BRICK: a novel exact active statistics counter architecture

Authors:
Nan Hua;Jun Xu;Bill Lin;Haiquan Zhao
Affiliations:
College of Computing, Georgia Institute of Technology, Atlanta, GA;College of Computing, Georgia Institute of Technology, Atlanta, GA;University of California, San Diego, San Diego, CA;Microsoft, Redmond, WA and College of Computing, Georgia Institute of Technology, Atlanta, GA
Venue:
IEEE/ACM Transactions on Networking (TON)
Year:
2011

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Abstract

In this paper, we present an exact active statistics counter architecture called Bucketized Rank Indexed Counters (BRICK) that can efficiently store per-flow variable-width statistics counters entirely in SRAM while supporting both fast updates and lookups (e.g., 40-Gb/s line rates). BRICK exploits statistical multiplexing by randomly bundling counters into small fixed-size buckets and supports dynamic sizing of counters by employing an innovative indexing scheme called rank indexing. Experiments with Internet traces show that our solution can indeed maintain large arrays of exact active statistics counters with moderate amounts of SRAM.