TruXy: Trusted Storage Cloud for Scientific Workflows

A wide array of clouds have been built and adopted by business and research communities. Similarly, many research communities use workflow environments and tools such as Taverna and Galaxy to model the execution of tasks to support and expedite the reenactment of complex processes, and ultimately su...

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Bibliographic Details
Published in:IEEE transactions on cloud computing Vol. 5; no. 3; pp. 428 - 442
Main Authors: Nepal, Surya, Sinnott, Richard O., Friedrich, Carsten, Wise, Catherine, Shiping Chen, Kanwal, Sehrish, Jinhui Yao, Lonie, Andrew
Format: Journal Article
Language:English
Published: IEEE Computer Society 01.07.2017
Subjects:
Bioinformatics
Cloud computing
data encryption
Data privacy
Distributed/Internet based software engineering tools and technique
Encryption
health care
integrity and protection
Protocols
security
ISSN:2168-7161, 2372-0018
Online Access:Get full text
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Summary:A wide array of clouds have been built and adopted by business and research communities. Similarly, many research communities use workflow environments and tools such as Taverna and Galaxy to model the execution of tasks to support and expedite the reenactment of complex processes, and ultimately support the repeatability of science. As a result, a number of systems that integrate clouds with these workflow systems have emerged including CloudMap, CloudMan, Galaxy cloud, BioBlend, etc. Though these systems have proven to be successful in service and data integration, they have not dealt with the data security issue inherent in cloud-based systems with the outsourced models of infrastructure provisioning. For many domains, e.g., health, this poses serious challenges regarding the adoption of cloud infrastructures. Yet such domains also have much to gain from clouds especially given the explosion of genomics data and opportunities for personalized medicine in the big data era. This paper addresses this problem by presenting a trusted storage cloud for scientific workflows, called TruXy. The paper describes the TruXy architecture, the corresponding protocols and illustrates the adoption of TruXy to support collaborative bioinformatics research in endocrine genomics. A range of experiments have been performed to measure the performance of TruXy for processing of exome data sets on individuals with a rare genetic disorders: disorders of sex development (DSD). Our results show that the performance of TruXy is comparable to that of using a standalone workflow tool and that it can handle the big data security challenges required.
ISSN:2168-7161
2372-0018
DOI:10.1109/TCC.2015.2489638