پژوهشنامه پردازش و مدیریت اطلاعات

پژوهشنامه پردازش و مدیریت اطلاعات

Achieving Sustainability in Computing by Minimizing Data Center Carbon Footprints

نوع مقاله : مقاله پژوهشی

نویسندگان
1 Al-Turath University, Baghdad 10013, Iraq
2 Al-Mansour University College, Baghdad 10067, Iraq
3 Osh State University, Osh City 723500, Kyrgyzstan
4 Al-Rafidain University College Baghdad 10064, Iraq
5 5Madenat Alelem University College, Baghdad 10006, Iraq
چکیده
Background: The exponential growth of data centers has significantly increased their carbon footprint, raising concerns about their environmental impact. As the demand for digital services and cloud computing intensifies, sustainable computing practices have become crucial for mitigating climate change.
Objective: This paper aims to explore strategies for reducing the carbon footprint of data centers by integrating sustainable computing practices, including energy-efficient hardware, renewable energy sources, and optimized cooling technologies.
Methods: A comprehensive review of existing literature was conducted, along with an analysis of case studies from major technology firms employing green computing strategies. Data center energy consumption patterns and carbon emissions were evaluated using energy efficiency metrics such as Power Usage Effectiveness (PUE) and Carbon Usage Effectiveness (CUE).
Results: Findings indicate that adopting energy-efficient hardware, coupled with renewable energy sources, can significantly reduce energy consumption and carbon emissions. Optimized cooling techniques, such as liquid cooling and free-air cooling, further contribute to energy savings. Companies employing these practices reported a reduction in carbon emissions by up to 30%.
Conclusion: Sustainable computing practices offer a viable path for reducing the environmental impact of data centers. By prioritizing energy efficiency and renewable energy integration, data centers can minimize their carbon footprint while maintaining operational efficiency, thus contributing to global sustainability goals.
کلیدواژه‌ها

عنوان مقاله English

Achieving Sustainability in Computing by Minimizing Data Center Carbon Footprints

نویسندگان English

Hayder Abdulameer Yousif 1
Abdulsatar Shaker Salman 2
Tazhikbaeva Sanaiym Toygonbaevna 3
Rana Khudhair Abbas Ahmed 4
Riyam M. Alsammarraie 5
1 Al-Turath University, Baghdad 10013, Iraq
2 Al-Mansour University College, Baghdad 10067, Iraq
3 Osh State University, Osh City 723500, Kyrgyzstan
4 Al-Rafidain University College Baghdad 10064, Iraq
5 5Madenat Alelem University College, Baghdad 10006, Iraq
چکیده English

Background: The exponential growth of data centers has significantly increased their carbon footprint, raising concerns about their environmental impact. As the demand for digital services and cloud computing intensifies, sustainable computing practices have become crucial for mitigating climate change.
Objective: This paper aims to explore strategies for reducing the carbon footprint of data centers by integrating sustainable computing practices, including energy-efficient hardware, renewable energy sources, and optimized cooling technologies.
Methods: A comprehensive review of existing literature was conducted, along with an analysis of case studies from major technology firms employing green computing strategies. Data center energy consumption patterns and carbon emissions were evaluated using energy efficiency metrics such as Power Usage Effectiveness (PUE) and Carbon Usage Effectiveness (CUE).
Results: Findings indicate that adopting energy-efficient hardware, coupled with renewable energy sources, can significantly reduce energy consumption and carbon emissions. Optimized cooling techniques, such as liquid cooling and free-air cooling, further contribute to energy savings. Companies employing these practices reported a reduction in carbon emissions by up to 30%.
Conclusion: Sustainable computing practices offer a viable path for reducing the environmental impact of data centers. By prioritizing energy efficiency and renewable energy integration, data centers can minimize their carbon footprint while maintaining operational efficiency, thus contributing to global sustainability goals.

کلیدواژه‌ها English

Sustainable computing
data centers
carbon footprint
energy efficiency
renewable energy
cooling technologies
Power Usage Effectiveness (PUE)
Carbon Usage Effectiveness (CUE)
green computing
environmental impact

