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Cloud-based architecture for web applications with load forecasting mechanism: a use case on the e-learning services of a distant university

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Abstract

In cloud systems, a clear necessity emerges related to the use of efficient and scalable computing resources. For this, accurate predictions on the load of computing resources are a key. Thanks to these accurate predictions, reduced power consumption and enhanced revenue of the system can be achieved, since resources can be ready when users need them and shutdown when they are no longer needed. This work presents an architecture to manage web applications based on cloud computing, which combines both local and public cloud resources. This work also presents the algorithms needed to efficiently manage such architecture. Among them, a load forecasting algorithm has been developed based on Exponential Smoothing. An use case of the e-learning services of our University presenting the behaviour of our architecture has been evaluated through a series of simulations. Among the most remarkable results, power consumption is reduced by 32 % at the cost of 367.31 US$ a month compared with the current architecture.

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Acknowledgments

The authors would like to acknowledge the support of the following European Union projects: RIPLECS (517836-LLP-1-2011-1-ES-ERASMUS-ESMO), PAC (517742-LLP-1-2011-1-BG-ERASMUS-ECUE), EMTM (2011-1-PL1-LEO05-19883), and MUREE (530332-TEMPUS-1-2012-1-JO-TEMPUS-JPCR). Furthermore, we also thank the Community of Madrid for the support of E-Madrid Network of Excellence (S2009/TIC-1650).

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Authors and Affiliations

  1. Dpto. de Sistemas de Comunicación y Control, Universidad Nacional de Educación a Distancia, Madrid, Spain

    Salvador Ros, Agustín C. Caminero, Roberto Hernández, Antonio Robles-Gómez & Llanos Tobarra

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  1. Salvador Ros
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  2. Agustín C. Caminero
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Correspondence to Agustín C. Caminero.

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Ros, S., Caminero, A.C., Hernández, R. et al. Cloud-based architecture for web applications with load forecasting mechanism: a use case on the e-learning services of a distant university. J Supercomput 68, 1556–1578 (2014). https://doi.org/10.1007/s11227-014-1125-x

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