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Analytical Performance Evaluation

The success of computer and communication systems strongly depends on their performance, typically reflected in the perception of speed. Optimizing system performance, subject to a set of resource and cost constraints, is thus a critical design goal for system engineers. An elegant technique to help in this matter is performance evaluation which can be performed either by measurements, simulation, or using theoretical methods. In particular, analytical performance evaluation has the fundamental merit of rapidly leading to rigorous and unequivocal insight into the behavior of systems which can be accordingly tuned and optimized.

Our own research is concerned with extending the theory of the stochastic network calculus, which is a probabilistic extension of the deterministic network calculus conceived by R. Cruz in the early 1990's. Over the past two decades the calculus has established itself as a versatile alternative methodology to the classical queueing theory for the performance analysis of computer and communication networks. Its prospect is that it can deal with problems that are fundamentally hard for queueing theory, based on the fact that it works with bounds rather than striving for exact solutions. We are in particular concerned with various fundamental research problems related to modelling and analyzing networks with flow transformations, or improving the bounds accuracy using refined inequalities. On the long term, we believe that our research can significantly contribute to establishing the stochastic network calculus as an indispensable mathematical tool for the performance analysis of resource sharing based systems.

Selected Publications

On Computing Bounds on Average Backlogs and Delays with Network Calculus
Citation key CH-CBABDNC-10
Author Ciucu, Florin and Hohlfeld, Oliver
Title of Book Proceedings of IEEE International Conference on Communications (ICC '10)
Pages 1–5
Year 2010
ISBN 978-1-4244-6402-9
ISSN 1550-3607
DOI http://dx.doi.org/10.1109/ICC.2010.5502376
Location Cape Town, South Africa
Month May
Publisher IEEE
Abstract The stochastic network calculus is an analytical tool which was mainly developed to compute tail bounds on backlogs and delays. From these, bounds on average backlogs and delays are derived in the literature by integration. This paper improves such bounds on average backlogs by using Jensen's inequality; furthermore, improved bounds on average delays follow immediately from Little's Law. The gain factor can be substantial especially at high utilizations, e.g., of order Ω(1/(1-ρ)) when ρ→1. This gain is further numerically illustrated for Markov-modulated On-Off arrival processes. Moreover, the paper shows how to improve standard standard stochastic network calculus performance bounds by suitably using FIFO service curves.
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