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Distributed Architecture for Grid Square Statistics

In: Evaluation Platform of Sustainability for Global Systems

Author

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  • Aki-Hiro Sato

    (Yokohama City University, Department of Data Science, Graduate School of Data Science)

  • Hiroe Tsubaki

    (The Institute of Statistical Mathematics)

Abstract

This chapter introduces distributed architecture for storing, searching, and computing Grid Square statistics. Since the data of Grid Square statistics is enormous, we need to consider efficient computation methods under limited computer resources. The distributed architecture gives us many solutions for handling Grid Square statistics. This chapter explains the fundamental principle of parallel computation with MapReduce algorithms or divide-and-conquer methods. We mention Amdahl’s law and Gustafson’s law. Moreover, we find an implementation of Web API a useful method to exchange data among elements of a distributed system. Finally, we propose a parallelization and distributed architecture for Grid Square statistics.

Suggested Citation

  • Aki-Hiro Sato & Hiroe Tsubaki, 2024. "Distributed Architecture for Grid Square Statistics," Springer Books, in: Evaluation Platform of Sustainability for Global Systems, chapter 0, pages 83-98, Springer.
    • Handle: RePEc:spr:sprchp:978-981-97-2296-9_6
    DOI: 10.1007/978-981-97-2296-9_6
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