Published April 24, 2018
| Version v1
Publication
Automated Throughput Optimization of Cloud Services via Model-driven Adaptation
Description
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.
Abstract
Ministerio de Ciencia e Innovación TIN2008-05932Abstract
Ministerio de Ciencia e Innovación TIN2008-031087Abstract
Ministerio de Ciencia e Innovación TIN2011-23795Abstract
Ministerio de Ciencia e Innovación TIN2012-35669Abstract
Junta de Andalucía P11-TIC-7659Additional details
Identifiers
- URL
- https://idus.us.es/handle//11441/73437
- URN
- urn:oai:idus.us.es:11441/73437