A Ternary Unification Framework for Optimizing TCAM-Based Packet Classification Systems

TCAM SPliT: Optimizing Space, Power, and Throughput for TCAM-based Packet Classification Systems

Packet classification is the core mechanism that enables many networking services such as packet filtering and traffic accounting. Using Ternary Content Addressable Memories (TCAMs) to perform high-speed packet classification has become the de facto standard in industry because TCAMs can facilitate constant time classification by comparing a packet with all rules of ternary encoding in parallel...

Algorithmic Approaches to Optimizing TCAM-Based Packet Classification

Packet classification is the core mechanism that enables many networking services such as packet filtering and traffic accounting. Using Ternary Content Addressable Memories (TCAMs) to perform high-speed packet classification has become the de facto standard in industry because TCAMs can facilitate constant time classification by comparing a packet with all rules of ternary encoding in parallel...

Topological Transformation Approaches to Optimizing TCAM-Based Packet Processing Systems

Bidirectional Range Extension for TCAM-Based Packet Classification

Packet classification is a fundamental task for network devices such as edge routers, firewalls, and intrusion detection systems. Currently, most vendors use Ternary Content Addressable Memories (TCAMs) to achieve high-performance packet classification. TCAMs use parallel hardware to check all rules simultaneously. Despite their high speed, TCAMs have a problem in dealing with ranges efficientl...

Scalable packet classification by TCAM entry encryption algorithm

Ternary content-addressable memory (TCAM) has been widely used to perform fast packet classification due to its ability of solving the problem in O(1) time without considering the number of entries, mask continuity and their lengths. However, it also comes with several shortcomings, such as the limited number of entries, expensive cost and power consumption. We propose an efficient algorithm to...