谷歌Chrome浏览器插件
订阅小程序
在清言上使用

An Approximation for Routing Planning, Mobile Charging, and Energy Sharing for Sensing Devices

Zifeng Liu, Dejun Kong,Yucen Gao,Haipeng Dai,Xiaofeng Gao,Tian He

2023 IEEE International Conference on Web Services (ICWS)(2023)

引用 0|浏览14
暂无评分
摘要
Wireless Charging Vehicles (WCVs) have been widely explored as a means of enabling continuous operation of sensors that are powered by batteries. However, the energy consumption of WCVs can be inefficient, leading to insufficient energy supply for sensors that are located in challenging-to-access areas. Consequently, there is a need to design an effective charging and energy sharing scheme for sensors to improve the quality of service in this setup. This paper focuses on the Joint optimization of Mobile charging and Energy sharing of sensors (JOIN-ME) problem, which is known to be NP-hard. To address this challenge, we first transform JOIN-ME into a submodular maximization problem with general constraints. Subsequently, we propose the Routing planning, Mobile charging, and Energy sharing for Sensing devices (RMES) algorithm, which has an approximation ratio of 1/8(1-1/e). Finally, we conduct experiments to showcase the superior performance of RMES compared to existing baselines, under varying scales and constraints. Our work on the design of an efficient charging and energy sharing scheme for sensors can significantly improve the reliability and longevity of wireless sensor networks, enabling the deployment of these networks in critical applications such as environmental monitoring, crowd sensing, and security surveillance.
更多
查看译文
关键词
Mobile Charging,Energy Sharing,Charging Route Planning,Sensing Devices,Approximation Algorithm
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要