CoNFV: A Heterogeneous Platform for Scalable Network Function Virtualization

Network function virtualization (NFV) is a powerful networking approach that leverages computing resources to perform a time-varying set of network processing functions. Although microprocessors can be used for this purpose, their performance limitations and lack of specialization present implementa...

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Veröffentlicht in:ACM transactions on reconfigurable technology and systems 2020-12, Vol.14 (1), p.1-29
Hauptverfasser: Zhang, Xuzhi, Shao, Xiaozhe, Provelengios, George, Dumpala, Naveen Kumar, Gao, Lixin, Tessier, Russell
Format: Artikel
Sprache:eng
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Zusammenfassung:Network function virtualization (NFV) is a powerful networking approach that leverages computing resources to perform a time-varying set of network processing functions. Although microprocessors can be used for this purpose, their performance limitations and lack of specialization present implementation challenges. In this article, we describe a new heterogeneous hardware-software NFV platform called CoNFV that provides scalability and programmability while supporting significant hardware-level parallelism and reconfiguration. Our computing platform takes advantage of both field-programmable gate arrays (FPGAs) and microprocessors to implement numerous virtual network functions (VNF) that can be dynamically customized to specific network flow needs. The most distinctive feature of our system is the use of global network state to coordinate NFV operations. Traffic management and hardware reconfiguration functions are performed by a global coordinator that allows for the rapid sharing of network function states and continuous evaluation of network function needs. With the help of state sharing mechanism offered by the coordinator, customer-defined VNF instances can be easily migrated between heterogeneous middleboxes as the network environment changes. A resource allocation and scheduling algorithm dynamically assesses resource deployments as network flows and conditions are updated. We show that our deployment algorithm can successfully reallocate FPGA and microprocessor resources in a fraction of a second in response to changes in network flow capacity and network security threats including intrusion.
ISSN:1936-7406
1936-7414
DOI:10.1145/3409113