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Department of Electrical and Computer Engineering, McGill University

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Project Abstracts Return to AAPN Projects

Traffic Demand Modelling & Prediction
 

Student: Wei Liu, M.Eng Student
Supervisor: Prof. Mark Coates

Abstract: In a wide-area network like AAPN, the control functionality will be implemented primarily at the edge of the photonic core. If core node performing time slot switching, the edge nodes request and relinquish time slots based on predicted upper bound on source-destination traffic demands. We propose a dynamic parametric traffic model to capture the traffic behavior in AAPN, which includes a time-varying Poisson model for total incoming traffic of an edge node and a gravity model for the splitting of the total incoming traffic between individual destinations. This approach allows us to capture both temporal and spatial information.

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