Algorithms and Data Structures to Accelerate Network Analysis
Jordi Ros-Giralt, Alan Commike, Peter Cullen, Richard Lethin
Publication Source: The 4th International Workshop on Innovating the Network for Data Intensive Science (INDIS) 2017, Denver, CO, USA.
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.