B. Srbinovski, M. Magno, B. O’flynn, V. Pakrashi, E. Popovici
{"title":"Energy aware adaptive sampling algorithm for energy harvesting wireless sensor networks","authors":"B. Srbinovski, M. Magno, B. O’flynn, V. Pakrashi, E. Popovici","doi":"10.1109/SAS.2015.7133582","DOIUrl":null,"url":null,"abstract":"Wireless sensor nodes have a limited power budget, while they are often expected to be functional for a very long period of time once deployed in the field. Therefore, the minimization of energy consumption and energy harvesting technology are key tools for maximization of network lifetime and achieving self sustainability in Wireless Sensor Networks (WSN). This paper proposes an energy aware Adaptive Sampling Algorithm (ASA) for WSN with power hungry sensors and harvesting capabilities. An existing ASA developed for wireless sensor networks with power hungry sensors is optimized and enhanced to adapt the sampling frequency according to the available energy of the node. The proposed algorithm is evaluated using an in-field testbed with a sensor node which incorporates a wind harvester and a power hungry wind speed/direction sensor. Simulation and comparison between an existing ASA and the energy aware ASA in terms of energy durability are carried out using the measured wind energy and the wind speed over a period of a month. The simulation results have shown that using ASA in combination with energy aware function on the nodes can drastically increase the lifetime of a WSN node. Moreover, the energy aware ASA in conjunction with the node energy harvesting capability can lead towards a perpetual operation of WSN and significantly outperform state-of-the-art ASA.","PeriodicalId":384041,"journal":{"name":"2015 IEEE Sensors Applications Symposium (SAS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"40","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE Sensors Applications Symposium (SAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SAS.2015.7133582","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 40
Abstract
Wireless sensor nodes have a limited power budget, while they are often expected to be functional for a very long period of time once deployed in the field. Therefore, the minimization of energy consumption and energy harvesting technology are key tools for maximization of network lifetime and achieving self sustainability in Wireless Sensor Networks (WSN). This paper proposes an energy aware Adaptive Sampling Algorithm (ASA) for WSN with power hungry sensors and harvesting capabilities. An existing ASA developed for wireless sensor networks with power hungry sensors is optimized and enhanced to adapt the sampling frequency according to the available energy of the node. The proposed algorithm is evaluated using an in-field testbed with a sensor node which incorporates a wind harvester and a power hungry wind speed/direction sensor. Simulation and comparison between an existing ASA and the energy aware ASA in terms of energy durability are carried out using the measured wind energy and the wind speed over a period of a month. The simulation results have shown that using ASA in combination with energy aware function on the nodes can drastically increase the lifetime of a WSN node. Moreover, the energy aware ASA in conjunction with the node energy harvesting capability can lead towards a perpetual operation of WSN and significantly outperform state-of-the-art ASA.