Customer-aware resource overallocation to improve energy efficiency in realtime Cloud Computing data centers

2011 ◽  
Author(s):  
Ismael Solis Moreno ◽  
Jie Xu
Keyword(s):  
Energy Efficiency ◽  
Cloud Computing ◽  
Data Centers ◽  
Improve Energy Efficiency

WIRELESS SENSOR NETWORKS TO IMPROVE ENERGY EFFICIENCY IN DATA CENTERS

2021 ◽  
pp. 163-174
Author(s):  
Levente Klein ◽  
Sergio Bermudez ◽  
Fernando Marianno ◽  
Hendrik Hamann
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Centers ◽  
Wireless Sensor ◽  
Improve Energy Efficiency

scholarly journals Multi-Objective Service Placement Scheme Based on Fuzzy-AHP System for Distributed Cloud Computing

2019 ◽  
Vol 9 (17) ◽  
pp. 3550 ◽  
Author(s):  
A-Young Son ◽  
Eui-Nam Huh
Keyword(s):  
Energy Efficiency ◽  
Cloud Computing ◽  
Response Time ◽  
Data Centers ◽  
Cloud Data ◽  
Multi Objective ◽  
Service Placement ◽  
Service Response Time ◽  
Cloud Data Centers ◽  
Distributed Cloud

With the rapid increase in the development of the cloud data centers, it is expected that massive data will be generated, which will decrease service response time for the cloud data centers. To improve the service response time, distributed cloud computing has been designed and researched for placement and migration from mobile devices close to edge servers that have secure resource computing. However, most of the related studies did not provide sufficient service efficiency for multi-objective factors such as energy efficiency, resource efficiency, and performance improvement. In addition, most of the existing approaches did not consider various metrics. Thus, to maximize energy efficiency, maximize performance, and reduce costs, we consider multi-metric factors by combining decision methods, according to user requirements. In order to satisfy the user’s requirements based on service, we propose an efficient service placement system named fuzzy- analytical hierarchical process and then analyze the metric that enables the decision and selection of a machine in the distributed cloud environment. Lastly, using different placement schemes, we demonstrate the performance of the proposed scheme.

scholarly journals The Numerical Simulation of the Airflow Distribution and Energy Efficiency in Data Centers with Three Types of Aisle Layout

2019 ◽  
Vol 11 (18) ◽  
pp. 4937 ◽  
Author(s):  
Jing Ni ◽  
Bowen Jin ◽  
Shanglei Ning ◽  
Xiaowei Wang
Keyword(s):  
Energy Efficiency ◽  
Power Consumption ◽  
Air Conditioning ◽  
Data Centers ◽  
Simulation Method ◽  
Cooling Capacity ◽  
Energy Utilization ◽  
Improve Energy Efficiency ◽  
Electricity Cost ◽  
Airflow Distribution

The energy consumption of fast-growing data centers is drawing attentions from not only energy organizations and institutions all over the world, but also charity groups, such as Greenpeace, and research shows that the power consumption of air conditioning makes up a large proportion of the electricity cost in data centers. Therefore, more detailed investigations of air conditioning power consumption are warranted. Three types of airflow distributions with different aisle layouts (the open aisle, the closed cold aisle, and the closed hot aisle) were investigated with Computational Fluid Dynamics (CFD) methods in a typical data center of four rows of racks in this study. To evaluate the results of thermal and bypass phenomenon, the temperature increase index (β) and the energy utilization index (ηr) were used. The simulations show that there is a better trend of the β index and ηr index both closed cold aisle and closed hot aisle compared with free open aisle. Especially with high air flow rate, the β index decreases and the ηr index increases considerably. Moreover, the results prove the closed aisles (both closed cold aisle and closed hot aisle) can not only significantly improve the airflow distribution, but also reduce the mixture of cold and heat flow, and therefore improve energy efficiency. In addition, it proves the design of the closed aisles can meet the increasing density of installations and our simulation method could evaluate the cooling capacity easily.

Self-Management of Applications and Systems to Optimize Energy in Data Centers

2012 ◽  
pp. 372-394 ◽  
Author(s):  
Frederico Alvares de Oliveira ◽  
Adrien Lèbre ◽  
Thomas Ledoux ◽  
Jean-Marc Menaud
Keyword(s):  
Cloud Computing ◽  
Data Centers ◽  
Performance Metrics ◽  
Scale Up ◽  
Direct Consequence ◽  
Cloud Infrastructure ◽  
Control Loops ◽  
Improve Energy Efficiency ◽  
Energy Footprint ◽  
Cloud Infrastructures

As a direct consequence of the increasing popularity of cloud computing solutions, data centers are growing amazingly and hence have to urgently face with the energy consumption issue. Available solutions are focused basically on the system layer, by leveraging virtualization technologies to improve energy efficiency. Another body of works relies on cloud computing models and virtualization techniques to scale up/down applications based on their performance metrics. Although those proposals can reduce the energy footprint of applications and by transitivity of cloud infrastructures, they do not consider the internal characteristics of applications to finely define a trade-off between applications Quality of Service and energy footprint. In this paper, the authors propose a self-adaptation approach that considers both application internals and system to reduce the energy footprint in cloud infrastructure. Each application and the infrastructure are equipped with control loops, which allow them to autonomously optimize their executions. The authors implemented the control loops and simulated them in order to show their feasibility. In addition, the chapter shows how the solution fits in federated clouds through a motivating scenario. Finally, it provides some discussion about open issues on models and implementation of the proposal.

Energy Efficiency and Air Quality Considerations in Airside Economized Data Centers

2015 ◽  
Author(s):  
Levente J. Klein ◽  
Sergio A. Bermudez ◽  
Fernando J. Marianno ◽  
Hendrik F. Hamann ◽  
Prabjit Singh
Keyword(s):  
Energy Efficiency ◽  
Air Quality ◽  
Data Center ◽  
Data Centers ◽  
High Sensitivity ◽  
Air Cooling ◽  
Improve Energy Efficiency ◽  
Free Air ◽  
Recent Developments ◽  
Contamination Event

Many data center operators are considering the option to convert from mechanical to free air cooling to improve energy efficiency. The main advantage of free air cooling is the elimination of chiller and Air Conditioning Unit operation when outdoor temperature falls below the data center temperature setpoint. Accidental introduction of gaseous pollutants in the data center along the fresh air and potential latency in response of control infrastructure to extreme events are some of the main concerns for adopting outside air cooling in data centers. Recent developments of ultra-high sensitivity corrosion sensors enable the real time monitoring of air quality and thus allow a better understanding of how airflow, relative humidity, and temperature fluctuations affect corrosion rates. Both the sensitivity of sensors and wireless networks ability to detect and react rapidly to any contamination event make them reliable tools to prevent corrosion related failures. A feasibility study is presented for eight legacy data centers that are evaluated to implement free air cooling.

The Issues Of Energy Efficiency In Cloud Computing Based Data Centers

2019 ◽  
Vol 12 (2) ◽  
pp. 485-490
Author(s):  
Anuj Kumar Yadav ◽  
M.L. Garg ◽  
Ritika Ritika
Keyword(s):  
Energy Efficiency ◽  
Cloud Computing ◽  
Data Centers
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