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Link to original content: https://unpaywall.org/10.1007/978-981-15-2810-1_64
A Novel Throughput Based Temporal Violation Handling Strategy for Instance-Intensive Cloud Business Workflows | SpringerLink
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A Novel Throughput Based Temporal Violation Handling Strategy for Instance-Intensive Cloud Business Workflows

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Data Science (ICDS 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1179))

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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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Notes

  1. 1.

    Hadoop: Open Source Implementation of MapReduce: https://hadoop.apache.org.

  2. 2.

    Amazon Simple Workflow Service: https://aws.amazon.com/swf.

  3. 3.

    https://aws.amazon.com/cn/pricing/.

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Acknowledgments

This work was partly supported by the National Natural Science Foundation of China (Grant Nos. 61602006, 615872005), Anhui Provincial Natural Science Foundation (No. 1908085MF206).

Author information

Authors and Affiliations

  1. School of Computer Science and Technology, Anhui University, Hefei, 230601, China

    Futian Wang & Cheng Zhang

  2. Software of Information Technology, Deakin University, Melbourne, 3125, Australia

    Xiao Liu

  3. School of Software, East China Institute of Technology, Nanchang, 330013, China

    Wei Zhang

Authors
  1. Futian Wang
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  2. Xiao Liu
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  3. Wei Zhang
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  4. Cheng Zhang
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Corresponding author

Correspondence to Cheng Zhang .

Editor information

Editors and Affiliations

  1. Swinburne University of Technology, Melbourne, VIC, Australia

    Jing He

  2. University of Illinois at Chicago, Chicago, USA

    Philip S. Yu

  3. College of Information Science and Technology, University of Nebraska at Omaha, Omaha, NE, USA

    Yong Shi

  4. Research Institute of Extenics and Innovation Methods, Guangdong University of Technology, Guangzhou, China

    Xingsen Li

  5. Ningbo University, Ningbo, China

    Zhijun Xie

  6. Deakin University, Burwood, VIC, Australia

    Guangyan Huang

  7. Department of Computer Science and Technology, Nanjing University of Science and Technology, Nanjing, China

    Jie Cao

  8. Nanjing University of Posts and Telecommunications, Nanjing, China

    Fu Xiao

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Wang, F., Liu, X., Zhang, W., Zhang, C. (2020). A Novel Throughput Based Temporal Violation Handling Strategy for Instance-Intensive Cloud Business Workflows. In: He, J., et al. Data Science. ICDS 2019. Communications in Computer and Information Science, vol 1179. Springer, Singapore. https://doi.org/10.1007/978-981-15-2810-1_64

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  • DOI: https://doi.org/10.1007/978-981-15-2810-1_64

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-2809-5

  • Online ISBN: 978-981-15-2810-1

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