Stationary Markovian arrival processes: Results and open problems




Markovian arrival process (MAP), Markov modulated Poisson process (MMPP), Markov switched Poisson process, over-dispersion, hazard rate, squared coefficient of variation, interarrival times, stationary process., bursty


We consider two classes of irreducible Markovian arrival processes specified by the matrices \(C\) and \(D\): the Markov-modulated Poisson process (MMPP) and the Markov-switched Poisson process (MSPP). The former exhibits a diagonal matrix D while the latter exhibits a diagonal matrix C. For these two classes we consider the following four statements: (I) the counting process is overdispersed; (II) the hazard rate of the event-stationary interarrival time is nonincreasing; (III) the squared coefficient of variation of the event-stationary process is greater than or equal to one; (IV) there is a stochastic order showing that the time-stationary interarrival time dominates the event-stationary interarrival time. For general MSPPs and order two MMPPs, we show that (I)–(IV) hold. Then for general MMPPs, it is easy to establish (I), while (II) is shown to be false by a counter-example. For general simple point processes, (III) follows from (IV). For MMPPs, we conjecture that (IV) and thus (III) hold. We also carry out some numerical experiments that fail to disprove this conjecture. Importantly, modelling folklore has often treated MMPPs as “bursty”, and implicitly assumed that (III) holds. However, to the best of our knowledge, proving this is still an open problem.



Author Biographies

Azam Asanjarani, The University of Auckland

Department of Mathematics, The University of Auckland, Auckland 1142, New Zealand.

Yoni Nazarathy

School of Mathematics and Physics, The University of Queensland, St Lucia, QLD, Australia.





Articles for Printed Issues