Author
Listed:
- Chenglong Li
(Computer College, National University of Defense Technology, Changsha 410073, China)
- Tao Li
(Computer College, National University of Defense Technology, Changsha 410073, China)
- Junnan Li
(Computer College, National University of Defense Technology, Changsha 410073, China)
- Zilin Shi
(Computer College, National University of Defense Technology, Changsha 410073, China)
- Baosheng Wang
(Computer College, National University of Defense Technology, Changsha 410073, China)
Abstract
Field Programmable Gate Array (FPGA) is widely used in real-time network processing such as Software-Defined Networking (SDN) switch due to high performance and programmability. Bit-Vector (BV)-based approaches can implement high-performance multi-field packet classification, on FPGA, which is the core function of the SDN switch. However, the SDN switch requires not only high performance but also low update latency to avoid controller failure. Unfortunately, the update latency of BV-based approaches is inversely proportional to the number of rules, which means can hardly support the SDN switch effectively. It is reasonable to split the ruleset into sub-rulesets that can be performed in parallel, thereby reducing update latency. We thus present SplitBV for the efficient update by using several distinguishable exact-bits to split the ruleset. SplitBV consists of a constrained recursive algorithm for selecting the bit positions that can minimize the latency and a hybrid lookup pipeline. It can achieve a significant reduction in update latency with negligible memory growth and comparable high performance. We implement SplitBV and evaluate its performance by simulation and FPGA prototype. Experimental results show that our approach can reduce 73% and 36% update latency on average for synthetic 5-tuple rules and OpenFlow rules respectively.
Suggested Citation
Chenglong Li & Tao Li & Junnan Li & Zilin Shi & Baosheng Wang, 2020.
"Enabling Packet Classification with Low Update Latency for SDN Switch on FPGA,"
Sustainability, MDPI, vol. 12(8), pages 1-16, April.
Handle:
RePEc:gam:jsusta:v:12:y:2020:i:8:p:3068-:d:344301
Download full text from publisher
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:12:y:2020:i:8:p:3068-:d:344301. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.