Intelligent congestion control is vital in encoded video streaming of a clip or film, as network traffic volatility requires constant adjustment of the bit-rate. Equation-based solutions to congestion control are prone to fluctuations in the delivery rate and may respond only when packet loss has already occurred, while both fluctuations and packet loss affect the end-user's perception of the delivered video. A type-1 fuzzy logic controller can operate at video display rates and can cope with uncertainties in packet delay measurements but this paper proposes an interval type-2 fuzzy logic congestion controller, as this has the ability to anticipate un-modeled network states, besides potentially reducing training time prior to deployment. The paper demonstrates an order of magnitude improvement in delivered video quality using type-2 fuzzy logic in respect to type-1 logic, when the control inputs are subject to noise, and reduced packet loss compared to an equation-based controller.
This paper seeks to establish under what conditions (mobility, network size, wireless channel) multi-source video streaming is feasible across a wireless Vehicular Ad Hoc Network (VANET). Overlay networks with multiple sources have proven to be robust, distributed solutions to multimedia transport, including streaming. To achieve video streaming over a VANET overlay, this paper introduces a spatial partition of a video stream based on Flexible Macroblock Ordering. Tests show this can achieve a gain of over 5 dB in video quality (PSNR) depending on video content and packet loss rates. However, routing of streamed services over multiple hops and multiple paths may lead to significant packet losses, resulting in unacceptable quality of service. The paper examines the impact of differing traffic densities and road layouts upon an overlay network's performance. The work modeled the emerging IEEE 802.11p for wireless VANETs. The research demonstrates that the vehicles' mobility pattern and their drivers' behaviour need to be carefully modeled to determine signal reception. The paper also considers the impact of the wireless channel, which also should be more realistically modeled.
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