...
首页> 外文期刊>IEEE transactions on mobile computing >Concurrently Wireless Charging Sensor Networks with Efficient Scheduling
【24h】

Concurrently Wireless Charging Sensor Networks with Efficient Scheduling

机译:高效调度的同时无线充电传感器网络

获取原文
获取原文并翻译 | 示例
           

摘要

Wireless charging technology is considered as a promising solution to address the energy limitation problem for wireless sensor networks (WSNs). In scenarios where the deployed chargers are static, we generally require a number of chargers to work simultaneously. However, due to the radio interference among different wireless chargers, scheduling these chargers is generally necessary. This scheduling problem is challenging since each charger's charging utility cannot be calculated independently due to the nonlinear superposition charging effect caused by radio interference. In this paper, based on the concurrent charging model, we formulate the concurrent charging scheduling problem (CCSP) with the objective of quickly fully charging all the sensor nodes. After proving the NP-hardness of CCSP, we propose two efficient greedy algorithms, and give the approximation ratio of one of them. Both the two greedy algorithms’ performances are very close to that of a well-designed genetic algorithm (GA) which performs almost as well as a brute force algorithm at small network and charger scale. However, the running time of the two greedy algorithms is far lower than that of the GA. We conduct extensive simulations and specially implemented a testbed for wireless chargers. The results verified the good performance of the proposed algorithms.
机译:无线充电技术被认为是解决无线传感器网络(WSN)的能量限制问题的有前途的解决方案。在部署的充电器是静态的情况下,我们通常需要多个充电器同时工作。但是,由于不同无线充电器之间的无线电干扰,通常需要安排这些充电器。由于无线电干扰导致的非线性叠加充电效应,每个充电器的充电效用无法独立计算,因此该调度问题具有挑战性。在本文中,基于并发充电模型,我们制定了并发充电调度问题(CCSP),以快速为所有传感器节点完全充电。在证明了CCSP的NP硬度之后,我们提出了两种有效的贪心算法,并给出其中一种的近似率。两种贪婪算法的性能都与精心设计的遗传算法(GA)的性能非常接近,遗传算法在小型网络和充电器规模下的性能几乎与蛮力算法相当。但是,两种贪婪算法的运行时间远低于GA。我们进行了广泛的仿真,并专门为无线充电器安装了一个试验台。结果证明了所提算法的良好性能。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号