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Toward Transcoding as a Service in a Multimedia Cloud: Energy-Efficient Job-Dispatching Algorithm

delete2014-06-01
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PRE
AI
W
Weiwen Zhang *
Yonggang Wen 封面图
Yonggang Wen (Yonggang Wen)
Jianfei Cai 封面图
Jianfei Cai (Jianfei Cai)
D
Dapeng Wu
DOI:10.1109/TVT.2014.2310394delete
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摘要

摘要

En 中文
In this paper, we investigate the energy-efficient job-dispatching algorithm for transcoding as a service (TaaS) in a multimedia cloud. We aim to minimize the energy consumption of service engines in the cloud while achieving low delay for TaaS. We formulate the job-dispatching problem as a constrained optimization problem under the framework of Lyapunov optimization. Using the drift-plus-penalty function, we propose an online algorithm that dispatches the transcoding jobs to service engines, with an objective to Reduce Energy consumption while achieving the QUEue STability (REQUEST). We first characterize the fundamental tradeoff between energy consumption and queue delay for the REQUEST algorithm numerically and obtain its performance bound theoretically. Second, we study the robustness of the REQUEST algorithm, with numerical results indicating that the REQUEST algorithm is robust to the inaccuracy of estimating the transcoding time. Third, we compare the performance of the REQUEST algorithm with the other two algorithms, i.e., the Round Robin and Random Rate algorithms. By simulation and real trace data, we show that by appropriately choosing the control variable, the REQUEST algorithm outperforms the Round Robin and Random Rate algorithms, with smaller time average energy consumption and time average queue length. The proposed REQUEST algorithm can be applied in cloud-assisted multimedia transcoding service.
Keyword:
Energy efficiency
job dispatching
transcoding as a service (TaaS)
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期刊

IEEE Transactions on Vehicular Technology 封面图
IEEE Transactions on Vehicular Technology
IF:
7.1
论文数:
1.8W
被引数:
6.6W

机构

State University System of Florida 封面图
State University System of Florida
学者数:
12.8W
论文数: 10.9W
被引数: 130
N
Nanyang Technological University
学者数:
4.9W
论文数: 4.8W
被引数: 8.1W
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