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Journal articles on the topic 'Energy efficiency in Data Centers'

Author: Grafiati

Published: 3 June 2025

Last updated: 1 August 2025

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1

Chong, Frederic T., Martijn J. R. Heck, Parthasarathy Ranganathan, Adel A. M. Saleh, and Hassan M. G. Wassel. "Data Center Energy Efficiency:Improving Energy Efficiency in Data Centers Beyond Technology Scaling." IEEE Design & Test 31, no. 1 (2014): 93–104. http://dx.doi.org/10.1109/mdat.2013.2294466.

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Redondo Gil, Carlos. "Energy Efficiency in Data Processing Centers." Renewable Energy and Power Quality Journal 1, no. 08 (2010): 1051–60. http://dx.doi.org/10.24084/repqj08.580.

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3

Doty, Steve. "Energy Efficiency In Computer Data Centers." Energy Engineering 103, no. 5 (2006): 50–76. http://dx.doi.org/10.1080/01998590609509477.

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4

Abdullah, Hamed AlQahtani. "Waste Energy in Data Centers." International Journal of Computer Science and Information Technology Research 11, no. 3 (2023): 172–75. https://doi.org/10.5281/zenodo.8383544.

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<strong>Abstract:</strong> Data centres are the backbone of the digital age, powering the storage and processing of vast amounts of information. However, their relentless demand for energy has raised concerns about environmental sustainability. This essay explores the concept of waste energy in data centres as a promising solution to mitigate their environmental footprint and improve overall energy efficiency. The exponential growth of data centre operations has led to significant energy consumption, resulting in carbon emissions and resource depletion. To address these challenges, data centre

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5

Hernandez, Lenonel, Genett Jimenez, and Piedad Marchena. "Energy Efficiency Metrics of University Data Centers." Knowledge Engineering and Data Science 1, no. 2 (2018): 64. http://dx.doi.org/10.17977/um018v1i22018p64-73.

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The data centers are fundamental pieces in the network and computing infrastructure, and evidently today more than ever they are relevant. Since they support the processing, analysis, assurance of the data generated in the network and by the applications in the cloud, which every day increases its volume thanks to technologies such as Internet of Things, Virtualization, and cloud computing, among others. Precisely the management of this large volume of information makes the data centers consume a lot of energy, generating great concern to owners and administrators. Green Data Centers offer a s

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Karamat Khan, Tehmina, Mohsin Tanveer, and Asadullah Shah. "Energy Efficiency in Virtualized Data Center." International Journal of Engineering & Technology 7, no. 4.15 (2018): 315. http://dx.doi.org/10.14419/ijet.v7i4.15.23019.

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Industrial and academic communities have been trying to get more computational power out of their investments. Data centers have recently received huge attention due to its increased business value and achievable scalability on public/private clouds. Infra-structure and applications of modern data center is being virtualized to achieve energy efficient operation on servers. Despite of data center advantages on performance, there is a tradeoff between power and performance especially with cloud data centers. Today, these cloud application-based organizations are facing many energy related chall

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Fernández-Cerero, Damián, Alejandro Fernández-Montes, and Francisco Velasco. "Productive Efficiency of Energy-Aware Data Centers." Energies 11, no. 8 (2018): 2053. http://dx.doi.org/10.3390/en11082053.

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Information technologies must be made aware of the sustainability of cost reduction. Data centers may reach energy consumption levels comparable to many industrial facilities and small-sized towns. Therefore, innovative and transparent energy policies should be applied to improve energy consumption and deliver the best performance. This paper compares, analyzes and evaluates various energy efficiency policies, which shut down underutilized machines, on an extensive set of data-center environments. Data envelopment analysis (DEA) is then conducted for the detection of the best energy efficiency

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Hamann, H. F., T. G. van Kessel, M. Iyengar, et al. "Uncovering energy-efficiency opportunities in data centers." IBM Journal of Research and Development 53, no. 3 (2009): 10:1–10:12. http://dx.doi.org/10.1147/jrd.2009.5429023.

