ENERGY‐SAVING TECHNOLOGIES OF SERVERS IN DATA CENTERS

2021 ◽  
pp. 337-348
Author(s):  
Weiwei Lin ◽  
Wentai Wu ◽  
Keqin Li
Keyword(s):  
Energies ◽  
2020 ◽  
Vol 13 (21) ◽  
pp. 5719
Author(s):  
JiHyun Hwang ◽  
Taewon Lee

The recent expansion of the internet network and rapid advancements in information and communication technology are expected to lead to a significant increase in power consumption and the number of data centers. However, these data centers consume a considerable amount of electric power all year round, regardless of working days or holidays; thus, energy saving at these facilities has become essential. A disproportionate level of power consumption is concentrated in computer rooms because air conditioners in these rooms are required to operate throughout the year to maintain a constant indoor environment for stable operation of computer equipment with high-heat release densities. Considerable energy-saving potential is expected in such computer rooms, which consume high levels of energy, if an outdoor air-cooling system and air conditioners are installed. These systems can reduce the indoor space temperature by introducing a relatively low outdoor air temperature. Therefore, we studied the energy-saving effect of introducing an outdoor air-cooling system in a computer room with a disorganized arrangement of servers and an inadequate air conditioning system in a research complex in Korea. The findings of this study confirmed that annual energy savings of up to approximately 40% can be achieved.


2020 ◽  
Vol 2020 ◽  
pp. 1-9 ◽  
Author(s):  
Shanchen Pang ◽  
Kexiang Xu ◽  
Shudong Wang ◽  
Min Wang ◽  
Shuyu Wang

Green computing focuses on the energy consumption to minimize costs and adverse environmental impacts in data centers. Improving the utilization of host computers is one of the main green cloud computing strategies to reduce energy consumption, but the high utilization of the host CPU can affect user experience, reduce the quality of service, and even lead to service-level agreement (SLA) violations. In addition, the ant colony algorithm performs well in finding suitable computing resources in unknown networks. In this paper, an energy-saving virtual machine placement method (UE-ACO) is proposed based on the improved ant colony algorithm to reduce the energy consumption and satisfy users’ experience, which achieves the balance between energy consumption and user experience in data centers. We improve the pheromone and heuristic factors of the traditional ant colony algorithm, which can guarantee that the improved algorithm can jump out of the local optimum and enter the global optimal, avoiding the premature maturity of the algorithm. Experimental results show that compared to the traditional ant colony algorithm, min-min algorithm, and round-robin algorithm, the proposed algorithm UE-ACO can save up to 20%, 24%, and 30% of energy consumption while satisfying user experience.


2020 ◽  
Vol 16 (6) ◽  
pp. 155014772093577
Author(s):  
Zan Yao ◽  
Ying Wang ◽  
Xuesong Qiu

With the rapid development of data centers in smart cities, how to reduce energy consumption and how to raise economic benefits and network performance are becoming an important research subject. In particular, data center networks do not always run at full load, which leads to significant energy consumption. In this article, we focus on the energy-efficient routing problem in software-defined network–based data center networks. For the scenario of in-band control mode of software-defined data centers, we formulate the dual optimal objective of energy-saving and the load balancing between controllers. In order to cope with a large solution space, we design the deep Q-network-based energy-efficient routing algorithm to find the energy-efficient data paths for traffic flow and control paths for switches. The simulation result reveals that the deep Q-network-based energy-efficient routing algorithm only trains part of the states and gets a good energy-saving effect and load balancing in control plane. Compared with the solver and the CERA heuristic algorithm, energy-saving effect of the deep Q-network-based energy-efficient routing algorithm is almost the same as the heuristic algorithm; however, its calculation time is reduced a lot, especially in a large number of flow scenarios; and it is more flexible to design and resolve the multi-objective optimization problem.


2014 ◽  
Vol 602-605 ◽  
pp. 928-932
Author(s):  
Min Li ◽  
Yun Wang ◽  
Zheng Qian Feng ◽  
Wang Li

By studying the energy-saving technologies of air-conditioning system in data centers, we designed a intelligent air conditioning system, improved the cooling efficiency of air conditioning system through a reasonable set of hot and cold aisles, reduced the running time of HVAC by using the intelligent heat exchange system, an provided a reference for energy saving research of air conditioning system of data centers.


Author(s):  
Tran Hoang Vu ◽  
Pham Ngoc Nam ◽  
Tran Thanh ◽  
Le Thai Hung ◽  
Le Anh Van ◽  
...  
Keyword(s):  

Sign in / Sign up

Export Citation Format

Share Document