Energy-efficient approach to lower the carbon emissions of data centers

被引:0
作者
Rajesh Bose
Sandip Roy
Haraprasad Mondal
Dipan Roy Chowdhury
Srabanti Chakraborty
机构
[1] Simplex Infrastructure Ltd.,
[2] Brainware University,undefined
[3] Dibrugarh University,undefined
[4] Elitte Institute of Engineering and Management,undefined
来源
Computing | 2021年 / 103卷
关键词
Data-center; Distributed computing; Energy consumption; Green computing; Carbon emission; 68U35;
D O I
暂无
中图分类号
学科分类号
摘要
Data Centers require enormous amounts of electrical energy to operate. The resultant emissions in the form of heat, directly, and carbon, indirectly, are cause for concern among Data Center managers and owners. In the past, and in many contemporary instances as well, Data Center managers have struggled to rein in large energy bills as operational activities increased. This paper attempts to address the problems without affecting operational efficiency of Data Centers and while maintaining high standards of system uptime. The latter is made possible by observing a set standard of Power Usage Efficiency and through rationalizing power consumption of equipment and Data Center infrastructure itself. Our research has shown that it is possible to control power consumption, and thus bring about savings in terms of electric bills paid, even when the count of servers in Data Centers racks increase from four to seven. Experiments conducted in the course of our research indicate to maintain a high quality of Data Center operational state and keep power consumption under control even in the wake of rising user numbers. The resultant savings in electrical units consumed, shall ultimately contribute in a small yet meaningful way towards a smaller carbon footprint and a greener planet.
引用
收藏
页码:1703 / 1721
页数:18
相关论文
共 50 条
[31]   Accelerated computation of the genetic algorithm for energy-efficient virtual machine placement in data centers [J].
Zhe Ding ;
Yu-Chu Tian ;
You-Gan Wang ;
Wei-Zhe Zhang ;
Zu-Guo Yu .
Neural Computing and Applications, 2023, 35 :5421-5436
[32]   A Hybrid Genetic Algorithm for the Energy-Efficient Virtual Machine Placement Problem in Data Centers [J].
Tang, Maolin ;
Pan, Shenchen .
NEURAL PROCESSING LETTERS, 2015, 41 (02) :211-221
[33]   Accelerated computation of the genetic algorithm for energy-efficient virtual machine placement in data centers [J].
Ding, Zhe ;
Tian, Yu-Chu ;
Wang, You-Gan ;
Zhang, Wei-Zhe ;
Yu, Zu-Guo .
NEURAL COMPUTING & APPLICATIONS, 2023, 35 (07) :5421-5436
[34]   Multilevel resource allocation for performance-aware energy-efficient cloud data centers [J].
Rossi, Fabio Diniz ;
Severo de Souza, Paulo Silas ;
Marques, Wagner dos Santos ;
Conterato, Marcelo da Silva ;
Ferreto, Tiago Coelho ;
Lorenzon, Arthur Francisco ;
Luizelli, Marcelo Caggiani .
2019 IEEE SYMPOSIUM ON COMPUTERS AND COMMUNICATIONS (ISCC), 2019, :462-467
[35]   Profile-based application assignment for greener and more energy-efficient data centers [J].
Vasudevan, Meera ;
Tian, Yu-Chu ;
Tang, Maolin ;
Kozan, Erhan .
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2017, 67 :94-108
[36]   An electricity price and energy-efficient workflow scheduling in geographically distributed cloud data centers [J].
Hussain, Mehboob ;
Wei, Lian-Fu ;
Rehman, Amir ;
Hussain, Abid ;
Ali, Muqadar ;
Javed, Muhammad Hafeez .
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES, 2024, 36 (08)
[37]   Evaluating power efficient algorithms for efficiency and carbon emissions in cloud data centers: A review [J].
Uddin, Mueen ;
Darabidarabkhani, Yasaman ;
Shah, Asadullah ;
Memon, Jamshed .
RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2015, 51 :1553-1563
[38]   Making the Cloud Energy Efficient An Approach to Make the Data Centers Greener [J].
Aion, Mainul Kabir ;
Bhuiyan, M. N. Abil ;
Jabed, Akib .
2015 4TH INTERNATIONAL CONFERENCE ON INFORMATICS, ELECTRONICS & VISION ICIEV 15, 2015,
[39]   An Energy Efficient VM Migration Algorithm in Data Centers [J].
Wu, Xiaodong ;
Zeng, Yuzhu ;
Lin, Guoxin .
2017 16TH INTERNATIONAL SYMPOSIUM ON DISTRIBUTED COMPUTING AND APPLICATIONS TO BUSINESS, ENGINEERING AND SCIENCE (DCABES), 2017, :27-30
[40]   EPBLA: energy-efficient consolidation of virtual machines using learning automata in cloud data centers [J].
Nayereh Rasouli ;
Ramin Razavi ;
Hamid Reza Faragardi .
Cluster Computing, 2020, 23 :3013-3027