{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,16]],"date-time":"2026-06-16T14:03:08Z","timestamp":1781618588752,"version":"3.54.5"},"reference-count":24,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,6,16]],"date-time":"2026-06-16T00:00:00Z","timestamp":1781568000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Big Data"],"abstract":"<jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>The rapid growth of artificial intelligence (AI) has significantly increased computing demand, intensifying the operational strain on the computing environment. While virtualization and containerization are established technologies for resource optimization, their comparative energy efficiency and environmental impact, particularly under GPU-accelerated AI workloads, are not well-quantified.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>This study evaluates the energy consumption and environmental impact of virtualization and containerization technologies when using Graphics Processing Units (GPUs) for AI model execution. Employing a computer vision benchmark, the performance, GPU resource utilization, and power consumption were measured. The experiment involved training a DenseNet-121 model on the MNIST dataset within a VirtualBox virtual machine and a Docker container environment.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      The analysis indicates that containerization consistently surpasses virtualization in energy efficiency. Specifically, Docker container configuration demonstrated an approximately 21.6% reduction in total energy consumption, and a corresponding reduction in carbon dioxide (CO\n                      <jats:sub>2<\/jats:sub>\n                      ) emissions compared to a VirtualBox virtual machine. Furthermore, containerization exhibited lower average and peak GPU utilization and power consumption.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Discussion<\/jats:title>\n                    <jats:p>These findings demonstrate that containerization offers a more energy-efficient and environmentally sustainable approach than VirtualBox virtualization for the specific GPU-enabled AI workload evaluated in this study. Statistical significance testing indicates that the observed performance differentials are significant, supporting the validity of the results within the experimental scope of this work.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Implementing containerization in this experimental setup may reduce energy consumption and environmental impact without compromising computational performance. Future studies should extend these analyses to larger neural network models, diverse AI workloads, and heterogeneous GPU platforms to enhance the generalizability of these findings beyond the current single-system experimental configuration.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fdata.2026.1838191","type":"journal-article","created":{"date-parts":[[2026,6,16]],"date-time":"2026-06-16T13:10:53Z","timestamp":1781615453000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Measuring the impact of virtualization and containerization on the environment when using GPUs for processing the AI models"],"prefix":"10.3389","volume":"9","author":[{"given":"Safaa","family":"Hriez","sequence":"first","affiliation":[{"name":"Cyber Security Department, Al Hussein Technical University","place":["Amman, Jordan"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mohammad","family":"Haikal","sequence":"additional","affiliation":[{"name":"SparklyMinds","place":["Amman, Jordan"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,6,16]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"52524","DOI":"10.1109\/ACCESS.2024.3387436","article-title":"Predictive energy management for docker containers in cloud computing: a time series analysis approach","volume":"12","author":"Algarni","year":"2024","journal-title":"IEEE Access"},{"key":"B2","doi-asserted-by":"publisher","first-page":"5533","DOI":"10.1007\/s11276-019-02001-x","article-title":"Reduced carbon emission and optimized power consumption technique using container over virtual machine","volume":"27","author":"Anusooya","year":"2021","journal-title":"Wireless Netw"},{"key":"B3","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3284557.3284738","article-title":"\u201cImpact of virtualization on cloud computing energy consumption: empirical study,\u201d","author":"Atiewi","year":"2018","journal-title":"Proceedings of the 2nd international symposium on computer science and intelligent control"},{"key":"B4","doi-asserted-by":"publisher","first-page":"159548","DOI":"10.1109\/ACCESS.2025.3606932","article-title":"Adaptive energy optimization