A TCP-Specific Traffic Profiling and Prediction Scheme for Performance Optimization in OBS Networks

The efficient transmission of transport control protocol (TCP) traffic over optical burst-switched (OBS) networks is a challenging problem, due to the high sensitivity of the TCP congestion control mechanism to losses. In this paper, a TCP-specific traffic profiling and traffic prediction scheme is proposed, for optimizing TCP transmission over one-way OBS networks. In the proposed scheme, the burst assembly unit inspects TCP packet headers in parallel to the assembly process, keeping flow-level traffic statistics. These are then exploited to derive accurate traffic predictions, in at least one round trip time prediction window. This allows traffic schedulers to be notified of upcoming traffic changes in advance, in order to optimally reschedule their resource reservations. In this paper, we detail the traffic profiling and prediction mechanism and also provide analytical and simulation results to assess its performance. The performance gains when using the prediction scheme are shown with a modified one-way OBS reservation protocol, which efficiently and in advance reserves resources at the burst level.