[Back]

V. Emeakaroha, P. Labaj, M. Maurer, I. Brandic, D. Kreil:
"Optimizing Bioinformatics Workflows for Data Analysis Using Cloud Management Techniques";
Talk: 6th Workshop on Workflows in Support of Large-Scale Science, WORKS 2011 co-located with SC 2011, Seattle, Washington, USA; 11-14-2011; in: "Proceedings of the 6th Workshop on Workflows in Support of Large-Scale Science, WORKS 2011 co-located with SC 2011", ACM, (2011), ISBN: 978-1-4503-1100-7; 37 - 46.

With the rapid development in recent years of high-throughput
technologies in the life sciences, huge amounts of data are being generated and stored in databases. Despite significant advances in computing capacity and performance, an analysis of these large-scale data in a search for biomedically relevant patterns remains a challenging task. Scientific workflow applications support data-mining in more complex scenarios that include many data sources and computational tools, as commonly found in bioinformatics. A
scientific workflow application is a holistic unit that defines,
executes, and manages scientific applications using different
software tools. Existing workflow applications are processor
data- rather than resource-oriented. Thus, they lack efficient
computational resource management capabilities, such as those provided by Cloud computing environments. Insufficient computational resources disrupt the execution of workflow applications, wasting time and money. To address this issue, advanced resource monitoring and management strategies are required to determine the resource consumption behaviours of workflow applications for a dynamical
allocation and deallocation of resources. In this paper, we present a novel Cloud resource monitoring technique and a knowledge management strategy to manage computational resources for workflow applications in order to guarantee their performance goals and their successful completion. We present the design description of these techniques, demonstrate how they can be applied to scientific workflow applications, and present first evaluation results as a proof of
concept.

Workflow Execution, Resource Monitoring, Workflow Management, Knowledge Database

http://dx.doi.org/10.1145/2110497.2110503

Project Head Ivona Brandic:
Foundations of Self-governing ICT Infrastructures