Joint source-channel coding and optimization for mobile video streaming in heterogeneous wireless networks

IEEE Trans. Parallel Distrib. Syst.

Cheng

et al. 2015

Self Cite

Load distribution is a key research issue in deploying the limited network resources available to support traffic transmissions. Developing an effective solution is critical for enhancing traffic performance and network utilization. In this paper, we investigate the problem of load distribution for real-time traffic over multipath networks. Due to the path diversity and unreliability in heterogeneous overlay networks, large end-to-end delay and consecutive packet losses can significantly degrade the traffic flow's goodput, whereas existing studies mainly focus on the delay or throughput performance. To address the challenging problems, we propose a GoodputAware Load distribuTiON (GALTON) model that includes three phases: (1) path status estimation to accurately sense the quality of each transport link, (2) flow rate assignment to optimize the aggregate goodput of input traffic, and (3) deadline-constrained packet interleaving to mitigate consecutive losses. We present a mathematical formulation for multipath load distribution and derive the solution based on utility theory. The performance of the proposed model is evaluated through semi-physical emulations in Exata involving both real Internet traffic traces and H.264 video streaming. Experimental results show that GALTON outperforms existing traffic distribution models in terms of goodput, video PSNR (Peak Signal-to-Noise Ratio), end-to-end delay, and aggregate loss rate.

Section: Emulation Setupmentioning

confidence: 99%

Goodput-Aware Load Distribution for Real-Time Traffic over Multipath Networks

IEEE Trans. Parallel Distrib. Syst.

Cheng

et al. 2015

Self Cite

“…The video frame selection and scheduling algorithms are proposed in [43] [44] but the time-varying channel status is not addressed in these solutions. In addition to the above studies, rate control has also been extensively investigated in [34][35][36] for delayconstrained video communication.…”

Section: Delay-constrained Video Communicationmentioning

confidence: 99%

Enabling Adaptive High-Frame-Rate Video Streaming in Mobile Cloud Gaming Applications

IEEE Trans. Circuits Syst. Video Technol.

Cheung

et al. 2015

Self Cite

High frame rate (HFR) video is emerging in popular gaming applications to enhance the smooth experience perceived by end-users. However, it is challenging to guarantee the delivery quality of HFR video in mobile cloud gaming scenarios because of the high transmission rate and limited wireless resources. To address this critical problem, we develop a novel transmission scheduling framework dubbed AdaPtive HFR vIdeo Streaming (APHIS). The term "adaptive" indicates this scheme's capability in dynamically adjusting the video traffic load and FEC (Forward Error Correction) coding. First, we propose an online video frame selection algorithm to minimize the total distortion based on the network status, input video data and delay constraint. Second, we introduce an unequal FEC coding scheme to provide differentiated protection for Intra (I) and Predicted (P) frames with low-latency cost. The proposed APHIS framework is able to appropriately filter video frames and adjust data protection levels to optimize the quality of HFR video streaming. We conduct extensive emulations in Exata involving HFR video encoded with H.264 codec. Experimental results show that APHIS outperforms the reference transmission schemes in terms of video PSNR (Peak Signal-to-Noise Ratio), end-to-end delay, and goodput. Therefore, we recommend APHIS for delivering HFR video streaming in mobile cloud gaming systems.Index Terms-High frame rate video, mobile cloud gaming, video frame selection, unequal error protection, forward error correction.

“…Based on the models, the authors develop models for rate control, FEC redundancy adaption and video quality of Skype. Indeed, rate control [47][48][49][50] is an effective solution to handle the bandwidth fluctuations and can be a future research direction to integrate with the proposed TELFORD to enhance streaming video quality. The design of an efficient rate control algorithm is a challenging task in the context of multiple-destination video communication.…”

Section: B Related Workmentioning

confidence: 99%

Trading Delay for Distortion in One-Way Video Communication Over the Internet

Cheng

IEEE Trans. Circuits Syst. Video Technol.

et al. 2016

Self Cite

We study the problem of one-way video communication in single-source, multiple-destination scenario over the lossy Internet. Forward Error Correction (FEC) coding is commonly adopted for data protection in implementing loss-resilient video transmission systems. However, the burst packet losses over the Internet frequently degrade the FEC performance and induce video quality deteriorations. To address the challenging problem, we propose a novel transmission scheme dubbed Trading dELay FOR Distortion (TELFORD) that includes three components: 1) adaptive multi-destination status estimation; 2) delay-constrained transmission rate assignment; 3) differentiated FEC packets spreading. We analytically formulate and solve the problem of FEC packets allocation and scheduling to minimize the endto-end video distortion. The proposed TELFORD is able to cope with multiple-destination scheduling separately. We conduct the performance evaluation through semi-physical emulations in Exata using real-time H.264 video streaming. Experimental results show that TELFORD outperforms existing error control transmission schemes in improving the video PSNR (Peak Signalto-Noise Ratio) and mitigating packet transmission impairments.