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Optimization of Network Traffic Flow
"... In modern backbone networks with heterogeneous traffic, providing connectivity is taken for granted. The MPLS technology is a de-facto standard in modern backbone networks because of the applications it enables, in particular L2/L3 VPNs and traffic engineering. This paper deals with traffic engineer ..."
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In modern backbone networks with heterogeneous traffic, providing connectivity is taken for granted. The MPLS technology is a de-facto standard in modern backbone networks because of the applications it enables, in particular L2/L3 VPNs and traffic engineering. This paper deals with traffic engineering in MPLS backbone networks. We propose a method of gathering network performance parameters and a model for optimizing the flow of network traffic based on class-based TE tunnel selection (n-CUBE). We implement this model as part of a traffic
Maximum Delay Computation for Interdomain Path Selection
"... One important problem when deploying interdomain path selec-tion is advertising metrics that hold for a long period of time. In this paper we propose a method to aid interdomain path selection mech-anisms in that sense. We present a means of computing a bound on the end-to-end delay of traversing a ..."
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One important problem when deploying interdomain path selec-tion is advertising metrics that hold for a long period of time. In this paper we propose a method to aid interdomain path selection mech-anisms in that sense. We present a means of computing a bound on the end-to-end delay of traversing a domain considering that the traf-fic varies within a given uncertainty set. This provides a robust and a verifiable quality of service value for traversing the Autonomous Sys-tem (AS), without revealing confidential information. Consequently, the bound can be safely conceived as a metric to be announced by each AS 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 and a numerical approxi-mation method for computing it, neither of which rely on a complex monitoring infrastructure. Simulations with real data that illustrate the problem and validate our results are also presented.