References

Benblidia, M. A., Brik, B., Esseghir, M., Merghem-Boulahia, L. (2022). Power Allocation and Energy Cost Minimization in Cloud Data Centers Microgrids: A Two-Stage Optimization Approach. IEEE Access, 10, 66213-66226. https://doi.org/:10.1109/ACCESS.2022.3184721
Bharany, S., Sharma, S., Khalaf, O. I.,, and Abdulsahib, G. M., Al Humaimeedy, A. S., Aldhyani, T. H. H., Maashi, M.. Alkahtani, H. (2022). A Systematic Survey on Energy-Efficient Techniques in Sustainable Cloud Computing. Sustainability, 14 (10). https://doi.org/:10.3390/su14106256
da Silva, M. D. M., Gamatié, A., Sassatelli, G., Poss, M., Robert. M. (2023). Optimization of Data and Energy Migrations in Mini Data Centers for Carbon-Neutral Computing.  IEEE Transactions on Sustainable Computing, 8 (1), 68-81. https://doi.org/:10.1109/TSUSC.2022.3197090
Heydari, A., Eslami, B., Radmard, V., Rebarber, F., Buell, T., Gray, K., Sather, S., & Rodriguez, J. (2022). Power Usage Effectiveness Analysis of a High-Density Air-Liquid Hybrid Cooled Data Center.  ASME 2022 International Technical Conference and Exhibition on Packaging and Integration of Electronic and Photonic Microsystems. https://doi.org/:10.1115/IPACK2022-97447
Höb, M., & Kranzlmüller, D. (2023). Enable Energy Efficient Data Centers. Proceedings of the HPC Asia 2023 Workshops, Singapore. https://doi.org/:10.1145/3581576.3581601
Huang, X., Yan, J., Zhou, X., Wu, Y., & Hu, S. (2023). Cooling Technologies for Internet Data Center in China: Principle, Energy Efficiency, and Applications. Energies, 16 (20). https://doi.org/:10.3390/en16207158
Jawad, A. M., Al-Aameri, M. G., & Qasim, N. H. (2023). Emerging Technologies and Applications of Wireless Power Transfer. Transport Development, 4 (19). https://doi.org/:10.33082/td.2023.4-19.12
Kaur, K., Garg, S., Aujla, G. S., Kumar, N., and Zomaya, A. Y. (2022). A Multi-Objective Optimization Scheme for Job Scheduling in Sustainable Cloud Data Centers.  IEEE Transactions on Cloud Computing, 10 (1), 172-186. https://doi.org/:10.1109/TCC.2019.2950002
Lin, W. T., Chen, G., and Li, H. (2023). Carbon-Aware Load Balance Control of Data Centers With Renewable Generations.  IEEE Transactions on Cloud Computing, 11 (2), 1111-1121. https://doi.org/:10.1109/TCC.2022.3150391
Liu, J., Xu, Z., Wu, J., Liu, K., Sun, X., and Guan, X. (2023). Optimal Planning of Internet Data Centers Decarbonized by Hydrogen-Water-Based Energy Systems.  IEEE Transactions on Automation Science and Engineering, 20 (3), 1577-1590. https://doi.org/:10.1109/TASE.2022.3213672
McMullen, M., and Wemhoff, A. P. (2023). Data Center Environmental Burden Reduction Through On-Site Renewable Power Generation.  ASME 2023 17th International Conference on Energy Sustainability, 5 (2), 021001 https://doi.org/:10.1115/1.4065053
Mondal, S., Faruk, F. B., Rajbongshi, D., Efaz, M. M., and Islam, M. M. (2023). GEECO: Green Data Centers for Energy Optimization and Carbon Footprint Reduction. Sustainability, 15 (21). https://doi.org/:10.3390/su152115249
Murino, T., Monaco, R., Nielsen, Per S., Liu, X., Esposito, G.,Scognamiglio, C. (2023). Sustainable Energy Data Centres: A Holistic Conceptual Framework for Design and Operations. Energies, 16 (15). https://doi.org/:10.3390/en16155764
Osibo, B., and Adamo, S. (2023). Data Centers and Green Energy: Paving the Way for a Sustainable Digital Future.  International Journal of Latest Technology in Engineering, Management & Applied Science, 12 (11), 15-30. https://doi.org/:10.51583/IJLTEMAS.2023.121103
Qasim, N., and Pyliavskyi, V. (2020). Color temperature line: forward and inverse transformation.  Semiconductor physics, quantum electronics and optoelectronics, 23, 75-80. https://doi.org/:10.15407/spqeo23.01.075
Qasim, N., Shevchenko, Y.P., and Pyliavskyi, V. (2019). Analysis of methods to improve energy efficiency of digital broadcasting.  Telecommunications and Radio Engineering, 78 (16), 1457-1469. https://doi.org/:10.1615/TelecomRadEng.v78.i16.40
Qasim, N. H., Salman, A. J., Salman, H. M., AbdelRahman, A. A., and Kondakova, A. (2024). Evaluating NB-IoT within LTE Networks for Enhanced IoT Connectivity.  35th Conference of Open Innovations Association (FRUCT), 552-559. https://doi.org/:10.23919/FRUCT61870.2024.10516400
Ran, Y., Hu, H., Wen, Y., and Zhou, X. (2023). Optimizing Energy Efficiency for Data Center via Parameterized Deep Reinforcement Learning.  IEEE Transactions on Services Computing, 16 (2), 1310-1323. https://doi.org/:10.1109/TSC.2022.3184835
Sviridov, A. N., and Demkin, V. I. (2022). ANALYSIS OF INCREASING THE DATA CENTERS ENERGY EFFICIENCY METHODS.  Modern High Technologies, 2, 110-115. https://doi.org/:10.17513/snt.39044
Wan, J., Duan, Y., Gui, X., Liu, C., Li, L., and Ma, Z. (2023). SafeCool: Safe and Energy-Efficient Cooling Management in Data Centers With Model-Based Reinforcement Learning.  IEEE Transactions on Emerging Topics in Computational Intelligence, 7 (6), 1621-1635. https://doi.org/:10.1109/TETCI.2023.3234545
Xu, S., Zhang, H., and Wang, Z. (2023). Thermal Management and Energy Consumption in Air, Liquid, and Free Cooling Systems for Data Centers: A Review. Energies, 16 (3). https://doi.org/:10.3390/en16031279
Yousif, O., Dawood, M., Jassem, F. T., and Qasim, N. H. (2024). Curbing crypto deception: evaluating risks, mitigating practices and regulatory measures for preventing fraudulent transactions in the middle east.  Encuentros: Revista de Ciencias Humanas, Teoría Social y Pensamiento Crítico, (22), 311-334. https://doi.org/:10.5281/zenodo.13732337
Zhang, Y., and Liu, J. (2022). Prediction of Overall Energy Consumption of Data Centers in Different Locations. Sensors, 22 (10). https://doi.org/:10.3390/s22103704