Aurora: a new model and architecture for data stream management
The VLDB Journal — The International Journal on Very Large Data Bases
A Technique for Information Sharing using Inter-Vehicle Communication with Message Ferrying
MDM '06 Proceedings of the 7th International Conference on Mobile Data Management
The CQL continuous query language: semantic foundations and query execution
The VLDB Journal — The International Journal on Very Large Data Bases
Travel time estimation using NiagaraST and latte
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
Flexible and scalable storage management for data-intensive stream processing
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
A clustering-based multi-channel vehicle-to-vehicle (V2V) communication system
ICUFN'09 Proceedings of the first international conference on Ubiquitous and future networks
Communication Reduction for Floating Car Data-Based Traffic Information Systems
GEOPROCESSING '10 Proceedings of the 2010 Second International Conference on Advanced Geographic Information Systems, Applications, and Services
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The sustainable urban mobility of people and goods in a territory has become one of the major challenges which has recently gained much interest in several ICT research areas. In this context the Pegasus Project aims to provide reliable and timely information to improve the safety and the efficiency of vehicles' and goods' flows. To do this, it is necessary to collect and integrate large amounts of geo-located stream items coming from On Board Units (OBUs) installed on vehicles. The final aim is to exploit these information for providing end users with various services to enhance mobility. We propose a data management solution where stream items coming from vehicles are processed and stored in a result container. The required data access functionalities are provided through an SQL-like query language enhanced with stream, event, spatial and temporal operators. Finally, we propose several communication-saving techniques for Vehicle to Infrastructure (V2I) and Vehicle to Vehicle (V2V) communications in order to aggregate and reduce the data coming from vehicles.