Modelling the Performance of In-Call Probing for Multi-Level Adaptive Applications

This paper looks at adaptive applications that can switch between a small number of different levels of service, with switching decisions made solely by the originating end-system. Typical of such applications are real time streaming protocols which can use different coding rates. The end-systems probe the network with sample traffic to determine congestion, and decide at what rate to enter according to the fate of their “probe” packets. During the lifetime of a connection, the procedure is repeated to reassess and possibly readjust the rate. We derive analytic models, based on diffusion limits under a natural scaling, to quantify the benefits of in-call probing. We then use simulation to compare the results in a number of scenarios, and show that this simple theory is remarkably accurate in predicting large-scale behaviour. The results also show that a small amount of in-call probing produces significant benefits to the system.