{"title":"Joint Wireless Charging and Sensor Activity Management in Wireless Rechargeable Sensor Networks","authors":"Yuanxiunan Gao, Cong Wang, Yuanyuan Yang","doi":"10.1109/ICPP.2015.88","DOIUrl":null,"url":null,"abstract":"Recent studies show that the novel wireless charging technology can extend the lifetime of Wireless Sensor Networks (WSNs) towards perpetual operations. Recharging Vehicles (RVs) can be applied in WSNs to recharge sensors conveniently via wireless charging devices. Most of existing work focused only on energy replenishment whereas ignored sensor activity management. In this paper, we propose a new framework that can jointly schedule sensor activity and recharging to save the traveling energy of RVs. First, we propose two schemes to manage sensor activity: balanced clustering and distributed sensor activation schemes. We further introduce a new metric so that the energy demand in each cluster can be managed. Then we formulate the recharging problem into a Traveling Salesman Problem with Profits, which is NP-hard. For the recharging route schedule, we first study the case of a single RV by coordinating sensor activity and energy replenishment, and then extend it to multiple RVs using two different schemes. The first scheme focuses on reducing traveling distance of RVs by confining their moving scopes and the second one improves the overall system performance by giving RVs a global view over the entire network. Finally, we validate the correctness and evaluate the performance of the sensor activity management schemes along with the recharging algorithms by extensive simulations. Our results indicate that significant reduction on system cost can be achieved. The sensor activity management schemes can save traveling energy of RVs by 16% while maintaining a reliable detection on targets. Compared with a simple greedy algorithm, the first and the second recharging schemes can save 41% and 13% traveling distance of RVs, and reduce nonfunctional nodes by 23% and 52%, respectively.","PeriodicalId":423007,"journal":{"name":"2015 44th International Conference on Parallel Processing","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 44th International Conference on Parallel Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPP.2015.88","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 14
Abstract
Recent studies show that the novel wireless charging technology can extend the lifetime of Wireless Sensor Networks (WSNs) towards perpetual operations. Recharging Vehicles (RVs) can be applied in WSNs to recharge sensors conveniently via wireless charging devices. Most of existing work focused only on energy replenishment whereas ignored sensor activity management. In this paper, we propose a new framework that can jointly schedule sensor activity and recharging to save the traveling energy of RVs. First, we propose two schemes to manage sensor activity: balanced clustering and distributed sensor activation schemes. We further introduce a new metric so that the energy demand in each cluster can be managed. Then we formulate the recharging problem into a Traveling Salesman Problem with Profits, which is NP-hard. For the recharging route schedule, we first study the case of a single RV by coordinating sensor activity and energy replenishment, and then extend it to multiple RVs using two different schemes. The first scheme focuses on reducing traveling distance of RVs by confining their moving scopes and the second one improves the overall system performance by giving RVs a global view over the entire network. Finally, we validate the correctness and evaluate the performance of the sensor activity management schemes along with the recharging algorithms by extensive simulations. Our results indicate that significant reduction on system cost can be achieved. The sensor activity management schemes can save traveling energy of RVs by 16% while maintaining a reliable detection on targets. Compared with a simple greedy algorithm, the first and the second recharging schemes can save 41% and 13% traveling distance of RVs, and reduce nonfunctional nodes by 23% and 52%, respectively.