maximize and the total moved distance minimize. Simulation results show that this scheme is better than the FBSD for isotropic sensing model and it is effective to improve network coverage for directed sensing model. The scheme achieves the optimal motion planning for sensor node in the isotropic sensing model.