Satisfying QoS with a learning based scheduling algorithm

Considers the problem of scheduling packets in a multiplexer, the aim being to provide sufficient service to each traffic stream such that their objectives are just satisfied, thus maximising the resources available for other streams. We propose a novel scheduling scheme based on stochastic learning automata which is capable of satisfying a variety of delay requirements in a dynamic traffic environment, and we show via simulation that the scheme outperforms several existing scheduling algorithms.