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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

Scaling Properties of Statistical End-to-End Bounds in Network Calculus
Citation key CBL-SPSEEBNC-06
Author Ciucu, Florin and Burchard, Almut and Liebeherr, Jorg
Pages 2300–2312
Year 2006
ISSN 0018-9448
DOI http://dx.doi.org/10.1109/TIT.2006.874380
Address Piscataway, NJ, USA
Journal IEEE Transactions on Information Theory
Volume 52
Number 6
Month June
Note Joint issue with IEEE/ACM Transaction on Networking (ToN), Special issue on networking and information theory
Publisher IEEE Press
Abstract The stochastic network calculus is an evolving new methodology for backlog and delay analysis of networks that can account for statistical multiplexing gain. This paper advances the stochastic network calculus by deriving a network service curve, which expresses the service given to a flow by the network as a whole in terms of a probabilistic bound. The presented network service curve permits the calculation of statistical end-to-end delay and backlog bounds for broad classes of arrival and service distributions. The benefits of the derived service curve are illustrated for the exponentially bounded burstiness (EBB) traffic model. It is shown that end-to-end performance measures computed with a network service curve are bounded by O(H log H), where H is the number of nodes traversed by a flow. Using currently available techniques, which compute end-to-end bounds by adding single node results, the corresponding performance measures are bounded by O(H3).
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