O. Mokrenko, Maria Isabel Vergara Gallego, W. Lombardi, S. Lesecq, C. Albea-Sánchez
{"title":"WSN power management with battery capacity estimation","authors":"O. Mokrenko, Maria Isabel Vergara Gallego, W. Lombardi, S. Lesecq, C. Albea-Sánchez","doi":"10.1109/NEWCAS.2015.7182060","DOIUrl":null,"url":null,"abstract":"Wireless sensor nodes are now cheap and reliable enough to be deployed in different environments. However, their limited energy capacity limits their lifespan. In this paper, a Management strategy at network-level of a set of nodes is implemented, taking into account an estimation of the remaining energy in each sensor node. The control formulation is based on Model Predictive Control with constraints and binary optimization variables, leading to a Mixed Integer Quadratic Programming problem. The estimation of the remaining energy in batteries must be simple enough to be implemented in low-cost, low-power, low-computational-capability sensor nodes.","PeriodicalId":404655,"journal":{"name":"2015 IEEE 13th International New Circuits and Systems Conference (NEWCAS)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE 13th International New Circuits and Systems Conference (NEWCAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NEWCAS.2015.7182060","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
Wireless sensor nodes are now cheap and reliable enough to be deployed in different environments. However, their limited energy capacity limits their lifespan. In this paper, a Management strategy at network-level of a set of nodes is implemented, taking into account an estimation of the remaining energy in each sensor node. The control formulation is based on Model Predictive Control with constraints and binary optimization variables, leading to a Mixed Integer Quadratic Programming problem. The estimation of the remaining energy in batteries must be simple enough to be implemented in low-cost, low-power, low-computational-capability sensor nodes.