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AuthorBilal, Kashif
AuthorErbad, Aiman
AuthorHefeeda, Mohamed
Available date2021-01-27T11:06:53Z
Publication Date2017
Publication NameIEEE Access
ResourceScopus
ISSN21693536
URIhttp://dx.doi.org/10.1109/ACCESS.2017.2720189
URIhttp://hdl.handle.net/10576/17474
AbstractAdvances and commoditization of media generation devices enable capturing and sharing of any special event by multiple attendees. We propose a novel system to collect individual video streams (views) captured for the same event by multiple attendees, and combine them into multi-view videos, where viewers can watch the event from various angles, taking crowdsourced media streaming to a new immersive level. The proposed system is called Cloud-based Multi-View Crowdsourced Streaming (CMVCS), and it delivers multiple views of an event to viewers at the best possible video representation based on each viewer's available bandwidth. The CMVCS is a complex system having many research challenges. In this paper, we focus on resource allocation of the CMVCS system. The objective of the study is to maximize the overall viewer satisfaction by allocating available resources to transcode views in an optimal set of representations, subject to computational and bandwidth constraints. We choose the video representation set to maximize QoE using Mixed Integer Programming. Moreover, we propose a Fairness-Based Representation Selection (FBRS) heuristic algorithm to solve the resource allocation problem efficiently. We compare our results with optimal and Top-N strategies. The simulation results demonstrate that FBRS generates near optimal results and outperforms the state-of-the-art Top-N policy, which is used by a large-scale system (Twitch).
SponsorThis work was supported by NPRP through the Qatar National Research Fund (a member of Qatar Foundation) under Grant 8-519-1-108.
Languageen
PublisherInstitute of Electrical and Electronics Engineers Inc.
SubjectCloud
Crowdsourcing
Multi-view video
QoE
Resource allocation
TitleCrowdsourced multi-view live video streaming using cloud computing
TypeArticle
Pagination12635-12647
Volume Number5


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