Please use this identifier to cite or link to this item: https://doi.org/10.1109/TCC.2015.2404807
Title: Monetary Cost Optimizations for Hosting Workflow-as-a-Service in IaaS Clouds
Authors: Zhou, Amelie Chi
He, Bingsheng 
Liu, Cheng 
Keywords: Science & Technology
Technology
Computer Science, Information Systems
Computer Science, Software Engineering
Computer Science, Theory & Methods
Computer Science
Cloud computing
cloud dynamics
spot prices
monetary cost optimizations
scientific workflows
Issue Date: 1-Jan-2016
Publisher: IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Citation: Zhou, Amelie Chi, He, Bingsheng, Liu, Cheng (2016-01-01). Monetary Cost Optimizations for Hosting Workflow-as-a-Service in IaaS Clouds. IEEE TRANSACTIONS ON CLOUD COMPUTING 4 (1) : 34-48. ScholarBank@NUS Repository. https://doi.org/10.1109/TCC.2015.2404807
Abstract: Recently, we have witnessed workflows from science and other data-intensive applications emerging on Infrastructureas- a-Service (IaaS) clouds, and many workflow service providers offering workflow-as-a-service (WaaS). The major concern of WaaS providers is to minimize the monetary cost of executing workflows in the IaaS clouds. The selection of virtual machines (instances) types significantly affects the monetary cost and performance of running a workflow. Moreover, IaaS cloud environment is dynamic, with high performance dynamics caused by the interference from concurrent executions and price dynamics like spot prices offered by Amazon EC2. Therefore, we argue that WaaS providers should have the notion of offering probabilistic performance guarantees for individual workflows to explicitly expose the performance and cost dynamics of IaaS clouds to users. We develop a scheduling system called Dyna to minimize the expected monetary cost given the user-specified probabilistic deadline guarantees. Dyna includes an A$ -based instance configuration method for performance dynamics, and a hybrid instance configuration refinement for using spot instances. Experimental results with three scientific workflow applications on Amazon EC2 and a cloud simulator demonstrate (1) the ability of Dyna on satisfying the probabilistic deadline guarantees required by the users; (2) the effectiveness on reducing monetary cost in comparison with the existing approaches.
Source Title: IEEE TRANSACTIONS ON CLOUD COMPUTING
URI: https://scholarbank.nus.edu.sg/handle/10635/215367
ISSN: 2168-7161
DOI: 10.1109/TCC.2015.2404807
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