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VLDB
2007
ACM

Optimization and evaluation of shortest path queries

10 years 12 months ago
Optimization and evaluation of shortest path queries
We investigate the problem of how to evaluate efficiently a collection of shortest path queries on massive graphs that are too big to fit in the main memory. To evaluate a shortest path query efficiently, we introduce two pruning algorithms. These algorithms differ on the extent of materialization of shortest path cost and on how the search space is pruned. By grouping shortest path queries properly, batch processing improves the performance of shortest path query evaluation. Extensive study is also done on fragment sizes, cache sizes and query types that we show that affect the performance of a disk-based shortest path algorithm. The performance and scalability of proposed techniques are evaluated with large road systems in the Eastern United States. To demonstrate that the proposed disk-based algorithms are viable, we show that their search times are significant better than that of mainmemory Dijkstra's algorithm.
Edward P. F. Chan, Heechul Lim
Added 05 Dec 2009
Updated 05 Dec 2009
Type Conference
Year 2007
Where VLDB
Authors Edward P. F. Chan, Heechul Lim
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