Artificial Intelligence Resources in Control and Automation Engineering

Indexed in: Book Citation Index, Science Edition, Scopus, EBSCO.

This e-book focuses on the application of artificial intelligence resources in fields related to Control and Automation Engineering. Techniques such as neural networks, fuzzy logic and expert systems ...
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Engineering Congestion Control of Internet Video Streaming with Fuzzy Logic

Pp. 92-107 (16)

Martin Fleury, Emanuel A. Jammeh and Mohammed Ghanbari


Congestion control of video streaming over the Internet is necessary, as access to these telecommunications networks is unregulated. A commercial IPTV service in this environment faces unacceptable quality degradation, if the video stream does not respond to the presence of other competing traffic flows. As a solution, fuzzy logic control offers real-time performance, comparatively simple models, fairness to other traffic, and a smooth response. This Chapter introduces the control problem faced in designing a fuzzy logic congestion controller in terms of the restrictions of a compressed video bitstream and the uncertainties that affect congestion control. The Chapter outlines the design of a congestion controller that relies on network packet delay and delay trend as inputs. The controller has been extensively tested and favorably compared to the standard congestion controller. Multimedia applications over telecommunications networks are a promising area to apply computational intelligence.


Congestion control, fuzzy logic, internet video straming.


University of Essex, School of Computer Science and Electronic Engineering, Multimedia Network Laboratory, Colchester, CO4 3SQ, United Kingdom