A Survey on Mobile Edge Computing for Video Streaming: Opportunities and Challenges
<p>5G communication brings substantial improvements in the quality of service provided to various applications by achieving higher throughput and lower latency. However, interactive multimedia applications (e.g., ultra high definition video conferencing, 3D and multiview video streaming, crowd...
Saved in:
| Main Author: | |
|---|---|
| Other Authors: | , , , , , |
| Published: |
2022
|
| Subjects: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1864513560916262912 |
|---|---|
| author | Muhammad Asif Khan (7367468) |
| author2 | Emna Baccour (16896366) Zina Chkirbene (16869987) Aiman Erbad (14150589) Ridha Hamila (7006457) Mounir Hamdi (14150652) Moncef Gabbouj (2276533) |
| author2_role | author author author author author author |
| author_facet | Muhammad Asif Khan (7367468) Emna Baccour (16896366) Zina Chkirbene (16869987) Aiman Erbad (14150589) Ridha Hamila (7006457) Mounir Hamdi (14150652) Moncef Gabbouj (2276533) |
| author_role | author |
| dc.creator.none.fl_str_mv | Muhammad Asif Khan (7367468) Emna Baccour (16896366) Zina Chkirbene (16869987) Aiman Erbad (14150589) Ridha Hamila (7006457) Mounir Hamdi (14150652) Moncef Gabbouj (2276533) |
| dc.date.none.fl_str_mv | 2022-11-07T00:00:00Z |
| dc.identifier.none.fl_str_mv | 10.1109/access.2022.3220694 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/journal_contribution/A_Survey_on_Mobile_Edge_Computing_for_Video_Streaming_Opportunities_and_Challenges/24056310 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Engineering Communications engineering Information and computing sciences Distributed computing and systems software Machine learning Streaming media Multi-access edge computing Cloud computing 5G mobile communication Deep learning Tutorials Servers Machine learning Live streaming mobile edge computing VoD video Streaming |
| dc.title.none.fl_str_mv | A Survey on Mobile Edge Computing for Video Streaming: Opportunities and Challenges |
| dc.type.none.fl_str_mv | Text Journal contribution info:eu-repo/semantics/publishedVersion text contribution to journal |
| description | <p>5G communication brings substantial improvements in the quality of service provided to various applications by achieving higher throughput and lower latency. However, interactive multimedia applications (e.g., ultra high definition video conferencing, 3D and multiview video streaming, crowd-sourced video streaming, cloud gaming, virtual and augmented reality) are becoming more ambitious with high volume and low latency video streams putting strict demands on the already congested networks. Mobile Edge Computing (MEC) is an emerging paradigm that extends cloud computing capabilities to the edge of the network i.e., at the base station level. To meet the latency requirements and avoid the end-to-end communication with remote cloud data centers, MEC allows to store and process video content (e.g., caching, transcoding, pre-processing) at the base stations. Both video on demand and live video streaming can utilize MEC to improve existing services and develop novel use cases, such as video analytics, and targeted advertisements. MEC is expected to reshape the future of video streaming by providing ultra-reliable and low latency streaming (e.g., in augmented reality, virtual reality, and autonomous vehicles), pervasive computing (e.g., in real-time video analytics), and blockchain-enabled architecture for secure live streaming. This paper presents a comprehensive survey of recent developments in MEC-enabled video streaming bringing unprecedented improvement to enable novel use cases. A detailed review of the state-of-the-art is presented covering novel caching schemes, optimal computation offloading, cooperative caching and offloading and the use of artificial intelligence (i.e., machine learning, deep learning, and reinforcement learning) in MEC-assisted video streaming services.</p><h2>Other Information</h2><p>Published in: IEEE Access<br>License: <a href="https://creativecommons.org/licenses/by/4.0/legalcode" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1109/access.2022.3220694" target="_blank">https://dx.doi.org/10.1109/access.2022.3220694</a></p> |
| eu_rights_str_mv | openAccess |
| id | Manara2_a8eb64b2bcfc43c25f0a806af57ebb32 |
| identifier_str_mv | 10.1109/access.2022.3220694 |
| network_acronym_str | Manara2 |
| network_name_str | Manara2 |
| oai_identifier_str | oai:figshare.com:article/24056310 |
