NDLI: Controlling the Deployment of Virtual Machines on Clusters and Clouds for Scientific Computing in CBRAIN

Content Provider	IEEE Xplore Digital Library
Author	Glatard, T. Rousseau, M.-E. Rioux, P. Adalat, R. Evans, A.C.
Copyright Year	2014
Description	Author affiliation: McConnell Brain Imaging Centre, McGill Univ., Montreal, QC, Canada (Glatard, T.; Rousseau, M.-E.; Rioux, P.; Adalat, R.; Evans, A.C.)
Abstract	The emergence of hardware virtualization, notably exploited by cloud infrastructures, led to a paradigm shift in distributed computing by enabling complete software customization and elastic scaling of resources. However, new software architectures and deployment algorithms are still required to fully exploit virtualization in web platforms used for scientific computing, commonly called science gateways. We propose a software architecture and an algorithm to enable and optimize the deployment of virtual machines on clusters and clouds in science gateways. Our architecture is based on 3 design principles: (i) separation between resource provisioning and task scheduling (ii) encapsulation of VMs in regular computing tasks (iii) association of a virtual computing site to each disk image. Our algorithm submits and removes VMs on clusters and clouds based on the current system workload, the number of available job slots in active VMs, the cost and current performance of clouds clusters, and a parameter quantifying the performance-cost trade-off. To cope with variable queuing and booting times, it replicates VMs on independent computing sites selected from a minimization of a make span-cost linear combination in the Pareto set of non-dominated solutions. Make span and cost are estimated from the last measured queuing, booting, and task execution times, using an exponential model of the gain yielded by VM replication. We implement this algorithm in CBRAIN, a science gateway widely used for neuroimaging, and we evaluate it on an infrastructure of 2 clusters and 1 cloud. Results show that it is able to reach some points of the performance-cost trade-off associated to VM deployment.
Starting Page	384
Ending Page	393
File Size	339375
Page Count	10
File Format	PDF
ISBN	9781479927845
DOI	10.1109/CCGrid.2014.42
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-05-26
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Logic gates Clustering algorithms Booting Virtual machining Portals Clouds Monitoring Software architecture Virtual machines Science gateways Clusters Cloud Multi-objective optimization
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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