ETAQA Truncation Models for the MAP/MAP/1 Departure Process

Authors:
Armin Heindl;Qi Zhang;Evgenia Smirni
Affiliations:
University Erlangen-Nuremberg, Germany;College of William and Mary, VA;College of William and Mary, VA
Venue:
QEST '04 Proceedings of the The Quantitative Evaluation of Systems, First International Conference
Year:
2004

Citing 0
Cited 6

Reconfigurable, Data-Driven Resource Allocation in Complex Systems: Practice and Theoretical Foundations

IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Workshop 10 - Volume 11
Correlation bounds for second-order MAPs with application to queueing network decomposition

Performance Evaluation - Modelling techniques and tools for computer performance evaluation
A tool for the analysis of hierarchical service-oriented extended open fork/join queueing networks

Proceedings of the 2nd international conference on Performance evaluation methodologies and tools
A joint moments based analysis of networks of MAP/MAP/1 queues

Performance Evaluation
Modeling Cross Correlation in Three-Moment Four-Parameter Decomposition Approximation of Queueing Networks

Operations Research
The two-moment three-parameter decomposition approximation of queueing networks with exponential residual renewal processes

Queueing Systems: Theory and Applications

Quantified Score

Hi-index	0.00

Visualization

Abstract

We propose a family of finite approximations for the departure process of a MAP/MAP/1 queue. The departure process approximations are derived via an exact aggregate solution technique (called ETAQA) applied to Quasi-Birth-Death processes (QBDs) and require only the computation of the frequently sparse fundamental-period matrix G. The approximations are indexed by a parameter n, which determines the size of the output model as n +1 QBD levels. The marginal distribution of the true departure process and the lag correlations of the interdeparture times up to lag n - 1 are preserved exactly. Via experimentation we show the applicability of the proposed approximation in traffic-based decomposition of queueing networks and investigate how correlation propagates through tandem queues.