Packet Classification with Limited Memory Resources
Citations
8 citations
2 citations
Cites methods from "Packet Classification with Limited ..."
...The papers [6], [7] investigate an approach based on the decomposition of the classification by many fields into several classifications by one field....
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1 citations
Cites background from "Packet Classification with Limited ..."
...This idea was pushed further to build scalable architecture through memory duplication in [18]....
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...The architecture was shown to be scalable even to higher throughputs [18], but only by using multiple copies of the memories....
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References
822 citations
Additional excerpts
...[13] proposed using recursive flow classification (RFC)....
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741 citations
"Packet Classification with Limited ..." refers background in this paper
...[9], is a practical implementation that leverages the fact that rule updates are infrequent compared to search operations....
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625 citations
"Packet Classification with Limited ..." refers background in this paper
...Several of the possible approaches to support multiple dimensions are described in [12]....
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572 citations
"Packet Classification with Limited ..." refers background or methods in this paper
...First algorithms and hardware architectures HiCuts [3] and HyperCuts [2] use the geometric representation of the classification problem, where packet header fields are dimensions and the classification is the searching in the n-dimensional space....
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...They have observed that HyperCuts and similar decision-tree-based algorithms do not efficiently deal with rules that have too much overlap with each other....
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...HiCuts [3] and HyperCuts [2] are examples of such algorithms....
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...A way to increase throughput of HyperCuts was introduced by Luo et al. [14]....
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...Kennedy et al. [15] implemented simplified version of HyperCuts algorithm with the goal of reducing power consumption and increase power efficiency....
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478 citations