Sensor communication model using cyber-physical system approach for green data center
Energy consumption in distributed computing system gains a lot of attention recently after its processing capacity becomes significant for better business and economic operations. Comprehensive analysis of energy efficiency in high-performance data center for distributed processing requires ability...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
International Association of Online Engineering
2019
|
| Online Access: | http://psasir.upm.edu.my/id/eprint/82090/1/Sensor%20communication%20model%20using%20cyber-physical%20system%20approach%20for%20green%20data%20center.pdf http://psasir.upm.edu.my/id/eprint/82090/ https://online-journals.org/index.php/i-jim/article/view/11310 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Energy consumption in distributed computing system gains a lot of attention recently after its processing capacity becomes significant for better business and economic operations. Comprehensive analysis of energy efficiency in high-performance data center for distributed processing requires ability to monitor a proportion of resource utilization versus energy consumption. In order to gain green data center while sustaining computational performance, a model of energy efficient cyber-physical communication is proposed. A real-time sensor communication is used to monitor heat emitted by processors and room temperature. Specifically, our cyber-physical communication model dynamically identifies processing states in data center while implying a suitable air-conditioning temperature level. The information is then used by administration to fine-tune the room temperature according to the current processing activities. Our automated triggering approach aims to improve edge computing performance with cost-effective energy consumption. Simulation experiments show that our cyber-physical communication achieves better energy consumption and resource utilization compared with other cooling model. |
|---|