.png){kind=icon}
.png){kind=icon}
Return
CoNFV: A Heterogeneous Platform for Scalable Network Function Virtualization
.png){kind=icon}
OA
AI
DOI：10.1145/3409113.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
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.
Keywords:
Network function virtualization
coordinator
heterogeneous middleboxes
FPGA
performance-aware VNF deployment
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
2.8
Papers:
597
Citations:
810