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Joint Transcoding Task Assignment and Association Control for Fog-assisted Crowdsourced Live Streaming

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journal contribution
posted on 09.09.2019 by Xingchi Liu, Mahsa Derakhshani, Sangarapillai Lambotharan
The rapid development of content delivery networks and cloud computing has facilitated crowdsourced live-streaming platforms (CLSP) that enable people to broadcast live videos which can be watched online by a growing number of viewers. However, in order to ensure reliable viewer experience, it is important that the viewers should be provided with multiple standard video versions. To achieve this, we propose a joint fog-assisted transcoding and viewer association technique which can outsource the transcoding load to a fog device pool and determine the fog device with which each viewer will be associated, to watch desired videos. The resulting non-convex integer programming has been solved using a computationally attractive complementary geometric programming (CGP). The performance of the proposed algorithm closely matches that of the globally optimum solution obtained by an exhaustive search. Furthermore, the trace-driven simulations demonstrate that our proposed algorithm is able to provide adaptive bit rate (ABR) services.

Funding

Engineering and Physical Sciences Research Council (EPSRC) under Grant EP/R006385/1

History

School

  • Mechanical, Electrical and Manufacturing Engineering

Published in

IEEE Communications Letters

Volume

23

Issue

11

Pages

2036 - 2040

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Version

AM (Accepted Manuscript)

Rights holder

© IEEE

Publisher statement

© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Publication date

2019-08-08

Copyright date

2019

ISSN

1089-7798

eISSN

2373-7891

Language

en

Depositor

Mr Mike Liu

Exports