Finding Nonequivalent Classifiers in Boolean Space to Reduce TCAM Usage


Packet classification is one in all the foremost challenges today in designing high-speed routers and firewalls, because it involves refined multi-dimensional looking out. Ternary content addressable memory (TCAM) has been widely used to implement packet classification, due to its parallel search capability and constant processing speed. However, TCAMs have limitations of high cost and high power consumption, which ignite the will to scale back TCAM usage. Recently, many works have been presented on this subject because of 2 opportunities. One is the well-known vary growth problem for packet classifiers to be stored in TCAM entries. The other is that there often exists redundancy among rules. During this paper, we have a tendency to propose a unique technique called Block Permutation (BP) to compress the packet classification rules stored in TCAMs. In contrast to previous schemes that compress classifiers by converting the initial classifiers to semantically equivalent classifiers, the BP technique innovatively finds semantically nonequivalent classifiers to realize compression by performing block-primarily based permutations on the foundations represented in Boolean House. We tend to have developed an efficient heuristic approach to seek out permutations for compression and have designed its hardware implementation by employing a field-programmable gate array (FPGA) to preprocess incoming packets. Our experiments with ClassBench classifiers and Internet Service Provider (ISP) real-life classifiers show that the proposed BP technique will considerably reduce thirty one.88% TCAM entries on average, in addition to the reduction contributed by different state-of-the-art schemes.

Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here

PROJECT TITLE :An Algorithm for Finding the Minimum Cost of Storing and Regenerating Datasets in Multiple Clouds - 2018ABSTRACT:The proliferation of cloud computing allows users to flexibly store, re-compute or transfer large
PROJECT TITLE :Path Finding for Maximum Value of Information in Multi-Modal Underwater Wireless Sensor Networks - 2018ABSTRACT:We contemplate underwater multi-modal wireless sensor networks (UWSNs) appropriate for applications
PROJECT TITLE : Finding Related Forum Posts through Content Similarity over Intention-based Segmentation - 2017 ABSTRACT: We have a tendency to study the problem of finding related forum posts to a post at hand. In distinction
PROJECT TITLE :A parallel radix-sort-based VLSI architecture for finding the first W maximum/minimum values (2014)ABSTRACT :Very-large-scale integration (VLSI) architectures for finding the first W (W>2) maximum (or minimum)
PROJECT TITLE :A Stochastic Approach for Finding Optimal Context in a Contextual Pattern Analysis TaskABSTRACT:This text issues contextual pattern analysis tasks. As different contexts offer totally different performances, models

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry