Digital Twin of a Data Center at Education Institution

Abdullah M Almutawa; A.S.  Tolba

Article Details

Digital Twin of a Data Center at Education Institution

Authors:

Abdullah M Almutawa | A.S. Tolba

Publisher:

Kuwait University

Journal:

Journal of Engineering Research Vol.11 Issue 1A, pp.0-0

Document Type:

Article

Publication Date:

1/2023

Document Language:

English

Document ID (Org No.):

2001942541

pISSN:

2307-1885

Abstract:

 Digital twins are among the most important trends of the fourth industrial revolution. They present a crucial tool for protecting critical mission systems and the development of new services, products, and processes. This paper presents the first digital twin for a data center. The rapid growth of the Internet of things and the areas of modeling and simulation results in high demand for the development of data center digital twins (DCDT) to ensure the safety/protection of critical and costly mission infrastructure and guarantee business continuity enhance efficiency, and sustain development. This paper presents the design and implementation of a digital twin for a university data center. Different sensory data like temperature, humidity, smoke, and water leakage are analyzed using an intelligent event detection approach, which detects abnormalities using an Extreme Learning Machine (ELM) fed with the minimum ratio between successive real-time data streams. The performance of ELM has outperformed that of both Learning Vector Quantization and Radial Basis Function-based neural network classifiers and proved much faster in abnormal event detection.

Article Details

Digital Twin of a Data Center at Education Institution

Authors: Abdullah M Almutawa | A.S. Tolba

Publisher: Kuwait University

Journal: Journal of Engineering Research Vol.11 Issue 1A, pp.0-0

Document Type: Article

Publication Date: 1/2023

Document Language: English

Document ID (Org No.): 2001942541

pISSN: 2307-1885

Issues

Authors:

Abdullah M Almutawa | A.S. Tolba

Publisher:

Kuwait University

Journal:

Journal of Engineering Research Vol.11 Issue 1A, pp.0-0

Document Type:

Article

Publication Date:

1/2023

Document Language:

English

Document ID (Org No.):

2001942541

pISSN:

2307-1885