{"title":"Green network technologies and the art of trading-off","authors":"R. Bolla, R. Bruschi, A. Carrega, F. Davoli","doi":"10.1109/INFCOMW.2011.5928827","DOIUrl":null,"url":null,"abstract":"In this contribution, we focus on energy-aware devices able to reduce their energy requirements by adapting their performance. We propose an analytical model to accurately represent the impact of green network technologies (i.e., low power idle and adaptive rate) on network- and energy-aware performance indexes. The model has been validated with experimental results, performed by using energy-aware software routers and real-world traffic traces. The achieved results demonstrate how the proposed model can effectively represent energy- and network-aware performance indexes. Moreover, also an optimization procedure based on the model has been proposed and experimentally evaluated. The procedure aims at dynamically adapting the energy-aware device configuration to minimize energy consumption, while coping with incoming traffic volumes and meeting network performance constraints.","PeriodicalId":402219,"journal":{"name":"2011 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"34","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INFCOMW.2011.5928827","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 34
Abstract
In this contribution, we focus on energy-aware devices able to reduce their energy requirements by adapting their performance. We propose an analytical model to accurately represent the impact of green network technologies (i.e., low power idle and adaptive rate) on network- and energy-aware performance indexes. The model has been validated with experimental results, performed by using energy-aware software routers and real-world traffic traces. The achieved results demonstrate how the proposed model can effectively represent energy- and network-aware performance indexes. Moreover, also an optimization procedure based on the model has been proposed and experimentally evaluated. The procedure aims at dynamically adapting the energy-aware device configuration to minimize energy consumption, while coping with incoming traffic volumes and meeting network performance constraints.