Toronto Networking Seminar 2006

On the Scaling of Statistical Delay Bounds
in  Communication Networks

Florin Ciucu
University of Virginia

Date:  February  17,  3pm
Location: BA1210 (Bahen Center)


The stochastic network calculus is an evolving new methodology for backlog and delay analysis of networks that can account for statistical multiplexing gain. This talk presents recent advances on  the development of statistical  network service curves,  that can express  the service experienced by a traffic flow in a network 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 previously available techniques, which compute end-to-end bounds by adding single node results, the corresponding performance measures are bounded by O(H^3).


Florin Ciucu received the B.Sc. degree in Informatics from the Faculty of Mathematics, University of Bucharest, in 1998, and the M.Sc. degree in Computer Science from George Mason University, in 2001. He is currently pursuing a Ph.D. degree in Computer Science at the University of Virginia. He received the Best Student Paper award at the ACM Sigmetrics 2005 Conference.