Efficient Scheduling of Multiple Mobile Chargers for Wireless Sensor Networks

In this paper, we study the deployment of multiple mobile charging vehicles to charge sensors in a large-scale wireless sensor network for a given monitoring period so that none of the sensors will run out of energy, where sensors can be charged by the charging vehicles with wireless energy transfer...

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Bibliographic Details
Published in:IEEE transactions on vehicular technology Vol. 65; no. 9; pp. 7670 - 7683
Main Authors: Xu, Wenzheng, Liang, Weifa, Lin, Xiaola, Mao, Guoqiang
Format: Journal Article
Language:English
Published: New York IEEE 01.09.2016
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Algorithms
Approximation algorithms
combinatorial optimization problems
Energy consumption
mobile chargers
Mobile communication
Monitoring
periodic charging cycles
Production scheduling
rechargeable sensor networks
Sensors
Vehicles
wireless energy transfer
Wireless sensor networks
ISSN:0018-9545, 1939-9359
Online Access:Get full text
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Summary:In this paper, we study the deployment of multiple mobile charging vehicles to charge sensors in a large-scale wireless sensor network for a given monitoring period so that none of the sensors will run out of energy, where sensors can be charged by the charging vehicles with wireless energy transfer. To minimize the network operational cost, we first formulate a charging scheduling problem of dispatching multiple mobile charging vehicles to collaboratively charge sensors such that the sum of travelling distance (referred to as the service cost) of these vehicles for this monitoring period is minimized, subject to that none of the sensors will run out of energy. Due to NP-hardness of the problem, we then propose a novel approximation algorithm with a guaranteed approximation ratio, assuming that the energy consumption rate of each sensor does not change for the given monitoring period. Otherwise, we devise a heuristic algorithm through modifications to the approximation algorithm. We finally evaluate the performance of the proposed algorithms via experimental simulations. Simulation results show that the proposed algorithms are very promising, which can reduce the service cost by up to 20% in comparison with the service costs delivered by existing ones.
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ISSN:0018-9545
1939-9359
DOI:10.1109/TVT.2015.2496971