Scaling properties of statistical end-to-end bounds in the network calculus

• Published in: IEEE transactions on information theory Vol. 52; no. 6; pp. 2300 - 2312
• Main Authors: Ciucu, F., Burchard, A., Liebeherr, J.
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.06.2006; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Bursting; Calculus; Communications networks; Computer networks; Delay; Delay estimation; Fluid flow measurement; Gain; Intelligent networks; Mathematical analysis; Multiplexing; Network service curve; Networks; Quality of service; Stochastic models; stochastic network calculus; Stochastic processes; Stochasticity; Studies; Switches; Telecommunication traffic; Traffic control
• ISSN: 0018-9448; 1063-6692; 1557-9654; 1558-2566
• DOI: 10.1109/TIT.2006.874380

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 /spl Oscr/(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 /spl Oscr/(H/sup 3/).