Logarithmic window increase for TCP Westwood+ for improvement in high speed, long distance networks
The majority of current Internet applications uses Transmission Control Protocol (TCP) for ensuring reliable end-to-end delivery of data over IP networks. The resulting path is, generally speaking, characterized by fairly large propagation delays (of the order of tens to hundreds of milliseconds) and increasing available bandwidth. Current TCPperformance is far from representing an optimal solution in such operating conditions. The main reason lies in the conservative congestion control strategy employed, which does not let TCP to exploit the always increasing available path capacity. As a consequence, TCP optimization has been an active research topic in the research community over the last 25 years, boosted in the last few years by the widespread adoption of high-speed optical fiber links in the backbone and the emergence of supercomputing networked applications from one side and tremendous growth of wireless bandwidth in network access from another. This has led to the introduction of several alternative proposals for performing congestion control. Most of them focus on the effectiveness of bandwidth utilization, introducing more ''aggressive'' congestion control strategies. However, such approaches result often in unfairness among flows with substantially different RTTs, or do not present the inter-protocol fairness features required for incremental network deployment. In this paper, we propose TCP LogWestwood+, a TCP Westwood+ enhancement based on a logarithmic increase function, targeting adaptation to the high-speed wireless environment. The algorithm shows low sensitivity with respect to RTT value, while maintaining high network utilization in a wide range of network settings. The performance, fairness and stability properties of the proposed TCP LogWestwood+ are studied analytically, and then validated by means of an extensive set of experiments including computer simulations and wide area Internet measurements.