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V, Amarnath, Mallikarjuna K, Nagendra J, Umesha D M, and Nalina V. "Review on Energy Efficiency Green Data Centers." International Journal of Recent Engineering Science 5, no. 2 (2018): 21–26. http://dx.doi.org/10.14445/23497157/ijres-v5i2p105.

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Digra, Lakshmi, and Sharanjeet Singh. "Survey on Energy Efficiency in Cloud Computing." Asian Journal of Computer Science and Technology 8, no. 1 (2019): 18–21. http://dx.doi.org/10.51983/ajcst-2019.8.1.2125.

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Data centers are serious, energy-hungry infrastructures that can run large scale Internet based services. Energy ingesting representations are essential in designing and improving energy-efficient operations to reduce excessive energy consumption in data centers. This paper presents a survey on Energy efficiency in data centers, importance of energy efficiency. It also describes the increasing demands for data center in worldwide and the reasons for data centers energy inefficient? In this paper we define the challenges for implementing changes in data centers and explain why and how the energ

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Gizli, Volkan, and Jorge Marx Gómez. "A Framework to Optimize Energy Efficiency in Data Centers Based on Certified KPIs." Technologies 6, no. 3 (2018): 87. http://dx.doi.org/10.3390/technologies6030087.

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Both electricity consumption and CO2 emission from Germany’s 50,000 data centers have grown continuously in recent years. However, projects that can be used to evaluate the energy efficiency of data centers are no longer available to companies. Thus, there is a need for solid solutions that are going to help data center operators to assess and improve a data center’s energy efficiency. A particular approach in the form of an evolutionary prototype, which is described in this article, is designed to serve as a basis for the development of the software, which will support companies in addressing

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Pawlish, Michael, Aparna S. Varde, Stefan A. Robila, and Anand Ranganathan. "A call for energy efficiency in data centers." ACM SIGMOD Record 43, no. 1 (2014): 45–51. http://dx.doi.org/10.1145/2627692.2627703.

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13

Kanthed, Surbhi. "Energy-Saving Practices in Data Centers." International Journal of Multidisciplinary Research and Growth Evaluation 4, no. 5 (2023): 1149–55. https://doi.org/10.54660/.ijmrge.2023.4.5.1149-1155.

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Data centers are vital to the digital economy but consume significant amounts of electrical energy, highlighting the need for more sustainable operational practices. This paper examines contemporary energy-saving solutions for data centers, emphasizing empirical strategies rather than theoretical discussions. Key methods include advanced cooling approaches (e.g., hot/cold aisle containment, economizer-based “free cooling,” and liquid immersion cooling), server optimization techniques (such as virtualization, containerization, and intelligent power management), and improvements in power distrib

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14

Morchapure, Soham V., and Snehal V. Raut. "Study of Green Computing." International Journal of Ingenious Research, Invention and Development (IJIRID) 3, no. 6 (2024): 599–604. https://doi.org/10.5281/zenodo.14576293.

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<em>Green Computing is an evolving practice that focuses on developing and managing information processing systems to enhance energy efficiency. Although initiatives like Energy Star have existed since the early 1990s, the increasing concerns about climate change and the energy crisis have sparked a renewed focus on sustainable computing solutions. Data centers play a major role in energy consumption, requiring power not only to run systems but also to maintain effective cooling mechanisms. This paper introduces an innovative strategy to optimize energy usage in data centers. The approach dyna

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Liu, Jun, Longchuan Yan, Chengxu Yan, et al. "Escope: An Energy Efficiency Simulator for Internet Data Centers." Energies 16, no. 7 (2023): 3187. http://dx.doi.org/10.3390/en16073187.

