Characterization of moments and autocorrelation in MAPs

Authors:
Giuliano Casale;Eddy Z. Zhang;Evgenia Smirni
Affiliations:
College of William & Mary, Williamsburg, VA;College of William & Mary, Williamsburg, VA;College of William & Mary, Williamsburg, VA
Venue:
ACM SIGMETRICS Performance Evaluation Review
Year:
2007

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Abstract

Markovian Arrival Processes (MAPs) [9] are a general class of point processes which admits, hyper-exponential, Erlang, and Markov Modulated Poisson Processes (MMPPs) as special cases. MAPs can be easily integrated within queueing models. This makes MAPs useful for evaluating the impact of non-Poisson workloads in networking and for quantifying the performance of multi-tiered e-commerce applications and disk drives [8, 10].