Algorithms for Searching Massive Graphs
IEEE Transactions on Knowledge and Data Engineering
IEEE Transactions on Knowledge and Data Engineering
An Efficient Path Computation Model for Hierarchically Structured Topographical Road Maps
IEEE Transactions on Knowledge and Data Engineering
Search space reduction in QoS routing
Computer Networks: The International Journal of Computer and Telecommunications Networking
A Spatiotemporal Model and Language for Moving Objects on Road Networks
SSTD '01 Proceedings of the 7th International Symposium on Advances in Spatial and Temporal Databases
Optimization and evaluation of shortest path queries
The VLDB Journal — The International Journal on Very Large Data Bases
Query processing in spatial network databases
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
An external memory data structure for shortest path queries (extended abstract)
COCOON'99 Proceedings of the 5th annual international conference on Computing and combinatorics
Constrained shortest path computation
SSTD'05 Proceedings of the 9th international conference on Advances in Spatial and Temporal Databases
On trip planning queries in spatial databases
SSTD'05 Proceedings of the 9th international conference on Advances in Spatial and Temporal Databases
Write it recursively: a generic framework for optimal path queries
Proceedings of the 13th ACM SIGPLAN international conference on Functional programming
Efficient Evaluation of Static and Dynamic Optimal Route Queries
SSTD '09 Proceedings of the 11th International Symposium on Advances in Spatial and Temporal Databases
Probabilistic path queries in road networks: traffic uncertainty aware path selection
Proceedings of the 13th International Conference on Extending Database Technology
Using the ACO algorithm for path searches in social networks
Applied Intelligence
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We investigate the problem of how to evaluate, fast and efficiently, classes of optimal route queries on a massive graph in a unified framework. To evaluate a route query effectively, a large network is partitioned into a collection of fragments, and distances of some optimal routes in the network are pre-computed. Under such a setting, we find a unified algorithm that can evaluate classes of optimal route queries. The classes that can be processed efficiently are called constraint preserving (CP) which include, among others, shortest path, forbidden edges, forbidden nodes and α-autonomy optimal route query classes. We prove the correctness of the unified algorithm. We then turn our attention to the optimization of the proposed algorithm. Several pruning and optimization techniques are derived that minimize the search time and I/O accesses. We show empirically that these techniques are effective. The proposed optimal route query evaluation algorithm, with all these techniques incorporated, is compared with a main-memory and a disk-based brute-force CP algorithms. We show experimentally that the proposed unified algorithm outperforms the brute-force algorithms, both in term of CPU time and I/O cost, by a wide margin.