| 摘要: |
| 得益于无线能量传输技术的突破，体域网节点可以捕获射频能量源的无线电波能量进行充电，从而持续不间断地工作.对能量源数量和位置进行合理规划可以有效提高节点的能量捕获功率，降低部署成本.现有工作大多考虑节点静止情况下的能量源部署问题或通过概率统计模型转化为节点静止的情况，因此具有明显的局限性.考虑体域网应用背景下，携带可穿戴节点的用户具有特定停留-移动模式，基于该模型归纳了满足节点能量不中断概率要求的能量源优化布置问题，并将该问题的限制条件分解，转化为一个等价问题.分别基于贪婪算法和分治-粒子群算法设计了能量源优化布置算法.通过多组仿真实验，在不同参数下将两种算法与现有路径覆盖算法的性能进行了对比.实现结果表明，在满足节点能量不中断概率要求的前提下，分治-粒子群算法相比贪婪算法和路径覆盖算法更能节省能量源部署成本. |
| 关键词: 停留-移动模型 能量源布置 射频能量捕获 移动体域网 |
| DOI： |
| 分类号: |
| 基金项目:国家自然科学基金（61772472，61432015，61472367，61672465）；浙江省自然科学基金（LY17F020020，LY15F020027） |
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| RF-Based Charger Placement for Wireless-Powered Mobile Body Area Networks |
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LI Yan-Jun, CHEN Yu-Zhe, CHI Kai-Kai, TIAN Xian-Zhong, ZHU Yi-Hua
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School of Computer Science and Technology, Zhejiang University of Technology, Hangzhou 310023, China
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| Abstract: |
| With the breakthrough in the technology of wireless power transmission, wireless-powered body sensor nodes are able to harvest radio frequency (RF) energy from RF-based chargers and thus operate continuously. Rational planning of the number and positions of the chargers is an effective way to improve the charging efficiency and save deployment budget. Previous studies on RF-based charger placement mainly consider the scenario that nodes are static, or convert to the static scenario using probability statistical model. With the background of mobile body area network, this paper considers the situation that users carrying sensor nodes have specific sojourn-move behavior patterns. Based on this behavior model, charger placement optimization problem is formulated with the constraint of node's non-outage probability. Both greedy and divide-and-conquer based particle swarm optimization (D&C-PSO) approaches are proposed to solve the problem. Finally, performances of the two proposed algorithms are evaluated and compared with existing path provisioning approach through various simulations. Simulation results show that the divide-and-conquer based particle swarm optimization outperforms both greedy and path provisioning approaches in the charger placement cost while it guarantees the node's non-outage probability. |
| Key words: sojourn-move model charger placement RF energy harvesting mobile body area network |