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Contemporary megawatt-scale data centers have emerged to meet the increasing demand for online cloud services and big data analytics. However, in such large-scale data centers, servers of different generations are installed gradually year by year, making the data center heterogeneous in computing capability and energy efficiency. Furthermore, due to different processor architectures, complex and diverse load dynamic changing, business coupling, and other reasons, operators pay great attention to processor hardware power consumption and server aggregation energy efficiency. Therefore, the simul

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Shenoy, Prashant. "Energy-Efficiency versus Carbon-Efficiency." ACM SIGEnergy Energy Informatics Review 2, no. 4 (2022): 1–2. http://dx.doi.org/10.1145/3584024.3584025.

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Improving the energy-efficiency of computing systems has been the focus of computer science research for many decades. In the data center domain, for example, there has been an intense focus on improving energy efficiency by improving the Power Usage Effectiveness (PUE) of data centers. Other domains such as civil and mechanical engineering have also focused on improving the energy efficiency of built environments such as buildings. More recently, there has been an increased emphasis on sustainability on the human-built infrastructure of various kinds motivated by climate change, which has res

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Paneru, Dinesh Raj, Madhu B. R., and Santosh Naik. "A SURVEY FOR ENERGY EFFICIENCY IN CLOUD DATA CENTERS." International Journal of Research -GRANTHAALAYAH 5, no. 4RACSIT (2017): 63–68. http://dx.doi.org/10.29121/granthaalayah.v5.i4racsit.2017.3353.

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Services such as Platform as a Service (PaaS), Infrastructure as a Service (IaaS) and Software as a Service (SaaS) are provided by Cloud Computing. Subscription based computing resources and storage is offered in cloud. Cloud Computing is boosted by Virtualization technology. To move running applications or VMs starting with one physical machine then onto the next, while the customer is associated is named as Live VM migration. VM migration is empowered by means of Virtualization innovation to adjust stack in the server farms. Movement is done fundamentally to deal with the assets progre

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Sviridov, A. N., and V. I. Demkin. "ANALYSIS OF INCREASING THE DATA CENTERS ENERGY EFFICIENCY METHODS." Современные наукоемкие технологии (Modern High Technologies), no. 2 2022 (2022): 110–15. http://dx.doi.org/10.17513/snt.39044.

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19

Salman Qadri. "Traffic Intensity Based Energy Efficiency Architecture for Data-Centers." Lahore Garrison University Research Journal of Computer Science and Information Technology 5, no. 1 (2021): 55–70. http://dx.doi.org/10.54692/lgurjcsit.2021.0501177.

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The world is moving towards cost-effective and time-constrained solutions. The uses of applications and automated devices have been growing day by day. In computing, resources available in personal computers are limited due to less storage capacity and lower computation speeds. Using all applications on personal systems may not be cost-effective. Therefore, the trends of online storage and computing have become popular. On the other hand, there must be some serving end for these users. One of the major issues, due to the growth of data centers is the increase in power usage of a larger number

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20

Sharma, Ankita, and Upinder Pal Singh. "Energy Efficiency in Cloud Data Centers Using Load Balancing." International Journal of Computer Trends and Technology 11, no. 4 (2014): 174–81. http://dx.doi.org/10.14445/22312803/ijctt-v11p137.

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21

Loper, Joe, and Sara Parr. "Energy efficiency in data centers: A new policy frontier." Environmental Quality Management 16, no. 4 (2007): 83–97. http://dx.doi.org/10.1002/tqem.20144.

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Dinesh, Raj Paneru, B. R. Madhu, and Naik Santosh. "A SURVEY FOR ENERGY EFFICIENCY IN CLOUD DATA CENTERS." International Journal of Research - Granthaalayah 5, no. 4 (2017): 63–68. https://doi.org/10.5281/zenodo.572297.

