Residential College | false |
Status | 已發表Published |
Real-time analysis and visualization for big data of energy consumption | |
Jiaxue Li1,2; Wei Song1; Simon Fong2 | |
2017-12-28 | |
Conference Name | ICSEB 2017: 2017 International Conference on Software and e-Business |
Source Publication | ICSEB 2017: Proceedings of the 2017 International Conference on Software and e-Business |
Pages | 13-16 |
Conference Date | 28 December, 2017- 30 December, 2017 |
Conference Place | Hong Kong Hong Kong |
Publisher | ASSOC COMPUTING MACHINERY, 1515 BROADWAY, NEW YORK, NY 10036-9998 USA |
Abstract | This paper proposes a research on real-time analysis and visualization for big data of energy consumption. In this research, we access real-time energy consumption data from cloud storage by a Transmission Control Protocol/Internet Protocol (TCP/IP). In order to optimize K-Means clustering algorithm, we implement CUDA C programming to finish data-intensive calculation in the Graphic Processing Unit (GPU), which enhances the efficiency of analysis for big data of energy consumption. Meanwhile, to realize data visualization, we draw the data mining results in a multidimensional plane utilizing DirectX, which is a standard graphics API. We also render the original energy consumption data directly in the form of four-dimensional geometry with the plane together, so as to obtain more useful information intuitively. |
Keyword | Big Data Energy Consumption K-means Directx Cuda |
DOI | 10.1145/3178212.3178229 |
URL | View the original |
Indexed By | CPCI-S |
Language | 英語English |
WOS Research Area | Computer Science |
WOS Subject | Computer Science, Information Systems ; Computer Science, Software Engineering ; Computer Science, Theory & Methods |
WOS ID | WOS:000501726100002 |
Scopus ID | 2-s2.0-85045888095 |
Fulltext Access | |
Citation statistics | |
Document Type | Conference paper |
Collection | DEPARTMENT OF COMPUTER AND INFORMATION SCIENCE |
Affiliation | 1.Department of Digital Media Technology, North China University of Technology, Beijing, China 2.Department of Computer and Information Science, University of Macau, Taipa, Macau SAR |
First Author Affilication | University of Macau |
Recommended Citation GB/T 7714 | Jiaxue Li,Wei Song,Simon Fong. Real-time analysis and visualization for big data of energy consumption[C]:ASSOC COMPUTING MACHINERY, 1515 BROADWAY, NEW YORK, NY 10036-9998 USA, 2017, 13-16. |
APA | Jiaxue Li., Wei Song., & Simon Fong (2017). Real-time analysis and visualization for big data of energy consumption. ICSEB 2017: Proceedings of the 2017 International Conference on Software and e-Business, 13-16. |
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