Approximate Shortest Distance Computing: A Query-Dependent Local Landmark Scheme

—Shortest distance query between two nodes is a fundamental operation in large-scale networks. Most existing methods in the literature take a landmark embedding approach, which selects a set of graph nodes as landmarks and computes the shortest distances from each landmark to all nodes as an embedding. To handle a shortest distance query between two nodes, the precomputed distances from the landmarks to the query nodes are used to compute an approximate shortest distance based on the triangle inequality. In this paper, we analyze the factors that affect the accuracy of the distance estimation in the landmark embedding approach. In particular we find that a globally selected, query-independent landmark set plus the triangulation based distance estimation introduces a large relative error, especially for nearby query nodes. To address this issue, we propose a query-dependent local landmark scheme, which identifies a local landmark close to the specific query nodes and provides a mor...

• Type: Journal
• Year: 2012
• Where: ICDE
• Authors: Miao Qiao, Hong Cheng, Lijun Chang, Jeffrey Xu Yu
• Keywords: Database, Global Landmark, ICDE 2012, Query Complexity, Triangle Inequality