NDLI: Packet classification using coarse-grained tuple spaces

Please wait, while we are loading the content...

An effective network processor design framework - using multi-objective evolutionary algorithms and object oriented techniques to optimise the intel IXP1200 network processor

A methodology for evaluating runtime support in network processors

High-throughput sketch update on a low-power stream processor

Symerton--using virtualization to accelerate packet processing

Sequence-preserving adaptive load balancers

Localized asynchronous packet scheduling for buffered crossbar switches

Scalable network-based buffer overflow attack detection

WormTerminator

Packet pre-filtering for network intrusion detection

2005 Symposium on Architectures for Networking and Communications Systems (ANCS)

Packet classification using coarse-grained tuple spaces

Content Provider	IEEE Xplore Digital Library
Author	Haoyu Song Turner, J. Dharmapurikar, S.
Copyright Year	2006
Description	Author affiliation: Washington Univ., St. Louis, MO (Haoyu Song; Turner, J.; Dharmapurikar, S.)
Abstract	While the problem of high performance packet classification has received a great deal of attention in recent years, the research community has yet to develop algorithmic methods that can overcome the drawbacks of TCAM-based solutions. This paper introduces a hybrid approach, which partitions the filter set into subsets that are easy to search efficiently. The partitioning strategy groups filters that are close to one another in tuple space [10], which makes it possible to use information from single field lookups to limit the number of subsets that must be searched. We can tradeoff running time against space consumption by adjusting the coarseness of the tuple space partition. We find that for two-dimensional filter sets, the method finds the best- matching filter with just four hash probes while limiting the memory space expansion factor to about 2. We also introduce a novel method for Longest Prefix Matching (LPM), which we use as a component of the overall packet classification algorithm. Our LPM method uses a small amount of on-chip memory to speedup the search of an off-chip data structure, but uses significantly less on-chip memory than earlier methods based on Bloom filters.
Starting Page	41
Ending Page	50
File Size	302688
Page Count	10
File Format	PDF
ISBN	9781595935809
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	Matched filters packet classification Memory management Filtering algorithms Classification algorithms Table lookup IP networks System-on-a-chip longest prefix matching
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Packet classification using coarse-grained tuple spaces

An improvement of IP address lookup based on rule filter analysis

An enhanced bloom filter for longest prefix matching

Packet Classification Using Coarse-grained Tuple Spaces ABSTRACT

A hierarchical high-throughput and low power architecture for longest prefix matching for packet forwarding

SRAM based longest prefix matching approach for multigigabit IP processing

Fast packet classification using bloom filters

Longest prefix matching using bloom filters

A memory efficient IPv6 lookup engine on FPGA

Packet classification using coarse-grained tuple spaces

Similar Documents

Packet classification using coarse-grained tuple spaces

An improvement of IP address lookup based on rule filter analysis

An enhanced bloom filter for longest prefix matching

Packet Classification Using Coarse-grained Tuple Spaces ABSTRACT

A hierarchical high-throughput and low power architecture for longest prefix matching for packet forwarding

SRAM based longest prefix matching approach for multigigabit IP processing

Fast packet classification using bloom filters

Longest prefix matching using bloom filters

A memory efficient IPv6 lookup engine on FPGA

Packet classification using coarse-grained tuple spaces