Effective data structure for smart big data systems applying an expectation-maximization algorithm

Younghwan Shin, Yunyeong Goh, Changsung Lee, Jong Moon Chung

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In a general big data system there are two major factors that contribute to the processing delay. The total execution time consists of communication time and computation time. In most cases, modern big data systems offload to cloud computing systems to complete their job when too high of a computation load is being processed on the current task assigned systems. However, the adoption of cloud computing can cause the communication delay to increase. As big data analysis is used in more and more real-time systems, reducing the communication delay is one of the major challenges in big data research. This paper presents the application of an expectation-maximization algorithm for a big data system structure in order to reduce the communication time significantly. The fact that a decrease in the communication time in related to the gain of the information entropy is also revealed in this paper.

Original languageEnglish
Title of host publicationProceedings of the 3rd World Conference on Smart Trends in Systems, Security and Sustainability, WorldS4 2019
EditorsXin-She Yang, Nilanjan Dey, Amit Joshi
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages136-140
Number of pages5
ISBN (Electronic)9781728137803
DOIs
Publication statusPublished - 2019 Jul
Event3rd World Conference on Smart Trends in Systems, Security and Sustainability, WorldS4 2019 - London, United Kingdom
Duration: 2019 Jul 302019 Jul 31

Publication series

NameProceedings of the 3rd World Conference on Smart Trends in Systems, Security and Sustainability, WorldS4 2019

Conference

Conference3rd World Conference on Smart Trends in Systems, Security and Sustainability, WorldS4 2019
CountryUnited Kingdom
CityLondon
Period19/7/3019/7/31

Bibliographical note

Funding Information:
ACKNOWLEDGMENT This research was supported by the Ministry of Science and ICT (MSIT), Korea, under the Information Technology Research Center (ITRC) support program (IITP-2018-2018-0-01799) supervised by the Institute for Information & communications Technology Promotion (IITP) and the Institute of BioMed-IT, Energy-IT, and Smart-IT Technology (BEST), a Brain Korea 21 plus program, Yonsei University, and the Institute for Information & communications Technology Promotion (IITP) grant funded by the Korea government (MSIT) (No. 2017-0-00282, The Development of Adaptive Network Technology with Multi-Media Multi-Path).

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Information Systems and Management
  • Renewable Energy, Sustainability and the Environment
  • Safety, Risk, Reliability and Quality
  • Education

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