#92 Parallel Order-Based Core Maintenance in Dynamic Graphs

The core numbers of vertices in a graph are one of the most well-studied cohesive subgraph models because of the linear running time. In practice, many data graphs are dynamic graphs that are continuously changing by inserting or removing edges. The core numbers are updated in dynamic graphs with edge insertions and deletions, which is called core maintenance. When a burst of a large number of inserted or removed edges come in, we have to handle these edges on time to keep up with the data stream. There are two main sequential algorithms for core maintenance, \textsc{Traversal} and \textsc{Order}. The experiments show that the \textsc{Order} algorithm significantly outperforms the \textsc{Traversal} algorithm over a variety of real graphs. To the best of our knowledge, all existing parallel approaches are based on the \textsc{Traversal} algorithm. These algorithms exploit parallelism only for vertices with different core numbers; they reduce to sequential algorithms when all vertices have the same core numbers. In this paper, we propose a new parallel core maintenance algorithm based on the \textsc{Order} algorithm. More importantly, our new approach always has parallelism, even for graphs where all vertices have the same core numbers. Extensive experiments are conducted over real-world, temporal, and synthetic graphs on a multicore machine. The results show that for inserting and removing a batch of edges using 16 workers, our method achieves up to 289x and 10x times speedups compared with the most efficient existing method, respectively.