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Optimal content placement and request dispatching for cloud-based video distribution services

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Abstract

The rapid progress of cloud technology has attracted a growing number of video providers to consider deploying their streaming services onto cloud platform for more cost-effective, scalable and reliable performance. In this paper, we utilize Markov decision process model to formulate the dynamic deployment of cloud-based video services over multiple geographically distributed datacenters. We focus on maximizing the average profits for the video service provider over a long run and introduce an average performance criteria which reflects the cost and user experience jointly. We develop an optimal algorithm based on the sensitivity analysis and sample-based policy iteration to obtain the optimal video placement and request dispatching strategy. We demonstrate the optimality of our algorithm with theoretical proof and specify the practical feasibility of our algorithm. We conduct simulations to evaluate the performance of our algorithm and the results show that our strategy can effectively cut down the total cost and guarantee users’ quality of experience (QoE).

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Authors and Affiliations

  1. Department of Automation, University of Science and Technology of China, Hefei, 230027, China

    Zheng-Huan Zhang, Xiao-Feng Jiang & Hong-Sheng Xi

Authors
  1. Zheng-Huan Zhang
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  2. Xiao-Feng Jiang
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  3. Hong-Sheng Xi
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Corresponding author

Correspondence to Hong-Sheng Xi.

Additional information

This work is supported by the State Key Program of National Natural Science Foundation of China (No. 61233003) and National Natural Science Foundation of China (No. 61503358).

Recommended by Associate Editor Yi Cao

Zheng-Huan Zhang received the B. Eng. degree in automation from University of Science and Technology of China, China in 2009. He is currently a Ph.D. degree candidate in Department of Automation at University of Science and Technology of China, China.

His research interests include modeling, optimization and performance analysis of the networking.

ORCID iD: 0000-0001-5066-4364

Xiao-Feng Jiang received the B.Eng. and Ph.D. degrees in information science and technology from University of Science and Technology of China (USTC), China in 2008 and 2013. He is a post doctoral fellow at Department of Automation of USTC from 2013. He has been a post doctoral fellow at the Department of Electrical Engineering, Columbia University, USA, from 2015.

His research interests include spectrum sensing, discrete event dynamic system, and wireless communications.

Hong-Sheng Xi received the B. Sc. and M. Sc. degrees in applied mathematics from University of Science and Technology of China (USTC), China in 1980 and 1985, respectively. He is currently a professor of School of Information Science and Technology, USTC. He also directs the Laboratory of Network Communication System and Control.

His research interests include stochastic control systems, discrete-event dynamic systems, network performance analysis and optimization, and wireless communications.

ORCID iD: 0000-0002-5747-9732

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Zhang, ZH., Jiang, XF. & Xi, HS. Optimal content placement and request dispatching for cloud-based video distribution services. Int. J. Autom. Comput. 13, 529–540 (2016). https://doi.org/10.1007/s11633-016-1025-z

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  • DOI: https://doi.org/10.1007/s11633-016-1025-z

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