Operation Risk Warning of Edge Data Centers
Article No.: 153, Pages 1 - 5
Abstract
The equipment scale of the edge data center is relatively small, even miniature. After clustering, the operation and maintenance work is extremely complex, which is not conducive to the performance of the edge data center cluster. There are two main reasons: first, the numbers of operation and maintenance personnel can not meet the demand; second, it is difficult to grasp the operation risk of edge data center during off-site monitoring, and the maintenance efficiency of dispatchers when they go to the site is very low. The operation risk warning of edge data center is one of the important measures to exert the overall efficiency of edge computing. Its core is to analyze the operation data of edge sites, mine the operation risk, and improve the operation and maintenance capacity and efficiency of edge data center. Therefore, this paper studies four different operation risks of edge data center, and proposes corresponding operational risk early warning methods.
References
[1]
Zhang H, Liu X, Zhang H. Research on Automation of IT Operation and Maintenance Management[J]. China Computer & Communication, 2017(9):34-35.
[2]
Emily Missner, Leslie J. Reynolds. Operations Management/Operations Research Web Sites [J]. Journal of Business&Finance Librarianship, 2003, 83-4:.
[3]
Guo Y, Cai H, Lei G E. Telecom intelligent operation system based on big data grid [J]. Telecommunications Science, 2018.
[4]
Zhang Y, Wang L. Research on Analysis Method of Information System Operation Discipline[C]//IOP Conference Series: Earth and Environmental Science. IOP Publishing, 2019, 252(3): 032049.
[5]
Liu R, Li W, Li F, State Features and Tendency Indices Embodying Abnormal Operation of Power Systems[J]. Automation of Electric Power Systems, 2013, 37(20):47-53.
[6]
Zhang Y, Wang J. The Evaluation Method For Maintenance of IT System [J]. Information Technology and Informatization, 2017(11):33-36.
[7]
Zhang Y F, Ai Q, Li Z Y, Feature Extraction Based Electricity Theft Detection for Edge Data Center [J]. Automation of Electric Power System, 44(9):128.
[8]
Sun M Y, Yu F, Zhao J Q, Integrated Operation/Maintenance Architecture and Key Technologies of New Generation Dispatching and Control System[J]. Automation of Electric Power System, 43(22):217.
[9]
Liang T . Some Measures of Improving the Ability of Electric Power Management Information System Operation Safety[J]. Energy Technology, 2008.
[10]
Xia J F, Guo Y L, Zhang Y. Operation and Maintenance of HIS System Based on Monitoring Data Analysis[J]. Chinese Journal of Health Informatics and Management, 2015.
Index Terms
- Operation Risk Warning of Edge Data Centers
Index terms have been assigned to the content through auto-classification.
Recommendations
Explicitly Consider Server-Attached Fans for Thermal Modeling in Edge Data Centers
e-Energy '20: Proceedings of the Eleventh ACM International Conference on Future Energy SystemsEdge data center has become an important data center type in recent years. Comparing to a conventional data center, an edge data center often lacks sophisticated cooling equipment and infrastructure support. In the resulting poor thermal environment, ...
Innovation on Transnational Investment Risk Warning Based on Radar Positioning of Chinese Enterprises
ICEE '12: Proceedings of the 2012 3rd International Conference on E-Business and E-Government - Volume 02The current sovereign debt ratings crisis of the United States has sounded the worldwide economic and financial red warning alert once again. The harsh reality forces us to fight our way out – go out to the transnational investment! As we identify that ...
Tail Risk Early Warning System for Capital Markets Based on Machine Learning Algorithms
AbstractScientific and effective tail risk measurement and early warning are key points and difficulties in the identification and control of major risks in capital markets. In this paper, we use the autoregressive conditional Fréchet model (AcF) to ...
Comments
Information & Contributors
Information
Published In
January 2021
1142 pages
ISBN:9781450389570
DOI:10.1145/3448734
Copyright © 2021 ACM.
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 17 May 2021
Check for updates
Author Tags
Qualifiers
- Research-article
- Research
- Refereed limited
Conference
CONF-CDS 2021
CONF-CDS 2021: The 2nd International Conference on Computing and Data Science
January 28 - 30, 2021
CA, Stanford, USA
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 23Total Downloads
- Downloads (Last 12 months)7
- Downloads (Last 6 weeks)0
Reflects downloads up to 02 Sep 2024
Other Metrics
Citations
View Options
Get Access
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign inFull Access
View options
View or Download as a PDF file.
PDFeReader
View online with eReader.
eReaderHTML Format
View this article in HTML Format.
HTML Format