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Services such as Platform as a Service (PaaS), Infrastructure as a Service (IaaS) and Software as a Service (SaaS) are provided by Cloud Computing. Subscription based computing resources and storage is offered in cloud. Cloud Computing is boosted by Virtualization technology. To move running applications or VMs starting with one physical machine then onto the next, while the customer is associated is named as Live VM migration. VM migration is empowered by means of Virtualization innovation to adjust stack in the server farms. Movement is done fundamentally to deal with the assets progressivel

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23

Nasser, Alkhaldi. "Ghost Servers in Data Centers." International Journal of Computer Science and Information Technology Research 11, no. 2 (2023): 100–104. https://doi.org/10.5281/zenodo.8001240.

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<strong>Abstract:</strong> This article examines the value of researching ghost servers in data centers and offers details on the effects, detection methods, and mitigation techniques related to these unused or underutilized servers. Ghost servers, which use resources without producing anything, have grown to be a problem in data center settings, resulting in higher energy use, resource waste, and financial repercussions. The introduction defines ghost servers and explores their causes, which include outmoded management techniques, ineffective resource management, and server sprawl. Due to its

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Qiu, Yeliang, Congfeng Jiang, Yumei Wang, Dongyang Ou, Youhuizi Li, and Jian Wan. "Energy Aware Virtual Machine Scheduling in Data Centers." Energies 12, no. 4 (2019): 646. http://dx.doi.org/10.3390/en12040646.

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Power consumption is a primary concern in modern servers and data centers. Due to varying in workload types and intensities, different servers may have a different energy efficiency (EE) and energy proportionality (EP) even while having the same hardware configuration (i.e., central processing unit (CPU) generation and memory installation). For example, CPU frequency scaling and memory modules voltage scaling can significantly affect the server’s energy efficiency. In conventional virtualized data centers, the virtual machine (VM) scheduler packs VMs to servers until they saturate, without con

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Xu, Yongmei, Jingru Zhang, Yuhui Deng, Lan Du, and Rong Jiao. "Analyzing the Cooling Efficiency of the Thermal Environment in Data Centers." International Journal of Grid and High Performance Computing 6, no. 4 (2014): 15–27. http://dx.doi.org/10.4018/ijghpc.2014100102.

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Given the explosive growth of data, scalability and fault tolerance have become a fundamental challenge for data center network structures. Temperature in data centers significantly affects the failure ratio of high-speed network devices. Various types of air distribution schemes influence the temperature of network equipment differently, and the cooling cost in data centers dominates the overall energy cost. On the basis of the energy efficiency of cooling systems, this study analyzes and compares the thermal load distribution in the enclosure of standard and non-standard data centers by cons

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Bhardwaj, Rakhi, R. Padmavathy, M. Preetha, et al. "EMS for Sustainable Data Centers." E3S Web of Conferences 591 (2024): 01006. http://dx.doi.org/10.1051/e3sconf/202459101006.

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With the rapid expansion of cloud computing, data centers have become one of the largest consumers of energy globally. To achieve energy efficiency and sustainability, integrating renewable energy sources such as solar and wind into the energy management system (EMS) of data centers has become essential. This paper proposes an intelligent EMS framework designed for sustainable data centers, which dynamically balances energy loads between renewable energy generation, battery storage, and grid supply. The system optimizes energy consumption by leveraging real-time data from renewable sources, mi

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Li, Yang Ping, Shao Fen Zhong, Xiao Heng Pan, and Hua Qiang Yuan. "Energy-Efficient Data Processing in Cloud Computing Centers." Advanced Materials Research 910 (March 2014): 397–400. http://dx.doi.org/10.4028/www.scientific.net/amr.910.397.

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Rapid growth in the cloud computing centers worldwide is posing serious challenges to both hardware and software designers on the energy efficiency issues. This paper explores particular challenges and potential promises on the part of data processing in these centers.

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Tarahomi, Mehran, and Mohammad Izadi. "Energy efficiency in virtual machines allocation for cloud data centers with lottery algorithm." International Journal of Electrical and Computer Engineering (IJECE) 9, no. 1 (2019): 546–53. https://doi.org/10.11591/ijece.v9i1.pp546-553.

