Article Per Year (5 Year)
p-Index From 2021 - 2026
0
P-Index
This Author published in this journals
All Journal IJIIS: International Journal of Informatics and Information Systems
Yang, Chao-Tung
Unknown Affiliation
Computer Science & IT

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
A High-Performance Data Accessing and Processing System for Campus Real-time Power Usage Chou, Sheng-Cang; Yang, Chao-Tung
International Journal of Informatics and Information Systems Vol 3, No 3: December 2020
Publisher : International Journal of Informatics and Information Systems

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/ijiis.v3i3.98

Abstract

With the flourishing of Internet of Things (IoT) technology, ubiquitous power data can be linked to the Internet and be analyzed for real-time monitoring requirements. Numerous power data would be accumulated to even Tera-byte level as the time goes. To approach a real-time power monitoring platform on them, an efficient and novel implementation techniques has been developed and formed to be the kernel material of this thesis. Based on the integration of multiple software subsystems in a layered manner, the proposed power-monitoring platform has been established and is composed of Ubuntu (as operating system), Hadoop (as storage subsystem), Hive (as data warehouse), and the Spark MLlib (as data analytics) from bottom to top. The generic power-data source is provided by the so-called smart meters equipped inside factories located in an enterprise practically. The data collection and storage are handled by the Hadoop subsystem and the data ingestion to Hive data warehouse is conducted by the Spark unit. On the aspect of system verification, under single-record query, these software modules: HiveQL and Impala SQL had been tested in terms of query-response efficiency. And for the performance exploration on the full-table query function. The relevant experiments have been conducted on the same software modules as well. The kernel contributions of this research work can be highlighted by two parts: the details of building an efficient real-time power-monitoring platform, and the relevant query-response efficiency for reference.
Implementation of Intelligent Green Energy Management System Yang, Chao-Tung; Yan, Yin-Zhen; Shen, Yu-Chuan; Wang, Yun-Ting; Huang, Chao-Wei; Chen, Shuo-Tsung
International Journal of Informatics and Information Systems Vol 1, No 2: December 2018
Publisher : International Journal of Informatics and Information Systems

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/ijiis.v1i2.102

Abstract

In this work, we mainly apply the cloud infrastructure (IaaS) and virtualization technology to provide the construction services of a green energy management system. First of all, we used MySQL Cluster database technology to build a data storage system which can solve the challenge of large demand. Digital electricity meter data and environmental information are collected efficiently and quickly in the proposed green energy management system. Next, a virtualized user-interface is provided by graphical presentation to facilitate data analysis. Finally, we control the electricity equipment to reduce Power Usage Effectiveness (PUE) and the overall power consumption target-based on this virtualized user-interface of the data analysis.
Co-Authors Chen, Shuo-Tsung Chou, Sheng-Cang Huang, Chao-Wei Shen, Yu-Chuan Wang, Yun-Ting Yan, Yin-Zhen