Traffic Matrix (TM) assessment is a key issue for optimizing network management costs and quality of service. This paper presents a method to measure the intensity of ingress-egress traffic flows on an ISP network that overcomes the limits of the classical measurement based approaches. The proposed algorithm, called SEgment Routing PErturbatioN Traffic (SERPENT), uses a routing perturbation approach enabled by the Segment Routing (SR) paradigm: the paths of a subset of flows are changed so that their intensities can be determined measuring the variation of the load of the network links. The TM is measured in successive steps, called snapshots, in which sets of flows are progressively re-routed and measured, under a maximum link utilization constraint. We state an ILP optimization problem to determine the flows to be re-routed in one snapshot. SERPENT is an heuristic offering an efficient solution to the stated ILP. Results show that SERPENT assesses the intensity of more than 80% of flows even when the network is highly stressed, while reducing the configuration cost with respect to classical approaches. Moreover, when used in conjunction with an estimation algorithm, SERPENT allows to reduce the estimation error by more than 50% with less than 5 snapshots.

Routing perturbation for traffic matrix evaluation in a segment routing network

Cianfrani, Antonio;
2018-01-01

Abstract

Traffic Matrix (TM) assessment is a key issue for optimizing network management costs and quality of service. This paper presents a method to measure the intensity of ingress-egress traffic flows on an ISP network that overcomes the limits of the classical measurement based approaches. The proposed algorithm, called SEgment Routing PErturbatioN Traffic (SERPENT), uses a routing perturbation approach enabled by the Segment Routing (SR) paradigm: the paths of a subset of flows are changed so that their intensities can be determined measuring the variation of the load of the network links. The TM is measured in successive steps, called snapshots, in which sets of flows are progressively re-routed and measured, under a maximum link utilization constraint. We state an ILP optimization problem to determine the flows to be re-routed in one snapshot. SERPENT is an heuristic offering an efficient solution to the stated ILP. Results show that SERPENT assesses the intensity of more than 80% of flows even when the network is highly stressed, while reducing the configuration cost with respect to classical approaches. Moreover, when used in conjunction with an estimation algorithm, SERPENT allows to reduce the estimation error by more than 50% with less than 5 snapshots.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11695/130965
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