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Accelerating VNF-based Deep Packet Inspection with the use of GPUs
Fed Univ Para, Technol Inst, Belem, PA, Brazil..
KTH, School of Electrical Engineering and Computer Science (EECS), Communication Systems, CoS, Optical Network Laboratory (ON Lab).ORCID iD: 0000-0001-7501-5547
Fuji Elect Co Ltd, Corp R&D Headquarters, 1 Fuji Machi, Hino, Tokyo, Japan..
Fed Univ Para, Technol Inst, Belem, PA, Brazil..
2018 (English)In: 2018 20TH ANNIVERSARY INTERNATIONAL CONFERENCE ON TRANSPARENT OPTICAL NETWORKS (ICTON) / [ed] Jaworski, M Marciniak, M, Institute of Electrical and Electronics Engineers (IEEE), 2018, article id 8473638Conference paper, Published paper (Refereed)
Abstract [en]

Network Function Virtualization (NFV) replaces the hardware that supports packet processing in network operation from specific-by general-purpose ones, reducing costs and bringing more flexibility and agility to the network operation. However, this shift can cause performance losses due to the non-optimal packet processing capabilities of the general-purpose hardware. Moreover, supporting the line rate of optical network channels with Virtualized Network Functions (VNFs) is a challenging task. This work analyzes the benefits of using Graphics Processing Units (GPUs) to support the execution of a Deep Packet Inspection (DPI) VNF towards supporting the line rate of an optical channel. The use of GPUs in VNFs has a great potential to increase throughput, but the delay incurred might be an issue for some functions. Our simulation was performed using an Intrusion Detection Systems (IDS) which performs DPI deployed as a VNF under real-world traffic scaled to high bit rates. Results show that the packet processing speedup achieved by using GPUs can reach up to 19 times, at the expense of a higher packet delay.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2018. article id 8473638
Series
International Conference on Transparent Optical Networks-ICTON, ISSN 2162-7339
Keywords [en]
Network Function Virtualization, Deep Packet Inspection, Graphics Processing Unit, Intrusion Detection System
National Category
Communication Systems
Identifiers
URN: urn:nbn:se:kth:diva-249909DOI: 10.1109/ICTON.2018.8473638ISI: 000462559300062Scopus ID: 2-s2.0-85055558488ISBN: 978-1-5386-6605-0 (print)OAI: oai:DiVA.org:kth-249909DiVA, id: diva2:1313134
Conference
20th International Conference on Transparent Optical Networks (ICTON), JUL 01-05, 2018, Univ Politehnica Bucharest, Cent Lib, Bucharest, ROMANIA
Note

QC 20190502

Available from: 2019-05-02 Created: 2019-05-02 Last updated: 2019-05-02Bibliographically approved

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Natalino, Carlos

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