Notice of Violation of IEEE Publication Principles: Scientific Workflow Partitioning and Data Flow Optimization in Hybrid Clouds

Abstract

Notice of Violation of IEEE Publication Principles “Scientific Workflow Partitioning and Data Flow Optimization in Hybrid Clouds” by Rubing Duan, Rick Siow Mong Goh, Zheng Qin and Young Liu in Pre-Prints for IEEE Transactions on Cloud Computing After careful and considered review of the content and authorship of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE's Publication Principles. Due to the nature of this violation, reasonable effort should be made to remove all past references to this paper and it should not be used for research or citation The scheduling and execution of workflow applications are complex issues because of the dynamic and heterogeneous nature of distributed computing environments like hybrid clouds. While hybrid cloud computing environments provide good potential for achieving high performance and low economic cost, it also introduces a broad set of unpredictable overheads. This paper describes a novel approach to refine workflow structure and optimize intermediate data transfers without changing the scale of scheduled cloud service for large-scale scientific workflows containing thousands (or even millions) of tasks. These methods include pre- and post-partitioning of workflows, data flow optimization, static and dynamic optimization, as well as virtual single execution environment incorporated into a workflow management system.We demonstrate the effectiveness of our methods on the three real applications, Montage, Broadband, and WIEN2k, executed in a real hybrid cloud.