QoS-aware bandwidth provisioning for IP network links

Current bandwidth provisioning procedures for IP network links are mostly based on simple rules of thumb, using coarse traffic measurements made on a time scale of e.g., 5 or 15min. A crucial question, however, is whether such coarse measurements give any useful insight into the capacity actually needed: QoS degradation experienced by the users is strongly affected by traffic rate fluctuations on a much smaller time scale. The present paper addresses this question. The goal is to develop provisioning procedures that require a minimal measurement effort. The bandwidth provisioning formula that we propose (and which we justify under minimal model assumptions) is of the form @[email protected]@r. Here @r (in Mbit/s) is the load of the system, which can evidently be estimated by coarse traffic measurements (e.g., 5 or 15min measurements). The @a depends on the characteristics of the individual flows and the QoS requirements. The QoS measure used is the probability that the traffic supply exceeds the available bandwidth, over some predefined (small) interval T, is below some small fixed number @e. The impact of changing the 'QoS parameters', i.e., T and @e, on the coefficient @a is explicitly given. The validity of the bandwidth provisioning rule is assessed through extensive measurements performed in several operational network environments.

[1]  Ilkka Norros,et al.  Most probable paths and performance formulae for buffers with gaussian input traffic , 2002, Eur. Trans. Telecommun..

[2]  Azer Bestavros,et al.  Self-similarity in World Wide Web traffic: evidence and possible causes , 1996, SIGMETRICS '96.

[3]  Thomas Bonald,et al.  Congestion at flow level and the impact of user behaviour , 2003, Comput. Networks.

[4]  Julio A. Garceran.  A New Approach for Allocating Buffers and Bandwidth to Heterogeneous , Regulated Traffic in an ATM Node ” , 2022 .

[5]  Tobias Oetiker,et al.  MRTG: The Multi Router Traffic Grapher , 1998, LISA.

[6]  Fouad A. Tobagi,et al.  Provisioning IP backbone networks to support latency sensitive traffic , 2003, IEEE INFOCOM 2003. Twenty-second Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE Cat. No.03CH37428).

[7]  Debasis Mitra,et al.  A New Approach for Allocating Buffers and Bandwidth to Heterogeneous Regulated Traffic in an ATM Node , 1995, IEEE J. Sel. Areas Commun..

[8]  Hamid Ahmadi,et al.  Equivalent Capacity and Its Application to Bandwidth Allocation in High-Speed Networks , 1991, IEEE J. Sel. Areas Commun..

[9]  Ilkka Norros,et al.  Testing the Gaussian approximation of aggregate traffic , 2002, IMW '02.

[10]  Alexander L. Stolyar,et al.  Load characterization, overload prediction, and anomaly detection for voice over IP traffic , 2001, SIGMETRICS 2001.

[11]  Åke Arvidsson,et al.  A Resource Allocation Law to Satisfy QoS Demands on ATM Burst and Connection Level , 1999 .

[12]  Ilkka Norros,et al.  On the Use of Fractional Brownian Motion in the Theory of Connectionless Networks , 1995, IEEE J. Sel. Areas Commun..

[13]  Alexandre Proutière,et al.  Statistical bandwidth sharing: a study of congestion at flow level , 2001, SIGCOMM.

[14]  Thomas Bonald,et al.  Statistical bandwidth sharing: a study of congestion at flow level , 2001, SIGCOMM.

[15]  F. Kelly,et al.  Stochastic networks : theory and applications , 1996 .

[16]  Michel Mandjes,et al.  Sample-path large deviations for tandem and priority queues with Gaussian inputs , 2005, math/0505214.

[17]  Sally Floyd,et al.  Wide-area traffic: the failure of Poisson modeling , 1994 .

[18]  Armand M. Makowski,et al.  M|G|/spl infin/ input processes: a versatile class of models for network traffic , 1997, Proceedings of INFOCOM '97.

[19]  Frank Kelly,et al.  Mathematical modeling of the Internet , 1999 .

[20]  Moshe Zukerman,et al.  Performance evaluation of a queue fed by a Poisson Pareto burst process , 2002, Comput. Networks.

[21]  Casey A. Volino,et al.  A First Course in Stochastic Models , 2005, Technometrics.

[22]  Alexander L. Stolyar,et al.  Load characterization and anomaly detection for voice over IP traffic , 2005, IEEE Trans. Neural Networks.

[23]  Ugo Mocci,et al.  Broadband Network Teletraffic: Final Report of Action COST 242 , 1996 .

[24]  B. Engquist,et al.  Mathematics Unlimited: 2001 and Beyond , 2001 .

[25]  Frank Kelly,et al.  Notes on effective bandwidths , 1994 .

[26]  Debasis Mitra,et al.  Effective bandwidth of general Markovian traffic sources and admission control of high speed networks , 1993, TNET.