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Energy usage of data centers is a challenging and complex issue because computing applications and data are growing so quickly that increasingly larger servers and disks are needed to process them fast enough within the required time period. In the past few years, many approaches to virtual machine placement have been proposed. This study proposes a new approach for virtual machine allocation to physical hosts. Either minimizes the physical hosts and avoids the SLA violation. The proposed method in comparison to the other algorithms achieves better results.

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Marina, Zapater, L. Risco-Martín José, Arroba Patricia, L. Ayala José, M. Moya José, and Hermida Román. "Runtime data center temperature prediction using Grammatical Evolution techniques." Applied Soft Computing 49 (December 1, 2016): 94–107. https://doi.org/10.1016/j.asoc.2016.07.042.

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Data Centers are huge power consumers, both because of the energy required for computation and the cooling needed to keep servers below thermal redlining. The most common technique to minimize cooling costs is increasing data room temperature. However, to avoid reliability issues, and to enhance energy efficiency, there is a need to predict the temperature attained by servers under variable cooling setups. Due to the complex thermal dynamics of data rooms, accurate runtime data center temperature prediction has remained as an important challenge. By using Grammatical Evolution techniques, this

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Al-Fatlawi, Ahmed Abdulhassan, and Israa Al-Barazanchi. "A novel approach for new architecture for green data centre." Bulletin of Electrical Engineering and Informatics 12, no. 1 (2023): 411–17. http://dx.doi.org/10.11591/eei.v12i1.4421.

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The massive energy usage of data centers may be traced in part to the growing number of data centers and workstations because of economies of scale for cloud computing. It does, though, indicate wasteful power usage. Consequently, researching ways to improve the energy efficiency of datacenter equipment is now a crucial aspect in reducing datacenter power consumption. In this study, we describe methodologies and algorithms for flexible, energy-efficient, and effective load balancing in data centers, resulting in lower energy consumption by systems. Because of difficulties related with energy c

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Nathany, Deepika. "Energy-Efficient Data Centers: A Supply Chain Approach to Sustainability." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 05, no. 06 (2021): 1–7. https://doi.org/10.55041/ijsrem8912.

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The increasing global demand for data storage and processing due to the explosion of artificial intelligence and cloud computing has led to the exponential growth in energy consumption of data centers. Traditional data centers incur high operational costs due to their inefficient infrastructure and power intensive cooling methods. This research explores the role of supply chain management in optimizing energy efficiency in data centers and how optimizing supply chains can contribute to energy efficiency and reduction in carbon footprint. It examines sustainable practices, including modular des

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32

Pokathota, Lingamurthy. "Energy Consumption and Cooling Efficiency Strategies in Data Centers: A Review." Journal of Energy Research and Reviews 17, no. 7 (2025): 125–33. https://doi.org/10.9734/jenrr/2025/v17i7438.

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Data centres require energy to power their computing equipment as well as to maintain proper environmental conditions through their extensive cooling systems. Data centres are a key part of digital infrastructure, but use a lot of energy, especially for cooling and computing. This paper explores energy trends and reviews solutions like CRAC systems, chilled water cooling, and free cooling. It also discusses energy efficiency using measures like Power Usage Effectiveness (PUE) and shows real examples of improvement. The goal is to help design greener, more efficient data centres. The research i

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Onyinyechukwu Chidolue, Peter Efosa Ohenhen, Aniekan Akpan Umoh, Bright Ngozichukwu, Adetomilola Victoria Fafure, and Kenneth Ifeanyi Ibekwe. "GREEN DATA CENTERS: SUSTAINABLE PRACTICES FOR ENERGY-EFFICIENT IT INFRASTRUCTURE." Engineering Science & Technology Journal 5, no. 1 (2024): 99–114. http://dx.doi.org/10.51594/estj.v5i1.730.

