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Issue No.06 - June (2012 vol.11)

pp: 1060-1072

Scott Pudlewski , State University of New York (SUNY), Buffalo

Tommaso Melodia , State University of New York (SUNY), Buffalo

Arvind Prasanna , State University of New York (SUNY), Buffalo

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TMC.2011.175

ABSTRACT

This paper presents the design of a networked system for joint compression, rate control and error correction of video over resource-constrained embedded devices based on the theory of Compressed Sensing (CS). The objective of this work is to design a cross-layer system that jointly controls the video encoding rate, the transmission rate, and the channel coding rate to maximize the received video quality. First, compressed sensing-based video encoding for transmission over Wireless Multimedia Sensor Networks (WMSNs) is studied. It is shown that compressed sensing can overcome many of the current problems of video over WMSNs, primarily encoder complexity and low resiliency to channel errors. A rate controller is then developed with the objective of maintaining fairness among different videos while maximizing the received video quality. It is shown that the rate of Compressed Sensed Video (CSV) can be predictably controlled by varying only the compressed sensing sampling rate. It is then shown that the developed rate controller can be interpreted as the iterative solution to a convex optimization problem representing the optimization of the rate allocation across the network. The error resiliency properties of compressed sensed images and videos are then studied, and an optimal error detection and correction scheme is presented for video transmission over lossy channels. Finally, the entire system is evaluated through simulation and test bed evaluation. The rate controller is shown to outperform existing TCP-friendly rate control schemes in terms of both fairness and received video quality. The test bed results show that the rates converge to stable values in real channels.

INDEX TERMS

Compressed sensing, optimization, multimedia content, congestion control, sensor networks.

CITATION

Scott Pudlewski, Tommaso Melodia, Arvind Prasanna, "Compressed-Sensing-Enabled Video Streaming for Wireless Multimedia Sensor Networks",

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