Codes for Load Balancing in TCAMs: Size Analysis

TL;DR

This paper analyzes the size of TCAM-based traffic splitting algorithms, providing bounds and expected sizes for minimal representations, which are crucial for efficient load balancing in networks.

Contribution

It offers theoretical bounds and analysis of minimal TCAM representations for traffic splitting, advancing understanding of their efficiency and limitations.

Findings

Established upper bounds for TCAM representation sizes.

Proved lower bounds for general TCAMs.

Showed expected size scales linearly with number of parts and log of address space.

Abstract

Traffic splitting is a required functionality in networks, for example for load balancing over paths or servers, or by the source's access restrictions. The capacities of the servers (or the number of users with particular access restrictions) determine the sizes of the parts into which traffic should be split. A recent approach implements traffic splitting within the ternary content addressable memory (TCAM), which is often available in switches. It is important to reduce the amount of memory allocated for this task since TCAMs are power consuming and are often also required for other tasks such as classification and routing. Recent works suggested algorithms to compute a smallest implementation of a given partition in the longest prefix match (LPM) model. In this paper we analyze properties of such minimal representations and prove lower and upper bounds on their size. The upper bounds hold for general TCAMs, and we also prove an additional lower-bound for general TCAMs. We also analyze the expected size of a representation, for uniformly random ordered partitions. We show that the expected representation size of a random partition is at least half the size for the worst-case partition, and is linear in the number of parts and in the logarithm of the size of the address space.