Proxies for Shortest Path and Distance Queries

• Published in: IEEE transactions on knowledge and data engineering Vol. 28; no. 7; pp. 1835 - 1850
• Main Authors: Ma, Shuai, Feng, Kaiyu, Li, Jianxin, Wang, Haixun, Cong, Gao, Huai, Jinpeng
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.07.2016; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithm design and analysis; Algorithms; Data preprocessing; Data reduction; Design engineering; Gold; Graphs; Indexes; Mathematical models; Queries; Roads; Routing; shortest distances; Shortest paths; Shortest-path problems; Social network services; speeding-up techniques; Tasks; data reduction; shortest distances; Shortest paths; speeding-up techniques
• ISSN: 1041-4347; 1558-2191
• DOI: 10.1109/TKDE.2016.2531667

Computing shortest paths and distances is one of the fundamental problems on graphs, and it remains a challenging task today. This article investigates a light-weight data reduction technique for speeding-up shortest path and distance queries on large graphs. To do this, we propose a notion of routing proxies (or simply proxies), each of which represents a small subgraph, referred to as deterministic routing areas (DRAs). We first show that routing proxies hold good properties for speeding-up shortest path and distance queries. Then, we design a linear-time algorithm to compute routing proxies and their corresponding DRAs. Finally, we experimentally verify that our solution is a general technique for reducing graph sizes and speeding-up shortest path and distance queries, using real-life large graphs.