NDLI: Efficient memory utilization on network processors for deep packet inspection

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Efficient memory utilization on network processors for deep packet inspection

Content Provider	IEEE Xplore Digital Library
Author	Piyachon, P. Yan Luo
Copyright Year	2006
Description	Author affiliation: Dept. of Electr. & Comput. Eng., Univ. of Massachusetts Lowell Lowell, Lowell, MA (Piyachon, P.; Yan Luo)
Abstract	Deep Packet Inspection (DPI) refers to examining both packet header and payload to look for predefined patterns, which is essential for network security, intrusion detection and content-aware switch etc. The increasing line speed and expanding pattern sets make DPI a challenging task. Network Processors (NPs) are chosen to perform DPI due to their packet processing performance and programmability. In this paper, we focus on achieving high performance DPI through exploitation of NP's on-chip resources (particularly memory) and inherent parallel processing capability. We study the parallelism in classical DPI algorithms and construct a memory model for different parallel matching methods. Based on the model, we find the optimal organization of state machines that requires minimal on-chip memory space and guides us to high performance NP architectures for DPI. The performance evaluation experiments show that our method can reduce the memory usage by up to 86%. With an Intel IXP28xx NP simulator, we observe that the estimated DPI throughput reaches up to 5 Gbps.
Starting Page	71
Ending Page	80
File Size	329755
Page Count	10
File Format	PDF
ISBN	9781595935809
DOI	10.1145/1185347.1185358
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-12-03
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Association for Computing Machinery, Inc. (ACM)
Subject Keyword	Program processors pattern matching deep packet inspection Memory management Parallel processing Data structures System-on-a-chip parallel processing Pattern matching network processor Payloads
Content Type	Text
Resource Type	Article

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