{"title":"Balancing Energy Harvesting and Transmission Scheduling in Aggregation Convergecast","authors":"Jesse Huard, I. Nikolaidis","doi":"10.1145/3242102.3242132","DOIUrl":null,"url":null,"abstract":"We study tradeoffs between aggregation convergecast and energy harvesting in wireless sensor networks. Existing aggregation convergecast algorithms do not capture the volatile nature of energy reserves of energy harvesting nodes. We therefore propose, and evaluate, new scheduling schemes to address this gap. We also introduce metrics to capture the impact of the inevitable energy depletion on the quantity of aggregated data received at a sink node. Specifically, we consider node behaviors where the inability to perform prompt communication due to energy depletion results in a reduction of the sampling rate (including for aggregated data) and, if it persists, loss of data. The performance evaluation is based on heat flow data collected from an apartment building in the Canadian North. The collected heat flow data are used to approximate the energy harvesting output of thermoelectric harvesters.","PeriodicalId":241359,"journal":{"name":"Proceedings of the 21st ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 21st ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3242102.3242132","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
We study tradeoffs between aggregation convergecast and energy harvesting in wireless sensor networks. Existing aggregation convergecast algorithms do not capture the volatile nature of energy reserves of energy harvesting nodes. We therefore propose, and evaluate, new scheduling schemes to address this gap. We also introduce metrics to capture the impact of the inevitable energy depletion on the quantity of aggregated data received at a sink node. Specifically, we consider node behaviors where the inability to perform prompt communication due to energy depletion results in a reduction of the sampling rate (including for aggregated data) and, if it persists, loss of data. The performance evaluation is based on heat flow data collected from an apartment building in the Canadian North. The collected heat flow data are used to approximate the energy harvesting output of thermoelectric harvesters.