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Motivated by emerging vision-based intelligent services, we consider theproblem of rate adaptation for high quality and low delay visual informationdelivery over wireless networks using scalable video coding. Rate adaptation inthis setting is inherently challenging due to the interplay between thevariability of the wireless channels, the queuing at the network nodes and theframe-based decoding and playback of the video content at the receiver at veryshort time scales. To address the problem, we propose a low-complexity,model-based rate adaptation algorithm for scalable video streaming systems,building on a novel performance model based on stochastic network calculus. Wevalidate the model using extensive simulations. We show that it allows fast,near optimal rate adaptation for fixed transmission paths, as well ascross-layer optimized routing and video rate adaptation in mesh networks, withless than $10$\% quality degradation compared to the best achievableperformance.

Performance Analysis of Reliable Video Streaming with Strict Playout Deadline in Multi-Hop Wireless Networks