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The digital age has led to a surge in connectivity, innovation, and information exchange, but it has also led to escalating energy consumption by data centers. Green data centers have emerged as a transformative solution, embodying a commitment to sustainability through eco-friendly practices and cutting-edge technologies. Key principles of green data centers include energy-efficient hardware, renewable energy integration, advanced cooling systems, and resource optimization strategies. Energy-efficient hardware involves replacing outdated servers, storage systems, and network equipment with en

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Ashok, Kumar Kalyanam. "Optimizing Data Centers through IoT A Comprehensive Overview (The Future of Connected Data Centers)." International Journal on Science and Technology 14, no. 4 (2023): 1–12. https://doi.org/10.5281/zenodo.14613855.

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IoT has actually revolutionized the data centers through introducing innovations related to automation, efficiency, and real-time decision-making. The article probes into how IoT has actually integrated into the data center to ensure its transformation to a very optimally operating entity. IoT data centers will leverage sensors, data analytics platforms, automated control systems, and edge computing to improve monitoring, resource allocation, and energy management. The benefits provided by the integration of IoT range from energy efficiency to reduced operational costs, along with better scala

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Dehkordi, Zahra Ghoreishi, and Hassan Ali Shirazi. "The Strategic Plan Founded on Efficiency of Using Green Computing Techniques in Data Centers." COMPUSOFT: An International Journal of Advanced Computer Technology 03, no. 08 (2014): 1038–47. https://doi.org/10.5281/zenodo.14752158.

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The ever-increasing costs of supplying energy as a part of total costs of any project and their environmental impacts have turned into a real challenge for IT industry and data centers in particular which are considered information processing and storage centers in IT industry which consume lots of energy. The need to optimize energy consumption is felt due to relatively fixed accessible energy sources, ever-increasing need to develop green data centers and expansion of existing centers. The present study aims at providing a standard strategy to reduce energy consumption and devastating impact

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Yadav, Rahul, Weizhe Zhang, Keqin Li, Chuanyi Liu, and Asif Ali Laghari. "Managing overloaded hosts for energy-efficiency in cloud data centers." Cluster Computing 24, no. 3 (2021): 2001–15. http://dx.doi.org/10.1007/s10586-020-03182-3.

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Chi, Ce, Fa Zhang, Kaixuan Ji, Avinab Marahatta, and Zhiyong Liu. "Improving energy efficiency in colocation data centers for demand response." Sustainable Computing: Informatics and Systems 29 (March 2021): 100476. http://dx.doi.org/10.1016/j.suscom.2020.100476.

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Balaras, Constantinos A., John Lelekis, Elena G. Dascalaki, and Dimitris Atsidaftis. "High Performance Data Centers and Energy Efficiency Potential in Greece." Procedia Environmental Sciences 38 (2017): 107–14. http://dx.doi.org/10.1016/j.proenv.2017.03.091.

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Sebagenzi, Jason*1 &. Suchithra. R2. "COMPARATIVE STUDYOF SCHEDULING OF ENERGY EFFICIENCY IN CLOUD DATA CENTERS." GLOBAL JOURNAL OF ENGINEERING SCIENCE AND RESEARCHES 6, no. 1 (2019): 22–29. https://doi.org/10.5281/zenodo.2532816.

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A long time ago, cloud data centers accounted problems of offline and online process. This paper, is oriented on elaboration, utilization and comparison of offline and online scheduling which is the crucial point in all the systems.  The conception and comparative study has been developed, and algorithms of scheduling are demonstrated in detail in the present paper. At the end, the analysis and the performance evaluation of those algorithms by simulation are also shown in order to be used.

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Chinnici, Andrea, Eyvaz Ahmadzada, Ah-Lian Kor, et al. "Towards Sustainability and Energy Efficiency Using Data Analytics for HPC Data Center." Electronics 13, no. 17 (2024): 3542. http://dx.doi.org/10.3390/electronics13173542.