| publishDate | 2022 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | A Survey on Mobile Edge Computing for Video Streaming: Opportunities and ChallengesMuhammad Asif Khan (7367468)Emna Baccour (16896366)Zina Chkirbene (16869987)Aiman Erbad (14150589)Ridha Hamila (7006457)Mounir Hamdi (14150652)Moncef Gabbouj (2276533)EngineeringCommunications engineeringInformation and computing sciencesDistributed computing and systems softwareMachine learningStreaming mediaMulti-access edge computingCloud computing5G mobile communicationDeep learningTutorialsServersMachine learningLive streamingmobile edge computingVoDvideo Streaming<p>5G communication brings substantial improvements in the quality of service provided to various applications by achieving higher throughput and lower latency. However, interactive multimedia applications (e.g., ultra high definition video conferencing, 3D and multiview video streaming, crowd-sourced video streaming, cloud gaming, virtual and augmented reality) are becoming more ambitious with high volume and low latency video streams putting strict demands on the already congested networks. Mobile Edge Computing (MEC) is an emerging paradigm that extends cloud computing capabilities to the edge of the network i.e., at the base station level. To meet the latency requirements and avoid the end-to-end communication with remote cloud data centers, MEC allows to store and process video content (e.g., caching, transcoding, pre-processing) at the base stations. Both video on demand and live video streaming can utilize MEC to improve existing services and develop novel use cases, such as video analytics, and targeted advertisements. MEC is expected to reshape the future of video streaming by providing ultra-reliable and low latency streaming (e.g., in augmented reality, virtual reality, and autonomous vehicles), pervasive computing (e.g., in real-time video analytics), and blockchain-enabled architecture for secure live streaming. This paper presents a comprehensive survey of recent developments in MEC-enabled video streaming bringing unprecedented improvement to enable novel use cases. A detailed review of the state-of-the-art is presented covering novel caching schemes, optimal computation offloading, cooperative caching and offloading and the use of artificial intelligence (i.e., machine learning, deep learning, and reinforcement learning) in MEC-assisted video streaming services.</p><h2>Other Information</h2><p>Published in: IEEE Access<br>License: <a href="https://creativecommons.org/licenses/by/4.0/legalcode" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1109/access.2022.3220694" target="_blank">https://dx.doi.org/10.1109/access.2022.3220694</a></p>2022-11-07T00:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.1109/access.2022.3220694https://figshare.com/articles/journal_contribution/A_Survey_on_Mobile_Edge_Computing_for_Video_Streaming_Opportunities_and_Challenges/24056310CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/240563102022-11-07T00:00:00Z |
| spellingShingle | A Survey on Mobile Edge Computing for Video Streaming: Opportunities and Challenges Muhammad Asif Khan (7367468) Engineering Communications engineering Information and computing sciences Distributed computing and systems software Machine learning Streaming media Multi-access edge computing Cloud computing 5G mobile communication Deep learning Tutorials Servers Machine learning Live streaming mobile edge computing VoD video Streaming |
| status_str | publishedVersion |
| title | A Survey on Mobile Edge Computing for Video Streaming: Opportunities and Challenges |
| title_full | A Survey on Mobile Edge Computing for Video Streaming: Opportunities and Challenges |
| title_fullStr | A Survey on Mobile Edge Computing for Video Streaming: Opportunities and Challenges |
| title_full_unstemmed | A Survey on Mobile Edge Computing for Video Streaming: Opportunities and Challenges |
| title_short | A Survey on Mobile Edge Computing for Video Streaming: Opportunities and Challenges |
| title_sort | A Survey on Mobile Edge Computing for Video Streaming: Opportunities and Challenges |
| topic | Engineering Communications engineering Information and computing sciences Distributed computing and systems software Machine learning Streaming media Multi-access edge computing Cloud computing 5G mobile communication Deep learning Tutorials Servers Machine learning Live streaming mobile edge computing VoD video Streaming |