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QoE-traffic Optimization Through Collaborative Edge Caching in Adaptive Mobile Video Streaming

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dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en
dc.contributor.author Mehrabidavoodabadi, Abbas
dc.contributor.author Siekkinen, Matti
dc.contributor.author Ylä-Jääski, Antti
dc.date.accessioned 2018-12-21T10:28:06Z
dc.date.available 2018-12-21T10:28:06Z
dc.date.issued 2018-09
dc.identifier.citation Mehrabidavoodabadi , A , Siekkinen , M & Ylä-Jääski , A 2018 , ' QoE-traffic Optimization Through Collaborative Edge Caching in Adaptive Mobile Video Streaming ' , IEEE Access , vol. 6 , pp. 52261-52276 . https://doi.org/10.1109/ACCESS.2018.2870855 en
dc.identifier.issn 2169-3536
dc.identifier.other PURE UUID: 055a8e20-5c5e-44c4-bc22-dff6818125de
dc.identifier.other PURE ITEMURL: https://research.aalto.fi/en/publications/055a8e20-5c5e-44c4-bc22-dff6818125de
dc.identifier.other PURE FILEURL: https://research.aalto.fi/files/30325427/08467314.pdf
dc.identifier.uri https://aaltodoc.aalto.fi/handle/123456789/35607
dc.description.abstract Multi-access edge computing has been proposed as a promising approach to localize the access of mobile clients to the network edges, therefore, reducing significantly the traffic congestion on the backhaul network. Due to time-varying wireless channel condition, the video caching at the mobile edges for dynamic adaptive video streaming over HTTP (DASH) needs to be efficiently handled to alleviate the high bandwidth demand on the backhaul network and improve the quality of experience (QoE) of end users. We investigate the impact of collaborative mobile edge caching on joint QoE and backhaul data traffic by proposing the joint QoE-traffic optimization with collaborative edge caching which introduces the BFTR (backhaul/fronthaul traffic ratio) parameter adjustable by the mobile network operator. We then design a self-tuned bitrate selection algorithm with low complexity to solve the optimization problem and further propose an efficient cache replacement strategy called retention-based collaborative caching. Through simulation-based evaluations, we show a noticeable gain in the percentage of cache miss and specify some threshold for BFTR parameter after which the significant reduction in the data traffic with further improvement in average video bitrate is obtained using collaborative caching. Our findings help mobile edge system developers design an efficient collaborative caching mechanism for 5G networks. en
dc.format.extent 15
dc.format.extent 52261-52276
dc.format.mimetype application/pdf
dc.language.iso en en
dc.relation.ispartofseries IEEE Access en
dc.relation.ispartofseries Volume 6 en
dc.rights openAccess en
dc.title QoE-traffic Optimization Through Collaborative Edge Caching in Adaptive Mobile Video Streaming en
dc.type A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä fi
dc.description.version Peer reviewed en
dc.contributor.department Professorship Ylä-Jääski A.
dc.contributor.department Helsinki Institute for Information Technology (HIIT)
dc.contributor.department Department of Computer Science en
dc.subject.keyword Collaborative caching, Dynamic adaptive video streaming over HTTP (DASH), Fairness, Integer non-linear programming, Multi-access edge computing (MEC), NP-hardness, Quality of experience
dc.subject.keyword Dynamic adaptive video streaming over HTTP (DASH)
dc.subject.keyword Fairnes
dc.subject.keyword Integer non-linear programming
dc.subject.keyword Multi-access edge computing (MEC)
dc.subject.keyword NP-hardnes
dc.subject.keyword Quality of experience
dc.identifier.urn URN:NBN:fi:aalto-201812216615
dc.identifier.doi 10.1109/ACCESS.2018.2870855
dc.type.version publishedVersion

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