In our upcoming NSDI 2018 paper, we focus on how to realize high performance NFV service chains at the true speed of the underlying hardware. We solve this challenging problem by exploiting the synergy between available network resources (i.e., programmable switches and network cards) and commodity servers, while eliminating inter-core communication among the service chain components. We demonstrate, via 40-Gbps and 100-Gbps experiments, that our approach achieves: (i) 2.75-6.5x better efficiency, (ii) up to 4.7x lower latency, and (iii) up to 7.8x higher throughput than the state of the art.

Credits

This is a joint work with Georgios P. Katsikas (RISE SICS Network Intelligence group), Tom Barbette (University of Liege), Dejan Kostic (KTH Royal Institute of Technology), Rebecca Steinert (RISE SICS Network Intelligence group), and Gerald Q. Maguire Jr. (KTH Royal Institute of Technology). The full abstract is as follows:

Abstract

In this paper we present Metron, a Network Functions Virtualization (NFV) platform that achieves high resource utilization by jointly exploiting the underlying network and commodity servers’ resources. This synergy allows Metron to: (i) offload part of the packet processing logic to the network, (ii) use smart tagging to setup and exploit the affinity of traffic classes, and (iii) use tag-based hardware dispatching to carry out the remaining packet processing at the speed of the servers’ fastest cache(s), with zero inter-core communication. Metron also introduces a novel resource allocation scheme that minimizes the resource allocation overhead for large-scale NFV deployments. With commodity hardware assistance, Metron deeply inspects traffic at 40 Gbps and realizes stateful network functions at the speed of a 100 GbE network card on a single server. Metron has 2.75-6.5x better efficiency than OpenBox, a state of the art NFV system, while ensuring key requirements such as elasticity, fine-grained load balancing, and flexible traffic steering.

In our NOMS 2018 paper, we focus on how to deploy distributed controllers for programmable networks. To solve this challenging problem, we propose an approach that can automatically decide the number of controllers, their locations and control regions, and is guaranteed to find a non-congestion controller deployment plan fulfilling requirements such as reliability and bandwidth. We demonstrate, via experiments, that our approach allows for finding close to optimal solutions under varying conditions and achieves 20.1%-50.1% bandwidth usage reduction when compared with the state of the art.

Credit

This is joint work with Shaoteng Liu,  Rebecca Steinert  and Dejan Kostic.  The work was done at RISE SICS Network Intelligence group. The full abstract is as follows:

Abstract

For large-scale programmable networks, flexible deployment of distributed control planes is essential for service availability and performance. However, existing approaches only focus on placing controllers whereas the consequent control traffic is often ignored. In this paper, we propose a black-box optimization framework offering the additional steps for quantifying the effect of the consequent control traffic when deploying a distributed control plane. Evaluating different implementations of the framework over real-world topologies shows that close to optimal solutions can be achieved. Moreover, experiments indicate that running a method for controller placement without considering the control traffic, cause excessive bandwidth usage (worst cases varying between 20.1%-50.1% more) and congestion, compared to our approach.

In our ICC 2018 paper, we focus on how to maintain stable network control services during intermittent network partitioning situations. To solve this challenging problem, we propose a new leader election algorithm that can perform leader election and node clustering in line with tunable optimization objectives related to group stability, size and merging cost. We demonstrate, via experiments, that with the same stability requirement our approach achieves: (i) upto 2x larger group size and (ii) up to 12x lower merging costs than existing approaches.

Credit

This is joint work with Shaoteng Liu,  Rebecca Steinert  and Dejan Kostic.  The work was done at RISE SICS Network Intelligence group. The full abstract is as follows:

Abstract

We propose a novel distributed leader election algorithm to deal with the controller and control service availability issues in programmable networks, such as Software Defined Networks (SDN) or programmable Radio Access Network (RAN). Our approach can deal with a wide range of network failures, especially intermittent network partitions, where splitting and merging of a network repeatedly occur.

In contrast to traditional leader election algorithms that mainly focus on the (eventual) consensus on one leader, the proposed algorithm aims at optimizing control service availability, stability and reducing the controller state synchronization effort during intermittent network partitioning situations. To this end, we design a new framework that enables dynamic leader election based on real-time estimates acquired from statistical monitoring. With this framework, the proposed leader election algorithm has the capability of being flexibly configured to achieve different optimization objectives, while adapting to various failure patterns. Compared with two existing algorithms, our approach can significantly reduce the synchronization overhead (up to 12x) due to controller state updates, and maintain up to twice more nodes under a controller.