Algorithms and Data Structures to Accelerate Network Analysis

TL;DR

This paper introduces five novel algorithms and data structures to enhance network traffic analysis, achieving significant speed improvements on high-performance network appliances.

Contribution

It presents new algorithms and data structures specifically designed for accelerating network analysis tasks in high-speed environments.

Findings

Achieved 5X speedup in network traffic analysis

Optimized algorithms for 10 Gbps traffic rates

Integrated solutions into R-Scope platform

Abstract

As the sheer amount of computer generated data continues to grow exponentially, new bottlenecks are unveiled that require rethinking our traditional software and hardware architectures. In this paper we present five algorithms and data structures (long queue emulation, lockless bimodal queues, tail early dropping, LFN tables, and multiresolution priority queues) designed to optimize the process of analyzing network traffic. We integrated these optimizations on R-Scope, a high performance network appliance that runs the Bro network analyzer, and present benchmarks showcasing performance speed ups of 5X at traffic rates of 10 Gbps.