Energy-aware QoE and Backhaul Traffic Optimization in Green Edge Adaptive Mobile Video Streaming

dc.contributorAalto-yliopistofi
dc.contributorAalto Universityen
dc.contributor.authorMehrabidavoodabadi, Abbas
dc.contributor.authorSiekkinen, Matti
dc.contributor.authorYlä-Jääski, Antti
dc.contributor.departmentProfessorship Ylä-Jääski A.
dc.contributor.departmentProfessorship Di Francesco Mario
dc.contributor.departmentHelsinki Institute for Information Technology (HIIT)
dc.contributor.departmentDepartment of Computer Scienceen
dc.date.accessioned2020-03-06T15:25:46Z
dc.date.available2020-03-06T15:25:46Z
dc.date.issued2019-05
dc.description.abstractCollaborative caching and processing at the network edges through mobile edge computing (MEC) helps to improve the quality of experience (QoE) of mobile clients and alleviate significant traffic on backhaul network. Due to the challenges posed by current grid powered MEC systems, the integration of time-varying renewable energy into the MEC known as green MEC (GMEC) is a viable emerging solution. In this paper, we investigate the enabling of GMEC on joint optimization of QoE of the mobile clients and backhaul traffic in particularly dynamic adaptive video streaming over HTTP (DASH) scenarios. Due to intractability, we design a greedy-based algorithm with self-tuning parameterization mechanism to solve the formulated problem. Simulation results reveal that GMEC-enabled DASH system indeed helps not only to decrease grid power consumption but also significantly reduce backhaul traffic and improve average video bitrate of the clients. We also find out a threshold on the capacity of energy storage of edge servers after which the average video bitrate and backhaul traffic reaches a stable point. Our results can be used as some guidelines for mobile network operators (MNOs) to judge the effectiveness of GMEC for adaptive video streaming in next generation of mobile networks.en
dc.description.versionPeer revieweden
dc.format.extent12
dc.format.extent1-12
dc.format.mimetypeapplication/pdf
dc.identifier.citationMehrabidavoodabadi , A , Siekkinen , M & Ylä-Jääski , A 2019 , ' Energy-aware QoE and Backhaul Traffic Optimization in Green Edge Adaptive Mobile Video Streaming ' , IEEE Transactions on Green Communications and Networking , pp. 1-12 . https://doi.org/10.1109/TGCN.2019.2918847en
dc.identifier.doi10.1109/TGCN.2019.2918847
dc.identifier.issn2473-2400
dc.identifier.otherPURE UUID: 5de779d6-9cac-4ca6-80a6-9f0e5beaa50c
dc.identifier.otherPURE ITEMURL: https://research.aalto.fi/en/publications/5de779d6-9cac-4ca6-80a6-9f0e5beaa50c
dc.identifier.otherPURE LINK: https://ieeexplore.ieee.org/document/8721527
dc.identifier.otherPURE LINK: http://www.scopus.com/inward/record.url?scp=85066988542&partnerID=8YFLogxK
dc.identifier.otherPURE FILEURL: https://research.aalto.fi/files/34095804/08721527.pdf
dc.identifier.urihttps://aaltodoc.aalto.fi/handle/123456789/43387
dc.identifier.urnURN:NBN:fi:aalto-202003062430
dc.language.isoenen
dc.publisherIEEE
dc.relation.ispartofseriesIEEE Transactions on Green Communications and Networkingen
dc.rightsopenAccessen
dc.subject.keywordBit rate
dc.subject.keywordDASH
dc.subject.keywordFairness
dc.subject.keywordGreedy-based algorithm.
dc.subject.keywordGreen mobile edge computing (GMEC)
dc.subject.keywordGreen products
dc.subject.keywordOptimization
dc.subject.keywordQuality of experience
dc.subject.keywordQuality of experience (QoE)
dc.subject.keywordRenewable energy sources
dc.subject.keywordServers
dc.subject.keywordStreaming media
dc.titleEnergy-aware QoE and Backhaul Traffic Optimization in Green Edge Adaptive Mobile Video Streamingen
dc.typeA1 Alkuperäisartikkeli tieteellisessä aikakauslehdessäfi
dc.type.versionacceptedVersion
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