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Author:

Meng, Xiangguang (Meng, Xiangguang.) | Guo, Jianxiong (Guo, Jianxiong.) | Ding, Xingjian (Ding, Xingjian.) | Zhang, Xiujuan (Zhang, Xiujuan.)

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Abstract:

Replenishing energy to wireless sensor networks is always a crucial problem as the energy capacity of sensor nodes is very limited. Scheduling mobile chargers to charge sensor nodes has been widely studied due to its efficiency and flexibility. However, most existing works focus on maximizing the charging utility or charging efficiency, which ignores the task performing functions of sensor nodes. In this paper, we study the problem of scheduling a mobile charger to maximize the task utility achieved by sensor nodes. We consider two different scenarios where sensor nodes are deployed on a line road and a ring road, respectively. We prove the NP-Hardness of our problems and design two approximation algorithms with guaranteed performance. We also investigate how to jointly schedule two mobile chargers in the line road scenario, and design a corresponding approximation algorithm to address the problem. We prove the approximation ratio of our algorithms through theoretical analysis, and conduct extensive simulations to validate the performance of our algorithms. Simulation results show that our algorithms always outperform the baselines, which demonstrates the effectiveness of our algorithms. © 2022 Elsevier B.V.

Keyword:

Sensor nodes Scheduling Roads and streets Approximation algorithms

Author Community:

  • [ 1 ] [Meng, Xiangguang]School of Distance and Continuing Education, Communication University of China, Beijing; 100024, China
  • [ 2 ] [Meng, Xiangguang]School of Information, Beijing Forestry University, Beijing; 100083, China
  • [ 3 ] [Guo, Jianxiong]Advanced Institute of Natural Sciences, Beijing Normal University, Zhuhai; 519087, China
  • [ 4 ] [Ding, Xingjian]Faculty of Information Technology, Beijing University of Technology, Beijing; 100124, China
  • [ 5 ] [Zhang, Xiujuan]School of Information, Renmin University of China, Beijing; 100872, China
  • [ 6 ] [Zhang, Xiujuan]School of Computer Science, Qufu Normal University, Rizhao; 276826, China

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Source :

Theoretical Computer Science

ISSN: 0304-3975

Year: 2022

Volume: 928

Page: 82-93

1 . 1

JCR@2022

1 . 1 0 0

JCR@2022

ESI Discipline: COMPUTER SCIENCE;

ESI HC Threshold:46

JCR Journal Grade:4

CAS Journal Grade:4

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 7

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