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المؤلفBilal, Kashif
المؤلفErbad, Aiman
المؤلفHefeeda, Mohamed
تاريخ الإتاحة2021-01-27T11:06:53Z
تاريخ النشر2017
اسم المنشورIEEE Access
المصدرScopus
الرقم المعياري الدولي للكتاب21693536
معرّف المصادر الموحدhttp://dx.doi.org/10.1109/ACCESS.2017.2720189
معرّف المصادر الموحدhttp://hdl.handle.net/10576/17474
الملخصAdvances 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).
راعي المشروعThis work was supported by NPRP through the Qatar National Research Fund (a member of Qatar Foundation) under Grant 8-519-1-108.
اللغةen
الناشرInstitute of Electrical and Electronics Engineers Inc.
الموضوعCloud
Crowdsourcing
Multi-view video
QoE
Resource allocation
العنوانCrowdsourced multi-view live video streaming using cloud computing
النوعArticle
الصفحات12635-12647
رقم المجلد5


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