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Details of Grant 

EPSRC Reference: GR/S15730/01
Title: Adaptive Methods and Congestion Control for Internet Traffic
Principal Investigator: Arrowsmith, Professor DK
Other Investigators:
Mondragon, Dr RJ Pitts, Professor JM
Researcher Co-Investigators:
Project Partners:
Department: Sch of Mathematical Sciences
Organisation: Queen Mary University of London
Scheme: Overseas Travel Grants Pre-FEC
Starts: 07 November 2002 Ends: 06 May 2003 Value (£): 6,550
EPSRC Research Topic Classifications:
Networks & Distributed Systems
EPSRC Industrial Sector Classifications:
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Panel History:  
Summary on Grant Application Form
It was shown by Leland in the mid-90s that packet traffic in an ethernet network exhibited self-similarity or long-range dependence (LRD). High variability and bursty behaviour of the packet traffic rate is seen over a range of time scales, by contrast, for example, with 'memoryless' voice traffic. One of the key statistical features which describes the self-similarity is the auto-correlation of packet profiles in a binary channel. The auto-correlation decay is exhibited as a power-law of the lag time. Essentially the variance of the batch averages does not decay rapidly with increase of the batch size. This results in LRD traffic with so-called 'memory'. This is to be compared with the once traditional voice-traffic over communication channels which is described as 'short-term' dependent' traffic. The key problems to address are:(a) the precise nature of LRD in networks and how it changes with respect to natural cycles of usage, type of traffic; (b) the modelling of these phenomena, (c) the nature of the onset of congestion in real networks; (d) the adapting of current protocols and the development of new protocols to address the long onset of congestion for LRD traffic and the associated erratic arrival time of packets.
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