Maximum Delay Computation under Traffic Matrix Uncertainty and Its Application to Interdomain Path Selection

One of the most important problems when deploying interdomain path selection with quality of service requirements is being able to rely the computations on metrics that hold for a long period of time. Our proposal for achieving such assurance is to compute bounds on the metrics, taking into account the uncertainty on the traffic demands. In particular, we will explore the computation of the maximum end-to-end delay of traversing a domain considering that the traffic is unknown but bounded. Since this provides a robust quality of service value for traversing the Autonomous System (AS), without revealing confidential information, we claim that the bound can be safely conceived as a metric to be announced by each AS to the entities performing the path selection, in the process of interdomain path selection. We show how the maximum delay value is obtained for an interdomain bandwidth demand and we propose an exact method for solving the optimization problem. Simulations with real data are also presented.

[1]  János Levendovszky,et al.  Developing Novel Statistical Bandwidths for Communication Networks with Incomplete Information , 2005, WEA.

[2]  Matthew Roughan,et al.  Traffic Matrix Reloaded: Impact of Routing Changes , 2005, PAM.

[3]  A. Brøndsted An Introduction to Convex Polytopes , 1982 .

[4]  Ariel Orda,et al.  QoS routing in networks with inaccurate information: theory and algorithms , 1999, TNET.

[5]  Adrian Farrel,et al.  Network Working Group A. Farrel Request for Comments: 4726 Old Dog Consulting Category: Informational a Framework for Inter-domain Multiprotocol Label Switching Traffic Engineering , 2022 .

[6]  Jean-Louis Rougier,et al.  Robust regression for minimum-delay load-balancing , 2009, 2009 21st International Teletraffic Congress.

[7]  Jordi Domingo-Pascual,et al.  QoS routing algorithms under inaccurate routing for bandwidth constrained applications , 2003, IEEE International Conference on Communications, 2003. ICC '03..

[8]  Olivier Bonaventure,et al.  Path Selection Techniques to Establish Constrained Interdomain MPLS LSPs , 2006, Networking.

[9]  Albert G. Greenberg,et al.  A flexible model for resource management in virtual private networks , 1999, SIGCOMM '99.

[10]  Ariel Orda,et al.  ETICS: QoS-enabled interconnection for Future Internet services , 2010 .

[11]  Gilles Bertrand,et al.  Ad-hoc Recursive PCE Based Inter-domain Path Computation (ARPC) Methods , 2008 .

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

[13]  Pedro Casas,et al.  Optimal volume anomaly detection and isolation in large-scale IP networks using coarse-grained measurements , 2010, Comput. Networks.

[14]  P. Varaiya,et al.  Ellipsoidal Toolbox (ET) , 2006, Proceedings of the 45th IEEE Conference on Decision and Control.

[15]  Mikael Johansson,et al.  Data-driven traffic engineering: techniques, experiences and challenges , 2006, 2006 3rd International Conference on Broadband Communications, Networks and Systems.

[16]  Klaus Jansen,et al.  Experimental and Efficient Algorithms , 2003, Lecture Notes in Computer Science.

[17]  Richard Douville,et al.  Design and correctness proof of a security protocol for mobile banking , 2009 .

[18]  Colin N. Jones,et al.  Polyhedral Tools for Control , 2005 .

[19]  Jean-Philippe Vasseur,et al.  MPLS Inter-Autonomous System (AS) Traffic Engineering (TE) Requirements , 2005, RFC.

[20]  Vladimir Gurvich,et al.  Generating All Vertices of a Polyhedron Is Hard , 2006, SODA '06.