{"title":"Traffic Estimation for Dynamic Capacity Adaptation in Load Adaptive Network Operation Regimes","authors":"A. Ahrens, C. Lange, C. Benavente-Peces","doi":"10.5220/0005932800990104","DOIUrl":null,"url":null,"abstract":"The energy demand of telecommunication equipment and networks has been identified to be significant. In the \n \ninformation society such networks are vital for societal and economic welfare as well as for the peopleâs private \n \nlives. Therefore an improved energy efficiency of telecommunication networks is essential in the context of \n \nsustainability and climate change. Load-adaptive regimes are a promising option for energy-efficient and \n \nsustainable network operation. As the capacity is adapted to temporally fluctuating traffic demands, they \n \nrequire a robust traffic demand estimation. As a potential solution to mitigate this problem, a method for \n \nreliable traffic demand forecasting on relevant time scales using Wiener filtering is presented. The results \n \nshow that the capacity dimensioning based on the proposed Wiener filtering traffic estimation method leads to \n \nreliable outcomes enabling sustainable and efficient network operation.","PeriodicalId":298357,"journal":{"name":"International Conference on Pervasive and Embedded Computing and Communication Systems","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Pervasive and Embedded Computing and Communication Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5220/0005932800990104","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
The energy demand of telecommunication equipment and networks has been identified to be significant. In the
information society such networks are vital for societal and economic welfare as well as for the peopleâs private
lives. Therefore an improved energy efficiency of telecommunication networks is essential in the context of
sustainability and climate change. Load-adaptive regimes are a promising option for energy-efficient and
sustainable network operation. As the capacity is adapted to temporally fluctuating traffic demands, they
require a robust traffic demand estimation. As a potential solution to mitigate this problem, a method for
reliable traffic demand forecasting on relevant time scales using Wiener filtering is presented. The results
show that the capacity dimensioning based on the proposed Wiener filtering traffic estimation method leads to
reliable outcomes enabling sustainable and efficient network operation.