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Open Access Highly Accessed Technical advance

The cloud paradigm applied to e-Health

Jordi Vilaplana1, Francesc Solsona1, Francesc Abella2, Rosa Filgueira3 and Josep Rius4*

Author Affiliations

1 Computer Science Department, University of Lleida, Jaume II 69, Lleida, 25001, Spain

2 Unitat de Tabaquisme of Hospital Santa Maria de Lleida, , Alcalde Rovira Roure, 44, Lleida, 25198, Spain

3 Edinburgh Data-Intensive Research Group, School of Informatics, The University of Edinburgh, Edinburgh, UK

4 ICG Software, Pol. Industrial Torrefarrera C. Mestral, , s/n 25123 Torrefarrera, Lleida, Spain

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BMC Medical Informatics and Decision Making 2013, 13:35  doi:10.1186/1472-6947-13-35

Published: 14 March 2013

Abstract

Background

Cloud computing is a new paradigm that is changing how enterprises, institutions and people understand, perceive and use current software systems. With this paradigm, the organizations have no need to maintain their own servers, nor host their own software. Instead, everything is moved to the cloud and provided on demand, saving energy, physical space and technical staff. Cloud-based system architectures provide many advantages in terms of scalability, maintainability and massive data processing.

Methods

We present the design of an e-health cloud system, modelled by an M/M/m queue with QoS capabilities, i.e. maximum waiting time of requests.

Results

Detailed results for the model formed by a Jackson network of two M/M/m queues from the queueing theory perspective are presented. These results show a significant performance improvement when the number of servers increases.

Conclusions

Platform scalability becomes a critical issue since we aim to provide the system with high Quality of Service (QoS). In this paper we define an architecture capable of adapting itself to different diseases and growing numbers of patients. This platform could be applied to the medical field to greatly enhance the results of those therapies that have an important psychological component, such as addictions and chronic diseases.

Keywords:
Cloud systems; e-Health; Queue systems; Quality of service