Hierarchical optimization of optimal path finding for transportation applications
CIKM '96 Proceedings of the fifth international conference on Information and knowledge management
Experimental analysis of dynamic algorithms for the single source shortest paths problem
Journal of Experimental Algorithmics (JEA)
Fully dynamic algorithms for maintaining shortest paths trees
Journal of Algorithms
Introduction to algorithms
Finding shortest paths in large network systems
Proceedings of the 9th ACM international symposium on Advances in geographic information systems
Path Computation Algorithms for Advanced Traveller Information System (ATIS)
Proceedings of the Ninth International Conference on Data Engineering
Materialization Trade-Offs in Hierarchical Shortest Path Algorithms
SSD '97 Proceedings of the 5th International Symposium on Advances in Spatial Databases
Location Based Services
Optimization and evaluation of shortest path queries
The VLDB Journal — The International Journal on Very Large Data Bases
Best routes selection in international intermodal networks
Computers and Operations Research
IPSN '08 Proceedings of the 7th international conference on Information processing in sensor networks
Scalable network distance browsing in spatial databases
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Shortest Path Tree Computation in Dynamic Graphs
IEEE Transactions on Computers
A data model for trip planning in multimodal transportation systems
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
Encyclopedia of GIS
A survey of computational location privacy
Personal and Ubiquitous Computing
Efficient Evaluation of Static and Dynamic Optimal Route Queries
SSTD '09 Proceedings of the 11th International Symposium on Advances in Spatial and Temporal Databases
Fast shortest path distance estimation in large networks
Proceedings of the 18th ACM conference on Information and knowledge management
Engineering fast route planning algorithms
WEA'07 Proceedings of the 6th international conference on Experimental algorithms
The next generation of transportation systems,greenhouse emissions, and data mining
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Query Processing Using Distance Oracles for Spatial Networks
IEEE Transactions on Knowledge and Data Engineering
A Lagrangian approach for storage of spatio-temporal network datasets: a summary of results
Proceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems
Algorithm Design
High performance multimodal networks
SSTD'05 Proceedings of the 9th international conference on Advances in Spatial and Temporal Databases
Heuristic techniques for accelerating hierarchical routing on road networks
IEEE Transactions on Intelligent Transportation Systems
Spatiotemporal data mining in the era of big spatial data: algorithms and applications
Proceedings of the 1st ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data
Data Mining Approaches for Geo-Spatial Big Data: Uncertainty Issues
International Journal of Organizational and Collective Intelligence
| Hi-index | 0.00 |
Increasingly, location-aware datasets are of a size, variety, and update rate that exceeds the capability of spatial computing technologies. This paper addresses the emerging challenges posed by such datasets, which we call Spatial Big Data (SBD). SBD examples include trajectories of cellphones and GPS devices, vehicle engine measurements, temporally detailed road maps, etc. SBD has the potential to transform society via next-generation routing services such as eco-routing. However, the envisaged SBD-based next-generation routing services pose several significant challenges for current routing techniques. SBD magnifies the impact of partial information and ambiguity of traditional routing queries specified by a start location and an end location. In addition, SBD challenges the assumption that a single algorithm utilizing a specific dataset is appropriate for all situations. The tremendous diversity of SBD sources substantially increases the diversity of solution methods. Newer algorithms may emerge as new SBD becomes available, creating the need for a flexible architecture to rapidly integrate new datasets and associated algorithms.