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High Performance On-Demand Video Tra...
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University of Louisiana at Lafayette.
High Performance On-Demand Video Transcoding Using Cloud Services.
紀錄類型:
書目-語言資料,手稿 : Monograph/item
正題名/作者:
High Performance On-Demand Video Transcoding Using Cloud Services./
作者:
Li, Xiangbo.
面頁冊數:
1 online resource (147 pages)
附註:
Source: Dissertation Abstracts International, Volume: 78-12(E), Section: B.
標題:
Computer engineering. -
電子資源:
click for full text (PQDT)
ISBN:
9780355113099
High Performance On-Demand Video Transcoding Using Cloud Services.
Li, Xiangbo.
High Performance On-Demand Video Transcoding Using Cloud Services.
- 1 online resource (147 pages)
Source: Dissertation Abstracts International, Volume: 78-12(E), Section: B.
Thesis (Ph.D.)--University of Louisiana at Lafayette, 2016.
Includes bibliographical references
Video streams usually have to be transcoded to match the characteristics of viewers' devices. Transcoding is a computationally expensive and time-consuming task. Streaming service providers have to store numerous transcoded versions of a given video to serve various display devices, which becomes cost-prohibitive while the video streaming demands increase significantly. Given the fact that viewers' access pattern to video streams follows a long tail distribution, we propose to transcode video streams with low access rate in an on-demand manner using cloud computing services. The challenge in utilizing cloud services for on-demand video transcoding is to maintain a robust QoS for viewers and cost-efficiency for streaming service providers. To address this challenge, in this dissertation, we present a Cloud-based Video Streaming Service (CVSS) architecture which includes a QoS-aware scheduling method to efficiently map video streams to cloud resources. With a detailed study and anlysis of the performance affinity of the transcoding operations on different types of Virtual Machines (VMs), we proposed self-configurable VM provisioning policies to transcode video in a more cost-efficient way. Simulation results demonstrate that with the policies, CVSS architecture maintains a robust QoS for viewers while reducing the incurred cost of the streaming service provider by up to 85%. This dissertation also presents a Cloud-based Video Live Streaming (VLSC) architecture that facilitates transcoding for live video streaming while considering QoS.
Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018
Mode of access: World Wide Web
ISBN: 9780355113099Subjects--Topical Terms:
569006
Computer engineering.
Index Terms--Genre/Form:
554714
Electronic books.
High Performance On-Demand Video Transcoding Using Cloud Services.
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High Performance On-Demand Video Transcoding Using Cloud Services.
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Source: Dissertation Abstracts International, Volume: 78-12(E), Section: B.
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Advisers: Magdy A. Bayoumi; Mohsen Amini Salehi.
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Video streams usually have to be transcoded to match the characteristics of viewers' devices. Transcoding is a computationally expensive and time-consuming task. Streaming service providers have to store numerous transcoded versions of a given video to serve various display devices, which becomes cost-prohibitive while the video streaming demands increase significantly. Given the fact that viewers' access pattern to video streams follows a long tail distribution, we propose to transcode video streams with low access rate in an on-demand manner using cloud computing services. The challenge in utilizing cloud services for on-demand video transcoding is to maintain a robust QoS for viewers and cost-efficiency for streaming service providers. To address this challenge, in this dissertation, we present a Cloud-based Video Streaming Service (CVSS) architecture which includes a QoS-aware scheduling method to efficiently map video streams to cloud resources. With a detailed study and anlysis of the performance affinity of the transcoding operations on different types of Virtual Machines (VMs), we proposed self-configurable VM provisioning policies to transcode video in a more cost-efficient way. Simulation results demonstrate that with the policies, CVSS architecture maintains a robust QoS for viewers while reducing the incurred cost of the streaming service provider by up to 85%. This dissertation also presents a Cloud-based Video Live Streaming (VLSC) architecture that facilitates transcoding for live video streaming while considering QoS.
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click for full text (PQDT)
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