.png){kind=icon}
返回
A Server Placement Algorithm for Reducing Risk and Improving Power Utilization in Data Centers
.png){kind=icon}
OA
AI
DOI：10.26599/TST.2023.9010009.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
As the power demand in data centers is increasing, the power capacity of the power supply system has become an essential resource to be optimized. Although many data centers use power oversubscription to make full use of the power capacity, there are unavoidable power supply risks associated with it. Therefore, how to improve the data center power capacity utilization while ensuring power supply security has become an important issue. To solve this problem, we first define it and propose a risk evaluation metric called Weighted Power Supply Risk (WPSRisk). Then, a method, named Hybrid Genetic Algorithm with Ant Colony System (HGAACS), is proposed to improve power capacity utilization and reduce power supply risks by optimizing the server placement in the power supply system. HGAACS uses historical power data of each server to find a better placement solution by population iteration. HGAACS possesses not only the remarkable local search ability of Ant Colony System (ACS), but also enhances the global search capability by incorporating genetic operators from Genetic Algorithm (GA). To verify the performance of HGAACS, we experimentally compare it with five other placement algorithms. The experimental results show that HGAACS can perform better than other algorithms in both improving power utilization and reducing the risk of power supply system.
Keyword:
server placement
power utilization
power supply risk
swarm intelligence algorithm
期刊
T
IF:
3.5
论文数:
987
被引数:
2.5K
机构
引用论文
Heavy Metal Transport and Detoxification in Crustacean Gastrointestinal and Renal Epithelial Cells
PREAI
分享收藏
Coordinated Priority-aware Charging of Distributed Batteries in Oversubscribed Data Centers在超额订购的数据中心中对分布式电池进行协调的优先级感知充电
PREAI
分享收藏分享收藏Scrapie at Abattoir: Monitoring, Control, and Differential Diagnosis of Wasting Conditions during Meat Inspection.png)
AnimalsOAAI
AnimalsIF0
OAAI分享收藏A New Method of Bearing Remaining Useful Life Based on Life Evolution and SE-ConvLSTM Neural NetworkMachinesOAAI
MachinesIF0
OAAI分享收藏
查看更多内容