Studio e realizzazione di un generatore di traffico ad alte prestazioni su piattaforma Network Processor

In questa tesi vengono analizzate le precedenti soluzioni adottate per la realizzazione di un generatore di traffico IP su piattaforma Network Processor e viene proposta una nuova soluzione altamente flessibile

Fast Packet Processing on High Performance Architectures

The rapid growth of Internet and the fast emergence of new network applications have brought great challenges and complex issues in deploying high-speed and QoS guaranteed IP network. For this reason packet classication and network intrusion detection have assumed a key role in modern communication networks in order to provide Qos and security. In this thesis we describe a number of the most advanced solutions to these tasks. We introduce NetFPGA and Network Processors as reference platforms both for the design and the implementation of the solutions and algorithms described in this thesis. The rise in links capacity reduces the time available to network devices for packet processing. For this reason, we show different solutions which, either by heuristic and randomization or by smart construction of state machine, allow IP lookup, packet classification and deep packet inspection to be fast in real devices based on high speed platforms such as NetFPGA or Network Processors

Faster Control Plane Experimentation with Horse

Simulation and emulation are popular approaches for experimentation in Computer Networks. However, due to their respective inherent drawbacks, existing solutions cannot perform both fast and realistic control plane experiments. To close this gap, we introduce Horse. Horse is a hybrid solution with an emulated control plane, for realism, and simulated data plane, for speed. Our decoupling of the control and data plane allows us to speed up the experiments without sacrificing control plane realism

State-Compute Replication: Parallelizing High-Speed Stateful Packet Processing

With the slowdown of Moore's law, CPU-oriented packet processing in software will be significantly outpaced by emerging line speeds of network interface cards (NICs). Single-core packet-processing throughput has saturated. We consider the problem of high-speed packet processing with multiple CPU cores. The key challenge is state--memory that multiple packets must read and update. The prevailing method to scale throughput with multiple cores involves state sharding, processing all packets that update the same state, i.e., flow, at the same core. However, given the heavy-tailed nature of realistic flow size distributions, this method will be untenable in the near future, since total throughput is severely limited by single core performance. This paper introduces state-compute replication, a principle to scale the throughput of a single stateful flow across multiple cores using replication. Our design leverages a packet history sequencer running on a NIC or top-of-the-rack switch to enable multiple cores to update state without explicit synchronization. Our experiments with realistic data center and wide-area Internet traces shows that state-compute replication can scale total packet-processing throughput linearly with cores, deterministically and independent of flow size distributions, across a range of realistic packet-processing programs

Datacenter in a box: Test your sdn cloud-datacenter controller at home

Abstract-In the last years, the widespread of Cloud computing as the main paradigm to deliver a large plethora of virtualized services significantly increased the complexity of Datacenters management and raised new performance issues for the intra-Datacenter network. Providing heterogeneous services and satisfying users' experience is really challenging for Cloud service providers, since system (IT resources) and network administration functions are definitely separated. As the Software Defined Networking (SDN) approach seems to be a promising way to address innovation in Datacenters, the paper presents a new framework that allows to develop and test new OpenFlow-based controllers for Cloud Datacenters. More specifically, our framework enhances both Mininet (a well-known SDN emulator) and POX (a network controller written in python), with all the extensions necessary to experiment novel control and management strategies of IT and network resources

ENDEAVOUR: A Scalable SDN Architecture For Real-World IXPs.

Innovation in interdomain routing has remained stagnant for over a decade. Recently, IXPs have emerged as economically-advantageous interconnection points for reducing path latencies and exchanging ever increasing traffic volumes among, possibly, hundreds of networks. Given their far-reaching implications on interdomain routing, IXPs are the ideal place to foster network innovation and extend the benefits of SDN to the interdomain level. In this paper, we present, evaluate, and demonstrate EN- DEAVOUR, an SDN platform for IXPs. ENDEAVOUR can be deployed on a multi-hop IXP fabric, supports a large number of use cases, and is highly-scalable while avoiding broadcast storms. Our evaluation with real data from one of the largest IXPs, demonstrates the benefits and scalability of our solution: ENDEAVOUR requires around 70% fewer rules than alternative SDN solutions thanks to our rule partitioning mechanism. In addition, by providing an open source solution, we invite ev- eryone from the community to experiment (and improve) our implementation as well as adapt it to new use cases.European Union’s Horizon 2020 research and innovation programme under the ENDEAVOUR project (grant agreement 644960)