A multi-attribute decision making approach for on-demand charging scheduling in wireless rechargeable sensor networks
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A multi-attribute decision making approach for on-demand charging scheduling in wireless rechargeable sensor networks Abhinav Tomar1
· Prasanta K. Jana1
Received: 21 July 2020 / Accepted: 18 November 2020 © Springer-Verlag GmbH Austria, part of Springer Nature 2020
Abstract Mobile charging in wireless rechargeable sensor networks is a well-referenced research problem. Numerous studies have been carried out to determine an efficient charging schedule for mobile charger (MC). However, the problem still remains challenging as it requires a wise scheduling decision based on the evaluation of various attributes that impact on network performance. In this regard, multi-attribute decision making (MADM) may be an effective approach which has shown great potential to solve complex decision making problems by coordinating multiple attributes, but has not been explored by existing mobile charging schemes till date. To this end, this paper proposes a novel charging scheme which integrates two popular MADM methods to determine charging schedule by evaluating various network attributes, namely residual energy, distance to MC, energy consumption rate, and neighborhood energy weightage. We take into account both MC’s limited energy and nodes’ uneven energy consumption rates in order to formulate feasibility conditions for scheduling the nodes effectively for further improvement of charging performance. Extensive simulations are performed to illustrate the effectiveness of the proposed scheme. When compared with relevant state-of-the-art methods, the results signify that the proposed scheme boosts charging performance in terms of various performance metrics. Keywords WRSN · Mobile charger · Charging schedule · MADM · AHP · TOPSIS Mathematics Subject Classification 68M18 · 68M20 · 90B50 · 62Cxx
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Abhinav Tomar [email protected] Department of Computer Science and Engineering, Indian Institute of Technology (ISM) Dhanbad, Dhanbad 826004, Jharkhand, India
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A. Tomar, P. K. Jana
1 Introduction The limited energy capacity of sensor nodes is by far one of the most alarming issues confronted by the real-world applications of wireless sensor networks (WSNs) [1–4]. Among numerous solutions proposed so far, powering sensor nodes through wireless energy transfer (WET) technology has been acknowledged as a very promising solution and encourages the application of wireless rechargeable sensor networks (WRSNs) [5]. The WET provides sustainable and controllable energy supplement to the nodes and so addresses the issues of energy renewal and lifetime extension in the WRSNs. For wireless charging, one or more mobile chargers (MCs) equipped with resonant coils are adopted which can approach sensors in close proximity [6]. This guarantees that operation time of the WRSNs can be extended for infinitely long [7,8]. However, one major challenge is to design an efficient charging schedule for the MC to meet the dynamic charging requirements of the nodes. Therefore, the charging scheduling problem is a prominent issue worth attentio
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