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Machine Learning at the Mobile Edge : The Case of Dynamic Adaptive Streaming over HTTP (DASH)
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- Behravesh, Rasaoul (författare)
- Fondazione Bruno Kessler, Italy,Fdn Bruno Kessler, Digital Socity Ctr, SNESE Unit, Trento, Italy.;Univ Bologna, Dept Elect Elect & Informat Engn, I-40126 Bologna, Italy.
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- Rao, Akhila (författare)
- RISE,Datavetenskap,Res Inst Sweden AB, Connected Intelligence, S-16440 Stockholm, Sweden.
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- Perez-Ramirez, Daniel F. (författare)
- RISE,Datavetenskap,Res Inst Sweden AB, Connected Intelligence, S-16440 Stockholm, Sweden.
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- Harutyunyan, Davit (författare)
- Robert Bosch GmbH, Corp Res, D-70465 Gerlingen, Germany.
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- Riggio, Roberto (författare)
- Politecnica delle Marche, Italy,Univ Politecn Marche, Informat Engn Dept, I-60121 Ancona, Italy.
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- Boman, Magnus (författare)
- KTH,Programvaruteknik och datorsystem, SCS
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Fondazione Bruno Kessler, Italy Fdn Bruno Kessler, Digital Socity Ctr, SNESE Unit, Trento, Italy;Univ Bologna, Dept Elect Elect & Informat Engn, I-40126 Bologna, Italy. (creator_code:org_t)
- Institute of Electrical and Electronics Engineers Inc. 2022
- 2022
- Engelska.
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Ingår i: IEEE Transactions on Network and Service Management. - : Institute of Electrical and Electronics Engineers Inc.. - 1932-4537. ; 19:4, s. 4779-4793
- Relaterad länk:
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https://urn.kb.se/re...
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https://doi.org/10.1...
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https://urn.kb.se/re...
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Abstract
Ämnesord
Stäng
- Dynamic Adaptive Streaming over HTTP (DASH) is a standard for delivering video in segments and adapting each segment’s bitrate (quality), to adjust to changing and limited network bandwidth. We study segment prefetching, informed by machine learning predictions of bitrates of client segment requests, implemented at the network edge. We formulate this client segment request prediction problem as a supervised learning problem of predicting the bitrate of a client’s next segment request, in order to prefetch it at the mobile edge, with the objective of jointly improving the video streaming experience for the users and network bandwidth utilization for the service provider. The results of extensive evaluations showed a segment request prediction accuracy of close to 90% and reduced video segment access delay with a cache hit ratio of 58%, and reduced transport network load by lowering the backhaul link utilization by 60.91%.
Ämnesord
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datorteknik (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Engineering (hsv//eng)
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Sciences (hsv//eng)
Nyckelord
- 5G
- Bandwidth
- Bit rate
- Caching
- DASH
- Machine Learning
- Measurement
- MEC
- Prediction algorithms
- Prefetching
- Servers
- Streaming media
- Video Streaming
- 5G mobile communication systems
- Forecasting
- HTTP
- Mobile edge computing
- Bit rates
- Dynamic Adaptive Streaming over HTTP
- Machine-learning
- Streaming medium
- Video-streaming
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
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