• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

A Bandwidth Estimation Scheme to Improve the QoE of HTTP Adaptive Streaming in the Multiple Client Environment

Vol. 12, No.1, January 31, 2018
10.3837/tiis.2018.01.015, Download Paper (Free):

Abstract

Abstract-HTTP adaptive streaming (HAS) is a promising technology for delivering video content over the Internet. HAS-based video streaming solutions rely on bandwidth estimation to select the appropriate video bitrate. Video streaming solutions that consider network conditions provide users with seamless video playback. However, when multiple clients compete for a common bottleneck link, conventional bandwidth estimation schemes that consider only one client overestimate the network bandwidth due to the ON-OFF traffic pattern. The bandwidth overestimation can cause Quality of Experience (QoE) degradation, such as unnecessary changes in video quality, and unfairness of video quality. In this paper, we propose a client-side bandwidth estimation scheme to obtain a better QoE of HAS in the multiple-client environment. The proposed scheme differentiates the client buffer status according to the buffer occupancy, and then estimates the available network bandwidth based on the buffer status and segment throughput. We evaluate the performance of HAS implemented in the ns-3 network simulator. Simulation results show that compared with the conventional schemes, the proposed scheme can enhance the QoE.


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Cite this article

[IEEE Style]
Sangwook Kim and Kwangsue Chung, "A Bandwidth Estimation Scheme to Improve the QoE of HTTP Adaptive Streaming in the Multiple Client Environment," KSII Transactions on Internet and Information Systems, vol. 12, no. 1, pp. 308-324, 2018. DOI: 10.3837/tiis.2018.01.015

[ACM Style]
Kim, S. and Chung, K. 2018. A Bandwidth Estimation Scheme to Improve the QoE of HTTP Adaptive Streaming in the Multiple Client Environment. KSII Transactions on Internet and Information Systems, 12, 1, (2018), 308-324. DOI: 10.3837/tiis.2018.01.015