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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 Ω(HlogH) Scaling of Network Delays
Citation key BLC-OOSND-07
Author Burchard, Almut and Liebeherr, Jorg and Ciucu, Florin
Title of Book Proceedings of IEEE INFOCOM 2007
Pages 1866–1874
Year 2007
ISBN 1-4244-1047-9
ISSN 0743-166X
DOI http://dx.doi.org/10.1109/INFCOM.2007.217
Location Anchorage, AK, USA
Address New York, NY, USA
Month May
Publisher IEEE
Abstract A recent result in network calculus theory provided statistical delay bounds for exponentially bounded traffic that grow as O(H log H) with the number of nodes on the network path. In this paper we establish the corresponding lower bound which shows that for such such types of traffic, typical end-to-end delays can indeed grow as Theta (H log H). The lower bound is obtained by analyzing the end-to-end delay in a tandem network where each packet maintains the same service time at each traversed node. The results of this paper provide conclusive evidence that, in general, delays have a qualitatively different scaling behavior than is suggested by a worst-case analysis or by an analysis that assumes independent service times at network nodes.
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