A TCP Prediction Scheme for Enhancing Performance in OBS Networks

The efficient transmission of TCP traffic over OBS networks is a challenging problem, due to the high sensitivity of TCP congestion control mechanism to losses. In this paper, a traffic prediction scheme is proposed that exploits TCP traffic dynamics to optimize the performance of TCP transmission over OBS networks. Due to the TCP flow control mechanism, traffic dynamics can be accurately predicted in at least one RTT-long prediction window. In the proposed scheme, the prediction process is tightly coupled with the burst assembly process since the edge node is capable of inspecting incoming TCP traffic, keeping traffic statistics in parallel to the assembly process. These statistics are then used for traffic predictions. In this way burst size can be predicted and thus in advance reserve the appropriate resources. In this paper, we detail the traffic prediction mechanism and we also provide simulation results to assess its performance.