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Streaming Mobile Cloud Gaming Video Over TCP With Adaptive Source-FEC Coding
Journal article   Peer reviewed

Streaming Mobile Cloud Gaming Video Over TCP With Adaptive Source-FEC Coding

Jiyan Wu, Chau Yuen, Ngai-Man Cheung, Junliang Chen and Chang Wen Chen
IEEE transactions on circuits and systems for video technology, Vol.27(1), pp.32-48
01/01/2017

Abstract

Engineering Engineering, Electrical & Electronic Science & Technology Technology
Cloud gaming has emerged as a promising application to enable high-end game playing with thin clients. Transmission control protocol (TCP) is pervasively adopted as the transport-layer protocol in the mainstream cloud gaming systems for video communication. However, streaming mobile cloud gaming video using the TCP is challenged with several key technical barriers: 1) the performance limitations of wireless networks in bandwidth and reliability; 2) the high throughput demand and stringent delay constraint imposed by high-quality gaming video transmission; and 3) the deadline violations and throughput fluctuations caused by the packet retransmission and congestion control mechanisms in the TCP. To address these critical problems, this paper proposes an application-layer source-forward error correction (FEC) coding framework dubbed adaptive sourceFEC coding over TCP (ESCOT). First, we analytically formulate the optimization problem of joint source- FEC coding to minimize the end-to-end distortion of real-time video communication over TCP. Second, we develop a heuristic solution for effective loss rate approximation, source rate control, and FEC coding adaptation. ESCOT is distinct from existing source- FEC coding schemes in proactive lyanalyzing and leveraging the TCP characteristics. The proposed solution is able to effectively mitigate both consecutive and sporadic video frame drops caused by congestion and random packet losses. We conduct the performance evaluation through extensive emulations in the Exata platform using realtime gaming video encoded by the H. 264 codec. Experimental results show that the ESCOT advances the state of the art with noticeable improvements in video peak signal-to-noise ratio, end-to-end delay, goodput, and frame success rate.

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