Title: Computation migration: a new approach to execute big-data bioinformatics workflows

Authors: Rickey T. P. Nunes; Santosh L. Deshpande

Addresses: VTU Research Resource Centre, Visvesvaraya Technological University, Belagavi, India ' Centre for Postgraduate Studies, Visvesvaraya Technological University, Belagavi, India

Abstract: Bioinformatics workflows frequently access various distributed biological data sources and computational analysis tools for data analysis and knowledge discovery. They move large volumes of data from biological data sources to computational analysis tools and follow the traditional data migration approach for workflow execution. However, in the advent of big-data in bioinformatics, moving large volumes of data to computation during workflow execution is no longer feasible. Considering the fact that the size of biological data is continuously growing and is much larger than the computational analysis tool size, moving computation to data in a workflow is a better solution to handle the growing data. In this paper, we therefore propose a computation migration approach to execute bioinformatics workflows. We move computational analysis tools to data sources during workflow execution and demonstrate with workflow patterns that moving computation instead of data yields high performance gains in terms of data-flow and execution time.

Keywords: big-data; bioinformatics; workflows; orchestration; computation migration.

DOI: 10.1504/IJBDI.2018.092658

International Journal of Big Data Intelligence, 2018 Vol.5 No.3, pp.156 - 164

Received: 13 Jun 2016
Accepted: 12 Oct 2016
Published online: 27 Jun 2018 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article