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High-performance computing (HPC) in data centers increases energy use and operational costs. Therefore, it is necessary to efficiently manage resources for the sustainability of and reduction in the carbon footprint. This research analyzes and optimizes ENEA HPC data centers, particularly the CRESCO6 cluster. The study starts by gathering and cleaning extensive datasets consisting of job schedules, environmental conditions, cooling systems, and sensors. Descriptive statistics accompanied with visualizations provide deep insight into collated data. Inferential statistics are then used to invest

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Mondal, Sudipto, Fashat Bin Faruk, Dibosh Rajbongshi, Mohammad Masum Khondhoker Efaz, and Md Motaharul Islam. "GEECO: Green Data Centers for Energy Optimization and Carbon Footprint Reduction." Sustainability 15, no. 21 (2023): 15249. http://dx.doi.org/10.3390/su152115249.

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Cloud computing has revolutionized data storage, processing, and access in modern data center operations. Conventional data centers use enormous amounts of energy for server operation, power supply, and cooling. The processors produce heat while processing the data and therefore increase the center’s carbon footprint, and the rising energy usage and carbon emissions caused by data centers pose serious environmental challenges. Under these circumstances, energy-efficient green data centers are being used as a phenomenal source of sustainable modernization. This study proposes the implementation

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M, Kishore Kumar, and Rahul Pawar. "Energy-Efficient Cloud Data Centers Strategies for Sustainability and Environmental Impact." International Journal of Innovative Research in Computer and Communication Engineering 12, no. 03 (2024): 1779–82. http://dx.doi.org/10.15680/ijircce.2024.1203067.

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As the insatiable thirst for cloud computing services intensifies, data centers grapple with an exponentially growing energy appetite, casting a long shadow on environmental sustainability. This research paper delves into the critical issue of energy efficiency within cloud data centers, aiming to identify strategies that mitigate environmental consequences while ensuring optimal performance. The study reviews current practices in cloud infrastructure, analyzes the challenges associated with energy consumption, and proposes innovative solutions for enhancing the sustainability of data centers.

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Nishant, Kumar, Raj Kumar Dr., and Mayank Aggrawal Dr. "Energy Efficient DVFS with VM Migration." European Journal of Advances in Engineering and Technology 5, no. 1 (2018): 61–68. https://doi.org/10.5281/zenodo.10701884.

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<strong>ABSTRACT </strong> Cloud Computing offers efficient computing with Pay-as-you-go models. It is now easy for consumer to start without need of initial setup, which saves a lot of infrastructure cost. As consumers are subscribing to the cloud, the load is increasing on the data centers, thus data centers are in need for more resources and more power. And all this process is increasing the carbon footprint and polluting environment. Now the time has come when we require efficiency in term of power. We really need to look for mechanism how the power can me be managed to be more efficient.

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Mrs.Manjushree, Hingamire-Zope, and Vadali Mr.Ramkrishna. "Energy Aware Green Computing Model for Data Centers." Journal of Computer Based Parallel Programming 3, no. 3 (2018): 20–25. https://doi.org/10.5281/zenodo.1494016.

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Cloud computing is widely used era providing ITservices for 24*7. In IT service business expansion the data centers are playing a vital role. As business demands are expanding the data centers usage are increased. The energy consumption by these centers is focus for many research studies. The impact of energy consumption is affecting environment with carbon emission. The increase in temperature is another issue caused by Data centers. The energy management should be conducted properly with some techniques to reduce energy consumption. Green computing technologies will definitely support to ste

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Anish Alex. "Sustainable energy strategies for data centers in the AI era." World Journal of Advanced Engineering Technology and Sciences 15, no. 2 (2025): 001–7. https://doi.org/10.30574/wjaets.2025.15.2.0471.

