CHASE: Charging and Scheduling Scheme for Stochastic Event Capture in Wireless Rechargeable Sensor Networks

被引:69
作者
Dai, Haipeng [1 ]
Ma, Qiufang [1 ]
Wu, Xiaobing [2 ]
Chen, Guihai [1 ]
Yau, David K. Y. [3 ]
Tang, Shaojie [4 ]
Li, Xiang-Yang [5 ]
Tian, Chen [1 ]
机构
[1] Nanjing Univ, State Key Lab Novel Software Technol, Nanjing 210023, Jiangsu, Peoples R China
[2] Univ Canterbury, Wireless Res Ctr, Christchurch 8041, New Zealand
[3] Singapore Univ Technol & Design, Informat Technol Syst & Design Pillar, Singapore 487372, Singapore
[4] Univ Texas Dallas, Naveen Jindal Sch Management, 800 W Campbell Rd, Richardson, TX 75080 USA
[5] Univ Sci & Technol China, Sch Comp Sci & Technol, Hefei 230026, Anhui, Peoples R China
基金
国家重点研发计划; 中国国家自然科学基金; 美国国家科学基金会;
关键词
Mobile charging; scheduling; wireless rechargeable sensor network; stochastic event capture; submodular optimization; approximation algorithm; ENERGY REPLENISHMENT;
D O I
10.1109/TMC.2018.2887381
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this paper, we consider the scenario in which a mobile charger (MC) periodically travels within a sensor network to recharge the sensors wirelessly. We design joint charging and scheduling schemes to maximize the Quality of Monitoring (QoM) for stochastic events, which arrive and depart according to known probability distributions of time. Information is considered captured if it is sensed by at least one sensor. We focus on two closely related research issues, i.e., how to choose the sensors for charging and decide the charging time for each of them, and how to schedule the sensors' activation schedules according to their received energy. We formulate our problem as the maximum QoM CHArging and SchEduling problem (CHASE). We first ignore the MCs travel time and study the resulting relaxed version of the problem, which we call CHASE-R. We show that both CHASE and CHASE-R are NP-hard. For CHASE-R, we prove that it can be formulated as a submodular function maximization problem, which allows two algorithms to achieve $1/6$1/6- and $1/(4 + \epsilon)$1/(4+)-approximation ratios. Then, for CHASE, we propose approximation algorithms to solve it by extending the CHASE-R results. We conduct simulations to validate our algorithm design.
引用
收藏
页码:44 / 59
页数:16
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