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Multi-node Scheduling Algorithm Based on Clustering Analysis and Data Partitioning in Emergency Management Cloud

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Web-Age Information Management (WAIM 2013)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 7901))

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Abstract

Real-time processing is a key problem for big data analysis and processing, especially in emergency management. Strongly promoted by the leading industrial companies, cloud computing becomes increasingly popular tool for emergency management, that is emergency management cloud. How to make optimal deployment of emergency management cloud applications is a challenging research problem. The paper proposes a multi-node scheduling algorithm based on clustering analysis and data partitioning in emergency management cloud. First, the presented method divides the cloud nodes into clusters according to the communication cost between different nodes, and then selects a cluster for the big data analysis services. Second, the load balancing theory is used to dispatch big data analysis to these computing nodes in a way to enable synchronized completion at best-effort performance. At last, to improve the real-time of big data analysis, the paper presents a multi-node scheduling algorithm based on game theory to find optimal scheduling strategy for each scheduling node. Experimental results show the effectiveness of our scheduling algorithm for big data analytics in emergency management.

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Author information

Authors and Affiliations

  1. School of Software Technology, Dalian University of Technology, Dalian, China, 116620

    Qingchen Zhang, Zhikui Chen & Liang Zhao

Authors
  1. Qingchen Zhang
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  2. Zhikui Chen
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  3. Liang Zhao
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Editor information

Editors and Affiliations

  1. College of Computer Science, Zhejiang University, Hangzhou, China

    Yunjun Gao

  2. Seoul National University, Seoul, Korea

    Kyuseok Shim

  3. Institute of Software, Chinese Academy of Sciences, South-Fourth-Street 4, Zhong-Guan-Cun, 100190, Beijing, P.R. China

    Zhiming Ding

  4. School of Computer Science and Technology, University of Science and Technology of China, 230027, Hefei, China

    Peiquan Jin

  5. School of Computer Science and Technology, Hangzhou Dianzi University, 310018, Hangzhou, China

    Zujie Ren

  6. Key Laboratory of Intelligence Computing and Novel Software Technology, Tianjin Key Laboratory of Computer Vision and System, Ministry of Education, Tianjin University of Technology, 300384, Tianjin, China

    Yingyuan Xiao

  7. CityU-USTC Advanced Research Institute, Suzhou, China

    An Liu

  8. School of Information Science and Technology, Southwest Jiaotong University, 610031, Chengdu, China

    Shaojie Qiao

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© 2013 Springer-Verlag Berlin Heidelberg

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Zhang, Q., Chen, Z., Zhao, L. (2013). Multi-node Scheduling Algorithm Based on Clustering Analysis and Data Partitioning in Emergency Management Cloud. In: Gao, Y., et al. Web-Age Information Management. WAIM 2013. Lecture Notes in Computer Science, vol 7901. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39527-7_18

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  • DOI: https://doi.org/10.1007/978-3-642-39527-7_18

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-39526-0

  • Online ISBN: 978-3-642-39527-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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