{"title":"基于 AHP-MCDM 的 WRSN 自适应移动充电器调度方案","authors":"Kondwani Makanda;Ammar Hawbani;Xingfu Wang;Abdulbary Naji;Ahmed Al-Dubai;Liang Zhao;Saeed Hamood Alsamhi","doi":"10.1109/TSUSC.2024.3391316","DOIUrl":null,"url":null,"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.","PeriodicalId":13268,"journal":{"name":"IEEE Transactions on Sustainable Computing","volume":"10 1","pages":"57-69"},"PeriodicalIF":3.0000,"publicationDate":"2024-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Adaptive Mobile Chargers Scheduling Scheme Based on AHP-MCDM for WRSN\",\"authors\":\"Kondwani Makanda;Ammar Hawbani;Xingfu Wang;Abdulbary Naji;Ahmed Al-Dubai;Liang Zhao;Saeed Hamood Alsamhi\",\"doi\":\"10.1109/TSUSC.2024.3391316\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":13268,\"journal\":{\"name\":\"IEEE Transactions on Sustainable Computing\",\"volume\":\"10 1\",\"pages\":\"57-69\"},\"PeriodicalIF\":3.0000,\"publicationDate\":\"2024-04-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Sustainable Computing\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10505737/\",\"RegionNum\":3,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, HARDWARE & ARCHITECTURE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Sustainable Computing","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10505737/","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, HARDWARE & ARCHITECTURE","Score":null,"Total":0}
Adaptive Mobile Chargers Scheduling Scheme Based on AHP-MCDM for WRSN
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.