in cloud computing through containerization","volume":"13","author":"Beena","year":"2025","journal-title":"IEEE Access"},{"key":"B5","volume-title":"Differences in Performance Between Containerization and Virtualization: With a Focus on http Requests","author":"Berggren","year":"2022"},{"key":"B6","year":"2025","journal-title":"What Direct Risks Does ai Pose to the Climate and Environment"},{"key":"B7","author":"Cyril","year":"2021","journal-title":"Containerization of Applications"},{"key":"B8","year":"2025","journal-title":"Global co2 Intensity Is Expected to Fall due to the Rise of Clean Energy"},{"key":"B9","year":"2025","journal-title":"Ai and Climate Change"},{"key":"B10","doi-asserted-by":"publisher","first-page":"1305","DOI":"10.1109\/TCC.2019.2920914","article-title":"An energy and performance aware consolidation technique for containerized datacenters","volume":"9","author":"Khan","year":"2019","journal-title":"IEEE Trans. Cloud Comput"},{"key":"B11","first-page":"844","article-title":"Energy aware resource management for cloud data centers","volume":"14","author":"Kumar","year":"2016","journal-title":"Int. J. Comput. Sci. Inform. Sec"},{"key":"B12","volume-title":"Containers and Virtual Machines: A Performance, Resource and Power Consumption Comparison","author":"Lindstr\u00f6m","year":"2022"},{"key":"B13","doi-asserted-by":"publisher","first-page":"984","DOI":"10.1126\/science.aba3758","article-title":"Recalibrating global data center energy use estimates","volume":"367","author":"Masanet","year":"2020","journal-title":"Science"},{"key":"B14","doi-asserted-by":"publisher","first-page":"522","DOI":"10.1109\/UCC.2015.93","article-title":"\u201cPower consumption of virtualization technologies: an empirical investigation,\u201d","author":"Morabito","year":"","journal-title":"2015 IEEE\/ACM 8th international conference on utility and cloud computing (UCC)"},{"key":"B15","doi-asserted-by":"publisher","first-page":"386","DOI":"10.1109\/IC2E.2015.74","article-title":"\u201cHypervisors vs. lightweight virtualization: a performance comparison,\u201d","author":"Morabito","year":"","journal-title":"2015 IEEE international conference on cloud engineering"},{"key":"B16","doi-asserted-by":"publisher","first-page":"677","DOI":"10.1109\/TCC.2017.2702586","article-title":"Cloud container technologies: a state-of-the-art review","volume":"7","author":"Pahl","year":"2017","journal-title":"IEEE Trans. Cloud Comput"},{"key":"B17","doi-asserted-by":"publisher","first-page":"1419","DOI":"10.1016\/j.procs.2020.04.152","article-title":"Performance evaluation of docker container and virtual machine","volume":"171","author":"Potdar","year":"2020","journal-title":"Proc. Comput. Sci"},{"key":"B18","doi-asserted-by":"publisher","first-page":"697","DOI":"10.1109\/ICCC.2015.7432984","article-title":"\u201cEvaluation of docker containers based on hardware utilization,\u201d","author":"Preeth","year":"2015","journal-title":"2015 International Conference on Control Communication and Computing India (ICCC)"},{"key":"B19","year":"2025","journal-title":"Tech Giants' Indirect Emissions Rose 150"},{"key":"B20","author":"Ruiz","year":"2018","journal-title":"Understanding and Visualizing DenseNets"},{"key":"B21","article-title":"\u201cVirtualization and containerization of application infrastructure: a comparison,\u201d","volume-title":"21st Twente student conference on IT, Vol. 21","author":"Scheepers","year":"2014"},{"key":"B22","doi-asserted-by":"publisher","DOI":"10.1002\/cpe.5693","article-title":"Performance evaluation of containers and virtual machines when running cassandra workload concurrently","author":"Shirinbab","year":"2020","journal-title":"Concurr. Comput.: Pract. Exp"},{"key":"B23","doi-asserted-by":"publisher","first-page":"e3462","DOI":"10.1002\/ett.3462","article-title":"Characterizing the power cost of virtualization environments","volume":"29","author":"Tadesse","year":"2018","journal-title":"Trans. Emerg. Telecommun. Technol"},{"key":"B24","year":"2023","journal-title":"Climate Change and Human Security"}],"container-title":["Frontiers in Big Data"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fdata.2026.1838191\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,6,16]],"date-time":"2026-06-16T13:10:54Z","timestamp":1781615454000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fdata.2026.1838191\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6,16]]},"references-count":24,"alternative-id":["10.3389\/fdata.2026.1838191"],"URL":"https:\/\/doi.org\/10.3389\/fdata.2026.1838191","relation":{},"ISSN":["2624-909X"],"issn-type":[{"value":"2624-909X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,6,16]]},"article-number":"1838191"}}