Fitting with matrix exponential mixtures generated by discrete probabilistic scaling
File(s)
Accepted version
Author(s)
Bor, Julianna
Casale, Giuliano
Knottenbelt, William
Smirni, Evgenia
Stathopoulos, Andreas
Type
Journal Article
Abstract
Matrix exponential (ME) distributions generalize phase-type distributions; however, their use in queueing theory is hampered by the difficulty of checking their feasibility. We propose a novel ME fitting algorithm that produces a valid distribution by construction. The ME distribution used during the fitting is a product of independent random variables that are easy to control in isolation. Consequently, the calculation of the CDF and the Mellin transform factorizes, making it possible to use these measures for the fitting without significant restriction on the distribution order. Trace-driven queueing simulations indicate that the resulting distributions yield highly accurate results.
Date Issued
2023-09-28
Date Acceptance
2023-10-01
Citation
ACM SIGMETRICS Performance Evaluation Review, 2023, 51 (2), pp.15-17
ISSN
0163-5999
Publisher
Association for Computing Machinery (ACM)
Start Page
15
End Page
17
Journal / Book Title
ACM SIGMETRICS Performance Evaluation Review
Volume
51
Issue
2
Copyright Statement
Copyright © 2023 Copyright is held by the owner/author(s).
Publication Status
Published
Article Number
2
Date Publish Online
2023-10-02