Reactive Robust Routing: Anomaly Localization and Routing Reconfiguration for Dynamic Networks

This paper presents a novel approach to deal with dynamic and highly uncertain traffic in dynamic network scenarios. The Reactive Robust Routing (RRR) approach is introduced, a combination of proactive and reactive techniques to improve network efficiency and robustness, simplifying network operation. RRR optimizes routing for normal-operation traffic, using a time-varying extension of the already established Robust Routing technique that outperforms the stable approach. To deal with anomalous and unexpected traffic variations, RRR uses a fast anomaly detection and localization algorithm that rapidly detects and localizes abrupt changes in traffic flows, permitting an accurate routing adaptation. This algorithm presents well-established optimality properties in terms of detection/localization rates and localization delay, which allows for generalization of results, independently of particular evaluations. The algorithm is based on a novel parsimonious model for traffic demands which allows for detection of anomalies using easily available aggregated-traffic measurements, reducing the overheads of data collection.

[1]  G. Nürnberger.  Approximation by Spline Functions , 1989 .

[2]  Michèle Basseville,et al.  Detection of abrupt changes , 1993 .

[3]  I. V. Nikiforov,et al.  A lower bound for the detection/isolation delay in a class of sequential tests , 2003, IEEE Trans. Inf. Theory.

[4]  Jennifer Rexford,et al.  Sensitivity of PCA for traffic anomaly detection , 2007, SIGMETRICS '07.

[5]  Michèle Basseville,et al.  Detection of Abrupt Changes: Theory and Applications. , 1995 .

[6]  Edith Cohen,et al.  Making intra-domain routing robust to changing and uncertain traffic demands: understanding fundamental tradeoffs , 2003, SIGCOMM '03.

[7]  Yin Zhang,et al.  COPE: traffic engineering in dynamic networks , 2006, SIGCOMM 2006.

[8]  Robert Nowak,et al.  Internet tomography , 2002, IEEE Signal Process. Mag..

[9]  Christophe Diot,et al.  Traffic matrix estimation: existing techniques and new directions , 2002, SIGCOMM 2002.

[10]  Konstantina Papagiannaki,et al.  Traffic matrices: balancing measurements, inference and modeling , 2005, SIGMETRICS '05.

[11]  Michèle Basseville,et al.  Detection of abrupt changes: theory and application , 1993 .

[12]  S. Vaton,et al.  Robust and Reactive Traffic Engineering for Dynamic Traffic Demands , 2008, 2008 Next Generation Internet Networks.

[13]  Mark Crovella,et al.  Characterization of network-wide anomalies in traffic flows , 2004, IMC '04.

[14]  W. Ben-Ameur.  Between fully dynamic routing and robust stable routing , 2007, 2007 6th International Workshop on Design and Reliable Communication Networks.

[15]  Christophe Diot,et al.  Diagnosing network-wide traffic anomalies , 2004, SIGCOMM.

[16]  Srikanth Kandula,et al.  Walking the tightrope: responsive yet stable traffic engineering , 2005, SIGCOMM '05.

[17]  Albert G. Greenberg,et al.  Fast accurate computation of large-scale IP traffic matrices from link loads , 2003, SIGMETRICS '03.

[18]  Albert G. Greenberg,et al.  Network anomography , 2005, IMC '05.

[19]  Sandrine Vaton,et al.  An adaptive multi-temporal approach for robust routing , 2007 .

[20]  Mikkel Thorup,et al.  Traffic engineering with estimated traffic matrices , 2003, IMC '03.

[21]  Donald F. Towsley,et al.  On optimal routing with multiple traffic matrices , 2005, Proceedings IEEE 24th Annual Joint Conference of the IEEE Computer and Communications Societies..

[22]  Cheng Jin,et al.  MATE: MPLS adaptive traffic engineering , 2001, Proceedings IEEE INFOCOM 2001. Conference on Computer Communications. Twentieth Annual Joint Conference of the IEEE Computer and Communications Society (Cat. No.01CH37213).

[23]  Pedro Casas,et al.  Multi Hour Robust Routing and Fast Load Change Detection for Traffic Engineering , 2008, 2008 IEEE International Conference on Communications.

[24]  Deep Medhi,et al.  Routing, flow, and capacity design in communication and computer networks , 2004 .

[25]  Kavé Salamatian,et al.  Combining filtering and statistical methods for anomaly detection , 2005, IMC '05.

[26]  Matthew Roughan,et al.  Computation of IP traffic from link , 2003, SIGMETRICS 2003.

[27]  Walid Ben-Ameur,et al.  Routing of Uncertain Traffic Demands , 2005 .

[28]  Igor V. Nikiforov.  A simple recursive algorithm for diagnosis of abrupt changes in random signals , 2000, IEEE Trans. Inf. Theory.

[29]  Thierry Chonavel,et al.  Efficient methods for traffic matrix modeling and on-line estimation in large-scale IP networks , 2009, 2009 21st International Teletraffic Congress.