Cyclic markov modulated poisson processes in traffic characterization
David Teyao Chen, Maria Rieders · Stochastic Models · 1996
A new class of Markov modulated Poisson processes (MMPP) is introduced where arrival rates vary according to a cyclic Markov chain. A closed form expression for the autocovariance function of the arrival rate process is derived and a recursive procedure for its calculation is given. Using a least square fitting procedure, the cyclic MMPP is applied to model packetized video traffic. A comparison with simulation results and other MMPP models from the literature reveal that a cyclic model can provide good estimates for performance measures of interest