Aggregating and managing big realtime data in the cloud: Application to intelligent transport for smart cities - Kemp, G.; Vargas-Solar, G.; Ferreira da Silva, C.; Ghodous, P.; Collet, C. (Proceedings of International Conference on Vehicle Technology and Intelligent Transport Systems (VEHITS), 2015)
The increasing power of computer hardware and the sophistication of computer software have brought many new possibilities to information world. On one side the possibility to analyse massive data sets has brought new insight, knowledge and information. On the other, it has enabled to massively distribute computing and has opened to a new programming paradigm called Service-Oriented Computing particularly well adapted to cloud computing. Applying these new technologies to the transport industry can bring new understanding to town transport infrastructures. The objective of our work is to manage and aggregate cloud services for managing big data and assist in decision making for transport systems. Thus this paper presents our approach for developing data storage, data cleaning and data integration services to make an efficient decision support system. Our services will implement algorithms and strategies that consume storage and computing resources of the cloud. For this reason, appropriate consumption models will guide their use. Proposing big data management strategies for data produced by transport infrastructures, whilst maintaining cost effective systems deployed on the cloud, is a promising approach.