By Topic

Faster Maximum Likelihood Estimation Algorithms for Markovian Arrival Processes

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Hiroyuki Okamura ; Dept. of Inf. Eng., Hiroshima Univ., Higashi-Hiroshima, Japan ; Tadashi Dohi

This paper proposes two improvements of fitting algorithms for Markovian arrival processes (MAPs). The first improvement is to enhance the computation speed of Ryd'en's EM algorithm (1996) for estimating MAP parameters. The second one is to provide an efficient sub-class of MAPs to be appropriate for fitting to real traffic data. More precisely, we propose a traffic modeling based on a hidden Markov model which belongs to a sub-class of MAPs. Such a modeling framework leads to a faster fitting algorithm than the conventional algorithm with general MAPs. In numerical examples, we present the effectiveness of proposed fitting algorithms through a real traffic trace.

Published in:

Quantitative Evaluation of Systems, 2009. QEST '09. Sixth International Conference on the

Date of Conference:

13-16 Sept. 2009