Adaptive Mobile Chargers Scheduling Scheme Based on AHP-MCDM for WRSN

IF 3.9 3区 计算机科学 Q2 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE IEEE Transactions on Sustainable Computing Pub Date : 2024-04-19 DOI:10.1109/TSUSC.2024.3391316
Kondwani Makanda;Ammar Hawbani;Xingfu Wang;Abdulbary Naji;Ahmed Al-Dubai;Liang Zhao;Saeed Hamood Alsamhi
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Abstract

Wireless Sensor Networks (WSNs) are used to sense and monitor physical conditions in various services and applications. However, there are a number of challenges in deploying WSNs, especially those pertaining to energy replenishment. Using the current solutions, when a significant number of sensors need to replenish their energy, this would be costly in terms of time, efforts and resources. Thus, this paper aims to solve this problem by efficiently deploying wireless power transfer technologies and scheduling Mobile Charging Vehicles (MCVs) in WRSN. The proposed method deploys multi-criteria decision-making (i.e., Analytical Hierarchy Process (AHP)) to schedule the charging tasks. To the best of our knowledge, this paper is the first to depend solely on AHP in MCVs scheduling. The paper demonstrates the validity of the proposed method by illustrating that the matrices that are created are within the accepted values of consistency ratio. In addition, the paper proposes a method of partitioning the values of our criteria to avoid the problem of different criteria having different measurement units. Unlike existing works, the paper aims to schedule an MCV for charging based on both the distance and residual energy of the sensor. The proposed method exhibits superiority in terms of the average remaining energy available in the system, having the shortest queue length, shorter MCV response time, shorter charging duration, and shorter queue waiting time against the state-of-the-art methods. Our study paves the way for next generation efficient charging and MCV scheduling.
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基于 AHP-MCDM 的 WRSN 自适应移动充电器调度方案
无线传感器网络(wsn)用于感知和监测各种服务和应用中的物理状况。然而,部署无线传感器网络存在许多挑战,特别是那些与能量补充有关的挑战。使用目前的解决方案,当大量传感器需要补充能量时,这将在时间、精力和资源方面付出高昂的代价。因此,本文旨在通过高效部署无线电力传输技术和调度移动充电车(mcv)来解决这一问题。该方法采用多准则决策(即层次分析法)对收费任务进行调度。据我们所知,本文是第一个完全依赖AHP的mcv调度方法。通过说明所创建的矩阵在一致性比的可接受值范围内,证明了所提出方法的有效性。此外,本文还提出了一种分割准则值的方法,以避免不同准则具有不同的测量单位的问题。与现有的工作不同,本文的目标是根据传感器的距离和剩余能量来安排MCV充电。该方法在系统平均剩余能量方面具有优势,与现有方法相比,具有最短的队列长度,更短的MCV响应时间,更短的充电持续时间和更短的队列等待时间。我们的研究为下一代高效充电和MCV调度铺平了道路。
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来源期刊
IEEE Transactions on Sustainable Computing
IEEE Transactions on Sustainable Computing Mathematics-Control and Optimization
CiteScore
7.70
自引率
2.60%
发文量
54
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