A network calculus with effective bandwidth
This paper establishes a link between two principal tools for the analysis of network traffic, namely, effective bandwidth and network calculus. It is shown that a general version of effective bandwidth can be expressed within the framework of a probabilistic version of the network calculus, where both arrivals and service are specified in terms of probabilistic bounds. By formulating well-known effective bandwidth expressions in terms of probabilistic envelope functions, the developed network calculus can be applied to a wide range of traffic types, including traffic that has self-similar characteristics. As applications, probabilistic lower bounds are presented on the service given by three different scheduling algorithms: Static Priority, Earliest Deadline First, and Generalized Processor Sharing. Numerical examples show the impact of specific traffic models and scheduling algorithms on the multiplexing gain in a network.
network calculus effective bandwidth qos statistical multiplexing