1,006 research outputs found

    SDN management layer: design requirements and future direction

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    Computer networks are becoming more and more complex and difficult to manage. The research community has been expending a lot of efforts to come up with a general management paradigm that is able to hide the details of the physical infrastructure and enable flexible network management. Software Defined Networking (SDN) is such a paradigm that simplifies network management and enables network innovations. In this survey paper, by reviewing existing SDN management layers (platforms), we identify the general common management architecture for SDN networks, and further identify the design requirements of the management layer that is at the core of the architecture. We also point out open issues and weaknesses of existing SDN management layers. We conclude with a promising future direction for improving the SDN management layer.This work is supported in part by the National Science Foundation (NSF grant CNS-0963974)

    Programming Protocol-Independent Packet Processors

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    P4 is a high-level language for programming protocol-independent packet processors. P4 works in conjunction with SDN control protocols like OpenFlow. In its current form, OpenFlow explicitly specifies protocol headers on which it operates. This set has grown from 12 to 41 fields in a few years, increasing the complexity of the specification while still not providing the flexibility to add new headers. In this paper we propose P4 as a strawman proposal for how OpenFlow should evolve in the future. We have three goals: (1) Reconfigurability in the field: Programmers should be able to change the way switches process packets once they are deployed. (2) Protocol independence: Switches should not be tied to any specific network protocols. (3) Target independence: Programmers should be able to describe packet-processing functionality independently of the specifics of the underlying hardware. As an example, we describe how to use P4 to configure a switch to add a new hierarchical label

    Dataplane Specialization for High-performance OpenFlow Software Switching

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    OpenFlow is an amazingly expressive dataplane program- ming language, but this expressiveness comes at a severe performance price as switches must do excessive packet clas- sification in the fast path. The prevalent OpenFlow software switch architecture is therefore built on flow caching, but this imposes intricate limitations on the workloads that can be supported efficiently and may even open the door to mali- cious cache overflow attacks. In this paper we argue that in- stead of enforcing the same universal flow cache semantics to all OpenFlow applications and optimize for the common case, a switch should rather automatically specialize its dat- aplane piecemeal with respect to the configured workload. We introduce ES WITCH , a novel switch architecture that uses on-the-fly template-based code generation to compile any OpenFlow pipeline into efficient machine code, which can then be readily used as fast path. We present a proof- of-concept prototype and we demonstrate on illustrative use cases that ES WITCH yields a simpler architecture, superior packet processing speed, improved latency and CPU scala- bility, and predictable performance. Our prototype can eas- ily scale beyond 100 Gbps on a single Intel blade even with complex OpenFlow pipelines

    Verifiably-safe software-defined networks for CPS

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    Next generation cyber-physical systems (CPS) are expected to be deployed in domains which require scalability as well as performance under dynamic conditions. This scale and dynamicity will require that CPS communication networks be programmatic (i.e., not requiring manual intervention at any stage), but still maintain iron-clad safety guarantees. Software-defined networking standards like OpenFlow provide a means for scalably building tailor-made network architectures, but there is no guarantee that these systems are safe, correct, or secure. In this work we propose a methodology and accompanying tools for specifying and modeling distributed systems such that existing formal verification techniques can be transparently used to analyze critical requirements and properties prior to system implementation. We demonstrate this methodology by iteratively modeling and verifying an OpenFlow learning switch network with respect to network correctness, network convergence, and mobility-related properties. We posit that a design strategy based on the complementary pairing of software-defined networking and formal verification would enable the CPS community to build next-generation systems without sacrificing the safety and reliability that these systems must deliver
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