Accelerating VNF-based Deep Packet Inspection with the use of GPUs

QC 20190502
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.

Natalino, Carlos,Dr.1987-KTH,Optical Network Laboratory (ON Lab)(Swepub:kth)u1qrfr5f (författare)
Santana, Adamo L.Fuji Elect Co Ltd, Corp R&D Headquarters, 1 Fuji Machi, Hino, Tokyo, Japan. (författare)
Cardoso, Diego L.Fed Univ Para, Technol Inst, Belem, PA, Brazil. (författare)
Fed Univ Para, Technol Inst, Belem, PA, Brazil.Optical Network Laboratory (ON Lab) (creator_code:org_t)

Ingår i:2018 20TH ANNIVERSARY INTERNATIONAL CONFERENCE ON TRANSPARENT OPTICAL NETWORKS (ICTON): Institute of Electrical and Electronics Engineers (IEEE)9781538666050

Av författaren/redakt...: Araujo, Igor M.; Natalino, Carlos ...; Santana, Adamo L ...; Cardoso, Diego L ...

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