Optimizing Quality-of-Experience for HTTP-based Adaptive Video Streaming: An SDN-based Approach

Sangeeta Ramakrishnan, Xiaoqing Zhu, Frank Chan, Kashyap Kodanda Ram Kambhatla, Zheng Lu, Cindy Chan and Bhanu Krishnamurthy
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Sangeeta Ramakrishnan: Cisco Systems, San Jose, CA, USA
Xiaoqing Zhu: Cisco Systems, San Jose, CA, USA
Frank Chan: Cisco Systems, San Jose, CA, USA
Kashyap Kodanda Ram Kambhatla: Cisco Systems, San Jose, CA, USA
Zheng Lu: Cisco Systems, San Jose, CA, USA
Cindy Chan: Cisco Systems, San Jose, CA, USA
Bhanu Krishnamurthy: Cisco Systems, San Jose, CA, USA

International Journal of Multimedia Data Engineering and Management (IJMDEM), 2016, vol. 7, issue 4, 22-44

Abstract: In this work, the authors present a novel bandwidth management solution for optimizing overall quality of experience (QoE) of multiple video streaming sessions. Instead of allocating bandwidth equally among competing flows, they propose to tailor the bandwidth allocation to both content complexity of requested video and playout buffer status of individual clients. The authors formulate the multi-client bandwidth allocation problem within the convex optimization framework, which is flexible enough to accommodate a wide variety of video quality metrics. Further, the authors present a practical architecture based on software defined networking (SDN) with two components: video quality monitoring and video quality optimization. Testbed-based experiments confirm that with quality-optimized allocation the network can support up to 75% more users at the same level of quality-of-experience (QoE) than conventional equal-rate allocations.

Date: 2016
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