DocumentCode
165922
Title
An optimized RFC algorithm with incremental update
Author
Trivedi, Uday ; Jangir, Mohan Lal
Author_Institution
Samsung R&D Inst. India, Bangalore, India
fYear
2014
fDate
24-27 Sept. 2014
Firstpage
120
Lastpage
127
Abstract
RFC (Recursive Flow Classification) is one of the best packet classification algorithms. However, RFC has moderate to prohibitive high preprocessing time for rule-sets having more than 10K rules. RFC does not provide incremental update. Due to these essential missing features, RFC is used in limited scenarios. This paper attempts to add these essential features in RFC. Our algorithm uses various memory and processing optimizations to speed up RFC preprocessing phase. We provide an algorithm to compute only those CBM (Class Bit Map) intersections for which corresponding value pairs are found in rules. We optimize CBM intersection by using ABV algorithm and min-max rule information. We also propose an optimized algorithm to manage real time incremental updates in RFC. The algorithm modifies only required parts of RFC tables and makes sure that the updated tables have information in correct order. For incremental update, moderate amount of extra memory is required. We tested our algorithm for preprocessing time and incremental update feature. The results indicate that we get moderate improvement in preprocessing time with real time incremental updates in our modified RFC.
Keywords
minimax techniques; packet switching; pattern classification; ABV algorithm; CBM intersection; RFC preprocessing phase; extra memory; incremental update feature; min-max rule information; optimized RFC algorithm; optimized algorithm; packet classification algorithms; real time incremental updates; recursive flow classification; Indexes; Packet classification; RFC with Incremental update; Recursive Flow Classification;
fLanguage
English
Publisher
ieee
Conference_Titel
Advances in Computing, Communications and Informatics (ICACCI, 2014 International Conference on
Conference_Location
New Delhi
Print_ISBN
978-1-4799-3078-4
Type
conf
DOI
10.1109/ICACCI.2014.6968240
Filename
6968240
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