Exact aggregate solutions for M/G/1-type Markov processes

Abstract

We introduce a new methodology for the exact analysis of M/G/1-type Markov processes. The methodology uses basic, well-known results for Markov chains by exploiting the structure of the repetitive portion of the chain and recasting the overall problem into the computation of the solution of a finite linear system. The methodology allows for the calculation of the aggregate probability of a finite set of classes of states from the state space, appropriately defined. Further, it allows for the computation of a set of measures of interest such as the system queue length or any of its higher moments. The proposed methodology is exact. Detailed experiments illustrate that the methodology is also numerically stable, and in many cases can yield significantly less expensive solutions when compared with other methods, as shown by detailed time and space complexity analysis.