Distributed Architecture for Grid Square Statistics

Aki-Hiro Sato () and Hiroe Tsubaki ()
Additional contact information
Aki-Hiro Sato: Yokohama City University, Department of Data Science, Graduate School of Data Science
Hiroe Tsubaki: The Institute of Statistical Mathematics

Chapter Chapter 6 in Evaluation Platform of Sustainability for Global Systems, 2024, pp 83-98 from Springer

Abstract: 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.

Date: 2024
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-981-97-2296-9_6

Ordering information: This item can be ordered from
http://www.springer.com/9789819722969

DOI: 10.1007/978-981-97-2296-9_6

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().