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Export Reference (APA) 
Kemp, G., Vargas-Solar, G., Ferreira da Silva, C., Ghodous, P. & Collet, C. (2015). Aggregating and managing big realtime data in the cloud: Application to intelligent transport for smart cities. In Markus Helfert and Oleg Gusikhin  (Ed.), Proceedings of International Conference on Vehicle Technology and Intelligent Transport Systems (VEHITS). (pp. 107-112). Lisboa: scitepress.
Export Reference (IEEE) 
K. G. et al.,  "Aggregating and managing big realtime data in the cloud: Application to intelligent transport for smart cities", in Proc. of Int. Conf. on Vehicle Technology and Intelligent Transport Systems (VEHITS), Markus Helfert and Oleg Gusikhin , Ed., Lisboa, scitepress, 2015, pp. 107-112
Export BibTeX 
@inproceedings{g.2015_1764938261326,
	author = "Kemp, G. and Vargas-Solar, G. and Ferreira da Silva, C. and Ghodous, P. and Collet, C.",
	title = "Aggregating and managing big realtime data in the cloud: Application to intelligent transport for smart cities",
	booktitle = "Proceedings of International Conference on Vehicle Technology and Intelligent Transport Systems (VEHITS)",
	year = "2015",
	editor = "Markus Helfert and Oleg Gusikhin ",
	volume = "",
	number = "",
	series = "",
	pages = "107-112",
	publisher = "scitepress",
	address = "Lisboa",
	organization = "",
	url = "http://www.scopus.com/inward/record.url?eid=2-s2.0-84939520441&partnerID=MN8TOARS"
}
Export RIS 
TY  - CPAPER
TI  - Aggregating and managing big realtime data in the cloud: Application to intelligent transport for smart cities
T2  - Proceedings of International Conference on Vehicle Technology and Intelligent Transport Systems (VEHITS)
AU  - Kemp, G.
AU  - Vargas-Solar, G.
AU  - Ferreira da Silva, C.
AU  - Ghodous, P.
AU  - Collet, C.
PY  - 2015
SP  - 107-112
CY  - Lisboa
UR  - http://www.scopus.com/inward/record.url?eid=2-s2.0-84939520441&partnerID=MN8TOARS
AB  - 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.
ER  -