Abstract
Big data storage and processing are considered as one of the main applications for cloud computing systems. Furthermore, the development of the Internet of Things (IoT) paradigm has advanced the research on Machine to Machine (M2M) communications and enabled novel tele-monitoring architectures for E-Health applications. However, there is a need for converging current decentralized cloud systems, general software for processing big data and IoT systems. The purpose of this paper is to analyze existing components and methods of integrating big data processing with cloud M2M systems based on Remote Telemetry Units (RTUs) and to propose a converged E-Health architecture built on Exalead CloudView, a search based application. Finally, we discuss the main findings of the proposed implementation and future directions.
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References
Kahn, E.: Natural language processing, big data, bioinformatics and biology. International Journal of Biology and Biomedical Engineering 8, 107–117 (2014)
Ochian, A., Suciu, G., Fratu, O., Suciu, V.: Big data search for environmental telemetry. In: IEEE International Black Sea Conference on Communications and Networking (BlackSeaCom), pp. 182–184 (2014)
Vermesan, O., Friess, P., Guillemi, P., Gusmeroli, S.: Internet of Things Strategic Research Agenda. In: Internet of Things – Global Technological and Societal Trends. River Publishers (2011)
Suciu, G., Halunga, S., Fratu, O., Vasilescu, A., Suciu, V.: Study for Renewable Energy Telemetry using a Decentralized Cloud M2M System. In: IEEE 15th International Symposium on Wireless Personal Multimedia Communications (WPMC), pp. 1–5 (2013)
McFedries, P.: The cloud is the computer. IEEE Spectrum 45(8), 20–22 (2008)
Hassan, M.M., Song, B., Huh, E.N.: A framework of sensor-cloud integration opportunities and challenges. In: Proceedings of International Conference Ubiquitous Information Management Communication, pp. 618–626 (2009)
Fox, G.C., Kamburugamuve, S., Hartman, R.D.: Architecture and measured characteristics of a cloud based internet of things. In: International Conference on IEEE Collaboration Technologies and Systems (CTS), pp. 6–12 (2012)
Kranz, M., Holleis, P., Schmidt, A.: Embedded Interaction - Interacting with the Internet of Things. IEEE Internet Computing 14(2), 46–53 (2010)
Jara, A.J., Genoud, D., Bocchi, Y.: Sensors data fusion for Smart Cities with KNIME - A real experience in the SmartSantander Testbed. In: 2014 IEEE World Forum on Internet of Things (WF-IoT), pp. 173–174 (2014)
McAfee, A., Brynjolfsson, E., Davenport, T.H., Patil, D.J., Barton, D.: Big Data. The management revolution. Harvard Bus Rev 90(10), 61–67 (2012)
The 3rd Generation Partnership Project (3GPP), TS 23.888 “System improvements for Machine-Type Communications (MTC),” Version 11.0.0 (2012)
Saad, W., Abbes, H., Jemni, M., Cerin, C.: Designing and implementing a cloud-hosted SaaS for data movement and sharing with SlapOS. International Journal of Big Data Intelligence 1(2), 18–35 (2014)
Shah, T., Rabhi, F., Ray, P.: Investigating an ontology-based approach for Big Data analysis of inter-dependent medical and oral health conditions. In: Cluster Computing, pp. 1–17 (2014)
Eckstein, R.: Interactive search processes in complex work situations - a retrieval framework. University of Bamberg Press 10, 62–67 (2011)
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Suciu, G., Suciu, V., Halunga, S., Fratu, O. (2015). Big Data, Internet of Things and Cloud Convergence for E-Health Applications. In: Rocha, A., Correia, A., Costanzo, S., Reis, L. (eds) New Contributions in Information Systems and Technologies. Advances in Intelligent Systems and Computing, vol 353. Springer, Cham. https://doi.org/10.1007/978-3-319-16486-1_15
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DOI: https://doi.org/10.1007/978-3-319-16486-1_15
Publisher Name: Springer, Cham
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