Elisavet Grigoriou, Theocharis Saoulidis, L. Atzori, Virginia Pilloni, P. Chatzimisios
{"title":"A QoE monitoring solution for LTE-Advanced Pro networks","authors":"Elisavet Grigoriou, Theocharis Saoulidis, L. Atzori, Virginia Pilloni, P. Chatzimisios","doi":"10.1109/CAMAD.2018.8514946","DOIUrl":null,"url":null,"abstract":"This paper presents a distributed agent-based Quality of Experience (QoE) monitoring solution for Long Term Evolution (LTE)-Advanced Pro networks. The proposed solution relies on an approach that considers the computational complexity and the network load to adjust the frequency of measurements while considering the estimation accuracy. Accordingly, the proposed system allows the Internet Service Provider (ISP) to monitor the network QoE level accurately without overloading the network by considering different Influence Factors (IFs). Some preliminary results are shown in terms of accuracy of estimations and computational complexity in case of video streaming service.","PeriodicalId":173858,"journal":{"name":"2018 IEEE 23rd International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE 23rd International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CAMAD.2018.8514946","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper presents a distributed agent-based Quality of Experience (QoE) monitoring solution for Long Term Evolution (LTE)-Advanced Pro networks. The proposed solution relies on an approach that considers the computational complexity and the network load to adjust the frequency of measurements while considering the estimation accuracy. Accordingly, the proposed system allows the Internet Service Provider (ISP) to monitor the network QoE level accurately without overloading the network by considering different Influence Factors (IFs). Some preliminary results are shown in terms of accuracy of estimations and computational complexity in case of video streaming service.