Comparison of resource platform selection approaches for scientific workflows

Cloud computing is increasingly considered as an additional computational resource platform for scientific workflows. The cloud offers opportunity to scale-out applications from desktops and local cluster resources. Each platform has different properties (e.g., queue wait times in high performance systems, virtual machine startup overhead in clouds) and characteristics (e.g., custom environments in cloud) that makes choosing from these diverse resource platforms for a workflow execution a challenge for scientists. Scientists are often faced with deciding resource platform selection trade-offs with limited information on the actual workflows. While many workflow planning methods have explored resource selection or task scheduling, these methods often require fine-scale characterization of the workflow that is onerous for a scientist. In this paper, we describe our early exploratory work in using blackbox characteristics for a costbenefit analysis of using different resource platforms. ...

• Type: Conference
• Year: 2010
• Where: HPDC
• Authors: Yogesh L. Simmhan, Lavanya Ramakrishnan
• Keywords: Distributed And Parallel Computing, HPDC 2010, Resource Platform, Resource Selections, Workflow