{"title":"Lightweight online power monitoring and control for mobile applications","authors":"Bo Wang, Xinghui Zhao, David Chiu","doi":"10.1109/PADSW.2014.7097845","DOIUrl":null,"url":null,"abstract":"Limited battery power has long been a challenge for mobile applications. As a result, the work in power monitoring and management has attracted great interests. In this paper, we propose a model to estimate power consumption of mobile applications at run-time, based on application-specific per-action power profiling. In addition, we have developed on-line optimization techniques which help maximize users' experience while conserving power. Our power model is lightweight and flexible, in that it can be used by any mobile applications as a plugin, and it can support user-defined optimization mechanisms. This approach has been evaluated using a case study, a mobile application for field studies, and the experimental results show that our model accurately captures power consumption of the application, and the model can be used to optimize the power consumption based on users' needs.","PeriodicalId":421740,"journal":{"name":"2014 20th IEEE International Conference on Parallel and Distributed Systems (ICPADS)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 20th IEEE International Conference on Parallel and Distributed Systems (ICPADS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PADSW.2014.7097845","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Limited battery power has long been a challenge for mobile applications. As a result, the work in power monitoring and management has attracted great interests. In this paper, we propose a model to estimate power consumption of mobile applications at run-time, based on application-specific per-action power profiling. In addition, we have developed on-line optimization techniques which help maximize users' experience while conserving power. Our power model is lightweight and flexible, in that it can be used by any mobile applications as a plugin, and it can support user-defined optimization mechanisms. This approach has been evaluated using a case study, a mobile application for field studies, and the experimental results show that our model accurately captures power consumption of the application, and the model can be used to optimize the power consumption based on users' needs.
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