Michael T. Loiacono (Rutgers University) “Cross-layer performance analysis and adaptation for real-time wireless video streaming” (2011)

Michael T. Loiacono (Rutgers University) “Cross-layer performance analysis and adaptation for real-time wireless video streaming”, Advisor: Prof. Wade Trappe (2011)

The proliferation of wireless technology, mobile computing, and increasingly sophisticated video codecs have fueled the sharp increase in demand for user and machine-centric applications (such as IPTV, telemedicine, cyber-physical control, and surveillance) involving wireless video streaming. Unfortunately, today's state of the art local wireless technologies, such as IEEE 802.11, can be easily demonstrated to fail when subjected to the conditions associated with many of these real-world applications. This is because wireless video streaming involves complex relationships between the video codec, the wireless PHY and MAC, and the application's (or user's) sensitivity to distortions in the video signal, and these relationships are not well understood or exploited by today's video streaming systems. In this dissertation, the author reveals and analyzes several key obstacles to wireless video streaming, and propose a set of adaptive real-time cross-layer approaches to deal with them. The dissertation begins with an overview of the major hurdles to wireless video streaming. A particular focus is on the instability of current link adaptation algorithms in CSMA/CA based wireless systems under the congested scenarios associated with wireless transmission of multiple simultaneous uplink video streams. Additionally, this dissertation focuses on congestion control with respect to the fairness policies employed by the IEEE 802.11 channel access mechanism, and demonstrates that airtime fairness is preferred to throughput fairness for transmission of multiple simultaneous uplink video streams in a multi-rate environment. Several other obstacles are presented, including: the need for cross-layer approaches in wireless video streaming; problems with the use of MSE and PSNR in existing cross-layer approaches in today's literature; and the difficulty with perceptual, task-based video quality assessment in the context of an adaptive real-time cross-layer video streaming system. After that, the author proposes several adaptive real-time cross-layer solutions to deal with these obstacles. They include: (i) airtime fair distributed cross-layer congestion control in multi-rate wireless environments; (ii) cross-layer link adaptation for wireless-video; (iii) video quality assessment in adaptive real-time cross-layer video streaming systems; and (iv) joint link adaptation and congestion control driven by user/task-centric resource allocation.

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