Abstract
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.
| Original language | English |
|---|---|
| Article number | 7412739 |
| Pages (from-to) | 1835-1850 |
| Number of pages | 16 |
| Journal | IEEE Transactions on Knowledge and Data Engineering |
| Volume | 28 |
| Issue number | 7 |
| DOIs | |
| State | Published - 1 Jul 2016 |
Keywords
- Shortest paths
- data reduction
- shortest distances
- speeding-up techniques
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