Meyer V, Facco Rodrigues V, da Rosa Righi R, Andre da Costa C, Galante G, Bonato Both C (2019)
Publication Language: English
Publication Type: Journal article
Publication year: 2019
Journal Issue: 1
DOI: 10.1504/IJCSYSE.2019.098414
Workflow has become a standard for many scientific applications that are characterized by a collection of processing elements. Particularly, a pipeline application is a type of workflow that receives a set of tasks, which must pass through all processing elements in a linear fashion. However, the strategy of using a fixed number of resources can cause under- or over-provisioning situations, besides not fitting irregular demands. In this context, our idea is to deploy the pipeline application in the cloud, so executing it with a feature that differentiates cloud from other distributed systems: resource elasticity. Thus, we propose Pipel: a reactive elasticity model that uses lower and upper load thresholds and the CPU metric to on-the-fly select the most appropriated number of compute nodes for each stage along the pipeline execution. The results were promising, presenting an average gain of 38% in the application time when comparing non-elastic and elastic executions.
APA:
Meyer, V., Facco Rodrigues, V., da Rosa Righi, R., Andre da Costa, C., Galante, G., & Bonato Both, C. (2019). Pipel: Exploiting Resource Reorganization to Optimize Performance of Pipeline-Structured Applications in the Cloud. International Journal of Computational Systems Engineering, 1. https://dx.doi.org/10.1504/IJCSYSE.2019.098414
MLA:
Meyer, Vinicius, et al. "Pipel: Exploiting Resource Reorganization to Optimize Performance of Pipeline-Structured Applications in the Cloud." International Journal of Computational Systems Engineering 1 (2019).
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