{"title":"无线可充电传感器网络中多个移动充电器的节能路径设计","authors":"Abhinav Tomar, P. K. Jana","doi":"10.1109/IC3.2017.8284332","DOIUrl":null,"url":null,"abstract":"Mobile charging is an important topic for wireless rechargeable sensor networks (WRSNs) which has been studied extensively over the past few years. With the help of wireless energy transfer (WET), it is now possible to extend lifetime of sensor nodes to a longer period. In WET, wireless charging vehicle (WCV) moves on its designed traveling path in the network and charges sensor nodes by halting at some stopping locations. However, large scale WRSNs demand for multiple WCVs to make mobile charging more feasible. It is to be noted that for designing energy efficient traveling paths, it is desirable to minimize the stopping locations of the WCV which improves charging efficiency in the noticeable amount. Moreover, charging multiple nodes at the same time improves charging performance and thus it is recent trend. Inspired by the above facts, in this paper, we serve the objective of designing energy efficient traveling paths for multiple WCVs with multi-node charging. Our proposed scheme works in two phases. In the first phase, we perform clustering to divide the network region into charging subregions according to available number of WCVs. In the second phase, we apply charging radius based nearest neighbor approach (CR-NN) to find anchor points (i.e., stopping locations) for those WCVs to design traveling paths. The simulation results confirm the effectiveness of our scheme and demonstrate performance gains with respect to several metrics such as charging latency, waiting time, node failure rate, and so on.","PeriodicalId":147099,"journal":{"name":"2017 Tenth International Conference on Contemporary Computing (IC3)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"Designing energy efficient traveling paths for multiple mobile chargers in wireless rechargeable sensor networks\",\"authors\":\"Abhinav Tomar, P. K. Jana\",\"doi\":\"10.1109/IC3.2017.8284332\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Mobile charging is an important topic for wireless rechargeable sensor networks (WRSNs) which has been studied extensively over the past few years. With the help of wireless energy transfer (WET), it is now possible to extend lifetime of sensor nodes to a longer period. In WET, wireless charging vehicle (WCV) moves on its designed traveling path in the network and charges sensor nodes by halting at some stopping locations. However, large scale WRSNs demand for multiple WCVs to make mobile charging more feasible. It is to be noted that for designing energy efficient traveling paths, it is desirable to minimize the stopping locations of the WCV which improves charging efficiency in the noticeable amount. Moreover, charging multiple nodes at the same time improves charging performance and thus it is recent trend. Inspired by the above facts, in this paper, we serve the objective of designing energy efficient traveling paths for multiple WCVs with multi-node charging. Our proposed scheme works in two phases. In the first phase, we perform clustering to divide the network region into charging subregions according to available number of WCVs. In the second phase, we apply charging radius based nearest neighbor approach (CR-NN) to find anchor points (i.e., stopping locations) for those WCVs to design traveling paths. The simulation results confirm the effectiveness of our scheme and demonstrate performance gains with respect to several metrics such as charging latency, waiting time, node failure rate, and so on.\",\"PeriodicalId\":147099,\"journal\":{\"name\":\"2017 Tenth International Conference on Contemporary Computing (IC3)\",\"volume\":\"2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 Tenth International Conference on Contemporary Computing (IC3)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IC3.2017.8284332\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 Tenth International Conference on Contemporary Computing (IC3)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IC3.2017.8284332","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Designing energy efficient traveling paths for multiple mobile chargers in wireless rechargeable sensor networks
Mobile charging is an important topic for wireless rechargeable sensor networks (WRSNs) which has been studied extensively over the past few years. With the help of wireless energy transfer (WET), it is now possible to extend lifetime of sensor nodes to a longer period. In WET, wireless charging vehicle (WCV) moves on its designed traveling path in the network and charges sensor nodes by halting at some stopping locations. However, large scale WRSNs demand for multiple WCVs to make mobile charging more feasible. It is to be noted that for designing energy efficient traveling paths, it is desirable to minimize the stopping locations of the WCV which improves charging efficiency in the noticeable amount. Moreover, charging multiple nodes at the same time improves charging performance and thus it is recent trend. Inspired by the above facts, in this paper, we serve the objective of designing energy efficient traveling paths for multiple WCVs with multi-node charging. Our proposed scheme works in two phases. In the first phase, we perform clustering to divide the network region into charging subregions according to available number of WCVs. In the second phase, we apply charging radius based nearest neighbor approach (CR-NN) to find anchor points (i.e., stopping locations) for those WCVs to design traveling paths. The simulation results confirm the effectiveness of our scheme and demonstrate performance gains with respect to several metrics such as charging latency, waiting time, node failure rate, and so on.