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Coordinated Placement of Meteorological Workflows and Data with Privacy Conflict Protection

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Cloud Computing, Smart Grid and Innovative Frontiers in Telecommunications (CloudComp 2019, SmartGift 2019)

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Abstract

Cloud computing is cited by various industries for its powerful computing power to solve complex calculations in the industry. The massive data of meteorological department has typical big data characteristics. Therefore, cloud computing has been gradually applied to deal with a large number of meteorological -services. Cloud computing increases the computational speed of meteorological services, but data transmission between nodes also generates additional data transmission time. At the same time, based on cloud computing technology, a large number of computing tasks are cooperatively processed by multiple nodes, so improving the resource utilization of each node is also an important evaluation indicator. In addition, with the increase of data confidentiality, there are some data conflicts between some data, so the conflicting data should be avoided being placed on the same node. To cope with this challenge, the meteorological application is modeled and a collaborative placement method for tasks and data based on Differential Evolution algorithm (CPDE) is proposed. The Non-dominated Sorting Differential Evolution (NSDE) algorithm is used to jointly optimize the average data access time, the average resource utilization of nodes and the data conflict degree. Finally, a large number of experimental evaluations and comparative analyses verify the efficiency of our proposed CPDE method.

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Acknowledgment

This research is supported by the Scientific Research Project of Silicon Lake College under Grant No. 2018KY23.

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Authors and Affiliations

  1. School of Computer Science and Technology, Silicon Lake College, Suzhou, China

    Tao Huang, Shengjun Xue, Qing Yang & Yachong Tian

  2. School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing, China

    Shengjun Xue

  3. Shanghai Huanan Environmental Management Limited Company, Shanghai, China

    Yumei Hu

  4. Library of Wuhan University of Technology, Wuhan University of Technology, Hubei, China

    Dan Zeng

Authors
  1. Tao Huang
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  2. Shengjun Xue
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  3. Yumei Hu
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  4. Qing Yang
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  5. Yachong Tian
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  6. Dan Zeng
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Corresponding author

Correspondence to Shengjun Xue .

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Editors and Affiliations

  1. Macquarie University, Sydney, NSW, Australia

    Xuyun Zhang

  2. Macquarie University, Sydney, NSW, Australia

    Guanfeng Liu

  3. Pace University, New York, NY, USA

    Meikang Qiu

  4. James Cook University, Cairns, QLD, Australia

    Wei Xiang

  5. James Cook University, Smithfield, QLD, Australia

    Tao Huang

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© 2020 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Huang, T., Xue, S., Hu, Y., Yang, Q., Tian, Y., Zeng, D. (2020). Coordinated Placement of Meteorological Workflows and Data with Privacy Conflict Protection. In: Zhang, X., Liu, G., Qiu, M., Xiang, W., Huang, T. (eds) Cloud Computing, Smart Grid and Innovative Frontiers in Telecommunications. CloudComp SmartGift 2019 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 322. Springer, Cham. https://doi.org/10.1007/978-3-030-48513-9_44

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  • DOI: https://doi.org/10.1007/978-3-030-48513-9_44

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-48512-2

  • Online ISBN: 978-3-030-48513-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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