Maintenance of Strongly Connected Component in Shared-memory Graph

TL;DR

This paper introduces a novel fully dynamic algorithm for maintaining strongly connected components in shared-memory directed graphs, demonstrating significant throughput improvements and potential applications in online graph analysis.

Contribution

It presents the first linearizable concurrent directed graph algorithm for dynamic SCC maintenance, combining ordered and unordered sets, with empirical performance validation.

Findings

3 to 6 times throughput increase over sequential and coarse-grained methods

Effective handling of concurrent edge and vertex updates

Potential extension to online community detection

Abstract

In this paper, we present an on-line fully dynamic algorithm for maintaining strongly connected component of a directed graph in a shared memory architecture. The edges and vertices are added or deleted concurrently by fixed number of threads. To the best of our knowledge, this is the first work to propose using linearizable concurrent directed graph and is build using both ordered and unordered list-based set. We provide an empirical comparison against sequential and coarse-grained. The results show our algorithm's throughput is increased between 3 to 6x depending on different workload distributions and applications. We believe that there are huge applications in the on-line graph. Finally, we show how the algorithm can be extended to community detection in on-line graph.