Presentation
Automated Throughput Optimization of Cloud Services via Model-driven Adaptation
Author/s | Troya Castilla, Javier
Cubo, Javier Martín, José Antonio Pimentel, Ernesto Vallecillo Moreno, Antonio |
Department | Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos |
Publication Date | 2013 |
Deposit Date | 2018-04-24 |
Published in |
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ISBN/ISSN | 978-989-8565-42-6 |
Abstract | Cloud computing promises easy access, low entry cost and elasticity. However, elastic service provisioning
is usually delivered via service replication, which must be supervised manually, hand-picking the services
to ... Cloud computing promises easy access, low entry cost and elasticity. However, elastic service provisioning is usually delivered via service replication, which must be supervised manually, hand-picking the services to replicate and ensuring their proper load balance. Automated service provisioning, i.e., the function of automatically scaling the services to cope up with their runtime demand, is a research challenge in cloud computing. In this work, we include such scalability analysis early in its development cycle, right at the design stage. We propose a model-driven approach where various QoS parameters can be simulated and analyzed using the e-Motions tool. Additionally, the model is automatically transformed to fit the given throughput requirements by replicating the services which cause the bottleneck. In order to evaluate the proposal, we present some initial experimental results run over the e-Motions tool. |
Project ID. | TIN2008-05932
![]() TIN2008-031087 ![]() TIN2011-23795 ![]() TIN2012-35669 ![]() P11-TIC-7659 ![]() |
Citation | Troya Castilla, J., Cubo, J., Martín, J.A., Pimentel, E. y Vallecillo Moreno, A. (2013). Automated Throughput Optimization of Cloud Services via Model-driven Adaptation. En MODELSWARD 2013: 1st International Conference on Model-Driven Engineering and Software Development (356-362), Barcelona, España: ScitePress Digital Library. |
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