Abstract
Given a directed acyclic graph (DAG), a k-hop reachability query u → ?k is used to answer whether there exists a path from u to v with length ≤ k. Answering k-hop reachability queries is a fundamental graph operation and has been extensively studied during the past years. Considering that existing approaches still suffer from inefficiency in practice when processing large graphs, we propose a novel labeling scheme, namely HT, to accelerate k-hop reachability queries answering. HTuses a constrained 2hop distance label to maintain the length of shortest paths between a set of hop nodes and other nodes, and for the remaining reachability information, HT uses a novel topological level to accelerate graph traversal. Further, we propose to enhance HT by two optimization techniques. The experimental results show that compared with the state-of-the-art approaches, HT works best for most graphs when answering k-hop reachability queries with small index size and reasonable index construction time.
Highlights
Given a directed graph, a reachability query u? v asks whether there exists a path from u to v
It uses topological orders to quickly prune unreachable queries, and uses interval of a breadth-first search (BFS) spanning tree to facilitate reachable queries answering. It was shown in [20] that when processing k-hop reachability queries on directed acyclic graph (DAG), BFSI-B performs better than kReach
DAGs can find its own applications in practice and existing approaches cannot work well, in this paper, we focus on efficiently answering k-hop reachability queries on DAGs
Summary
A reachability query u? v asks whether there exists a path from u to v. By Label+G, it means that the index covers only a part of shortest distance information, and we need to perform graph traversal, if we cannot get the answer directly from the index. Even though both kinds of approaches are much more efficient than the naive approaches, they still suffer from inefficiency in practice for large graphs. The basic idea is to further increase the coverage of node label by efficiently constructing a compact index that captures shortest distance between most nodes, such that many k-hop reachability queries can be answered without graph traversal. The experimental results show that our approach works best on most datasets for queries answering with small index size and reasonable index construction time
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