2019
DOI: 10.1186/s13638-019-1617-8
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Ingredients to enhance the performance of two-stage TCAM-based packet classifiers in internet of things: greedy layering, bit auctioning and range encoding

Abstract: Using packet classification algorithms in network equipment increases packet processing speed in Internet of Things (IoT). In the hardware implementation of these algorithms, ternary content-addressable memories (TCAMs) are often preferred to other implementations. As a common approach, TCAMs are used for the parallel search to match packet header information with the rules of the classifier. In two-stage architectures of hardware-based packet classifiers, first the decision tree is created, and then the rules… Show more

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Cited by 4 publications
(1 citation statement)
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“…TCAMs are expensive and have a very high level of power consumption. This is why increasing FIGURE 2 The structure of OpenFlow switch the size of flow tables is costly and is likely to increase power consumption [9][10][11]. In a flow table, the information of each incoming flow packet is compared with the entries in the table.…”
Section: Introductionmentioning
confidence: 99%
“…TCAMs are expensive and have a very high level of power consumption. This is why increasing FIGURE 2 The structure of OpenFlow switch the size of flow tables is costly and is likely to increase power consumption [9][10][11]. In a flow table, the information of each incoming flow packet is compared with the entries in the table.…”
Section: Introductionmentioning
confidence: 99%