SPONGE: Software-Defined Traffic Engineering to Absorb Influx of Network Traffic

Benoît Henry (1) , Shihabur Rahman Chowdhury (2) , Abdelkader Lahmadi (3) , Romain Azaïs (4) , Jérôme François (3) , Raouf Boutaba (2)

1 IMT Lille Douai - Ecole nationale supérieure Mines-Télécom Lille Douai
2 CS - Cheriton School of Computer Science [Waterloo]
3 RESIST - Resilience and Elasticity for Security and ScalabiliTy of dynamic networked systems
4 MOSAIC - Simulation et Analyse de la morphogenèse in siliCo

Existing shortest path-based routing in wide area networks or equal cost multi-path routing in data center networks do not consider the load on the links while taking routing decisions. As a consequence, an influx of network traffic stemming from events such as distributed link flooding attacks and data shuffle during large scale analytics can congest network links despite the network having sufficient capacity on alternate paths to absorb the traffic. This can have several negative consequences, service unavailability, delayed flow completion, packet losses, among others. In this regard, we propose SPONGE, a traffic engineering mechanism for handling sudden influx of network traffic. SPONGE models the network as a stochastic process, takes the switch queue occupancy and traffic rate as inputs, and leverages the multiple available paths in the network to route traffic in a way that minimizes the overall packet loss in the network. We demonstrate the practicality of SPONGE through an OpenFlow based implementation, where we periodically and pro-actively reroute network traffic to the routes computed by SPONGE. Mininet emulations using real network topologies show that SPONGE is capable of reducing packet drops by 20% on average even when the network is highly loaded because of an ongoing link flooding attack.

Domaines: Réseaux et télécommunications [cs.NI]

Benoît Henry, Shihabur Rahman Chowdhury, Abdelkader Lahmadi, Romain Azaïs, Jérôme François, et al.. SPONGE: Software-Defined Traffic Engineering to Absorb Influx of Network Traffic. LCN 2019 - 44th IEEE Conference on Local Computer Networks, Oct 2019, Osnabrück, Germany. ⟨hal-02403616⟩