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This article addresses the critical challenge of integrating sustainable energy solutions into data centers amid the explosive growth of artificial intelligence and cloud computing. As computational demands intensify, data centers face unprecedented energy consumption challenges, necessitating innovative approaches to renewable energy adoption. The article examines diverse renewable energy sources, including solar, wind, geothermal, hydropower, and biomass, highlighting their applicability and efficiency in data center environments. Energy storage technologies and grid integration strategies a

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Butwall, Mani, and Rajesh Rajaan. "DESIGNING SUSTAINABLE DATA CENTERS FOR GREEN COMPUTING." COMPUSOFT: An International Journal of Advanced Computer Technology 13 (November 25, 2024): 4021–23. https://doi.org/10.5281/zenodo.15087328.

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The proliferation of data centers worldwide has raised critical concerns regarding their environmental impact. As demand for computational resources grows, data centers have become significant contributors to energy consumption and greenhouse gas emissions. This paper outlines a conceptual framework for designing sustainable data centers, focusing on energy efficiency, renewable energy integration, and innovative cooling technologies. The framework emphasizes scalable modular architecture, intelligent workload distribution, and industry collaboration to achieve carbon-neutral and environmental

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H.L., Phalachandra, and Sitaram Dinkar. "Optimizing Energy Efficiencies in Cloud Data Center Resources with Availability Constraints." International Journal of Engineering and Advanced Technology (IJEAT) 9, no. 3 (2020): 1406–15. https://doi.org/10.35940/ijeat.C4746.029320.

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Cloud infrastructure Resources hosted in Data Centers, support the effective execution of Cloud computing applications. Given the increased adoption of the Cloud Computing Applications and the Businesses getting to be Data-driven, there is a huge increase in the number of Data Centers and the Size and amount of resources hosted in these Data Centers. These Data Center resources consume a significant amount of energy and this continuous scaling of the resources is leading to increased power consumption and a large carbon footprint. Given our fragile eco-system, optimization of the Data Center r

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Researcher. "LEVERAGING AI AND ML TO REVOLUTIONIZE ENERGY EFFICIENCY IN DATA CENTERS." International Journal of Computer Engineering and Technology (IJCET) 15, no. 4 (2024): 370–83. https://doi.org/10.5281/zenodo.13269832.

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This article explores the transformative impact of Artificial Intelligence (AI) and Machine Learning (ML) on energy efficiency in data centers. It examines various areas where these technologies drive significant improvements, including predictive analytics, dynamic cooling management, smart workload scheduling, automated peak shaving, real-time optimization, enhanced maintenance strategies, and holistic system integration. Implementing AI/ML solutions optimizes operational costs and contributes to sustainability efforts by reducing the overall carbon footprint of data center facilities. Throu

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Chi, Ce, Kaixuan Ji, Penglei Song, et al. "Cooperatively Improving Data Center Energy Efficiency Based on Multi-Agent Deep Reinforcement Learning." Energies 14, no. 8 (2021): 2071. http://dx.doi.org/10.3390/en14082071.

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The problem of high power consumption in data centers is becoming more and more prominent. In order to improve the energy efficiency of data centers, cooperatively optimizing the energy of IT systems and cooling systems has become an effective way. In this paper, a model-free deep reinforcement learning (DRL)-based joint optimization method MAD3C is developed to overcome the high-dimensional state and action space problems of the data center energy optimization. A hybrid AC-DDPG cooperative multi-agent framework is devised for the improvement of the cooperation between the IT and cooling syste

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Isaev, E. A., V. V. Kornilov, and A. A. Grigoriev. "Data Center Efficiency Model: A New Approach and the Role of Artificial Intelligence." Mathematical Biology and Bioinformatics 18, no. 1 (2023): 215–27. http://dx.doi.org/10.17537/2023.18.215.

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Bioinformatics technologies play a significant and growing role in life science research, and as these technologies develop, so does the complexity of data. The challenge of biological data growth has given rise to a number of bioinformatics data centers that offer services and solutions ranging from large-scale biosystems analyze that accounts for entire OMICs to nanoscale experiments where molecular modeling can provide insight o structure and dynamics of molecular complexes of biological components. Obviously, this kind of research requires a highly specialized level of computational and st

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