GRU: Efficient reachability answering for large graphs using united interval labeling

Abstract

The issue in reachability problem of graph G = (V, E) is whether there is a path between two given nodes or not. This problem plays a key role in areas such as Bioinformatics, Semantic Web, Computer Networks and Social Networks, which have very large graph-structured data. Also, the reachability problem is employed considerably in the graph management and graph algorithms. In this paper, we propose a novel labeling approach for large directed graphs. Our presented method is called GRU (Graph Reachability indexing using United intervals), that can answer reachability queries in constant time even for large graphs. The significant point in this approach is that all the reachability information is computed after indexing time. In addition, this computation is performed only with one time DFS (post-order) traverse and labels are calculated precisely and stored in an efficient way. Analytical and experimental results reveal that effectiveness of our method is more than other interval labeling methods. Furthermore, our approach results show improvement in query time in comparison with GRAIL, which is only a scalable index for reachability queries.