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2020 | OriginalPaper | Buchkapitel

A Novel Throughput Based Temporal Violation Handling Strategy for Instance-Intensive Cloud Business Workflows

verfasst von : Futian Wang, Xiao Liu, Wei Zhang, Cheng Zhang

Erschienen in: Data Science

Verlag: Springer Singapore

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Abstract

Temporal violations take place during the batch-mode execution of instance-intensive business workflows running in the cloud environments which may significantly affect the QoS (Quality of Service) of cloud workflow system. However, currently most research in the area of workflow temporal QoS focuses on single scientific workflow rather than business workflow with a batch of parallel workflow instances. Therefore, how to handle temporal violations of instance-intensive cloud business workflows is a new challenge. To address such a problem, in this paper, we propose a novel throughput based temporal violation handling strategy. Specifically, firstly we present a definition of throughput based temporal violation handling point to determine where temporal violation handling should be conducted, and secondly we design a new method for adding necessary cloud computing resources for recovering detected temporal violations. Experimental results show that our temporal violation handling strategy can effectively handle temporal violations in cloud business workflow and thus guarantee satisfactory on-time completion rate.

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Titel: A Novel Throughput Based Temporal Violation Handling Strategy for Instance-Intensive Cloud Business Workflows
verfasst von: Futian Wang
Xiao Liu
Wei Zhang
Cheng Zhang
Verlag: Springer Singapore
Buch: Data Science
Print ISBN: 978-981-15-2809-5

Electronic ISBN: 978-981-15-2810-1

Copyright-Jahr: 2020
DOI: https://doi.org/10.1007/978-981-15-2810-1_64

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