An Analytical Study on Green Cloud Computing for Reducing Carbon Footprint in Modern IT Infrastructure

George Sebastian; Sanjay Menon; Deepak Nair; Ajith Kumar; Varghese David

doi:https://doi.org/10.47001/ICJES/2026.502003

Authors

George Sebastian

Department of Computer Applications, Mar Athanasius College of Engineering, Kothamangalam, Kerala, India

Sanjay Menon

Department of Computer Applications, Mar Athanasius College of Engineering, Kothamangalam, Kerala, India

Deepak Nair

Department of Computer Applications, Mar Athanasius College of Engineering, Kothamangalam, Kerala, India

Ajith Kumar

Department of Computer Applications, Mar Athanasius College of Engineering, Kothamangalam, Kerala, India

Varghese David

Department of Computer Applications, Mar Athanasius College of Engineering, Kothamangalam, Kerala, India

Abstract

Green cloud computing pertains to the design, execution, and utilization of cloud infrastructures and services that prioritize energy efficiency and environmental sustainability. This paper examines the ways in which green cloud computing contributes to the reduction of the carbon footprint associated with data centers, the cutting-edge technologies and strategies employed, practical applications by prominent industry leaders, the advantages and obstacles encountered, and the prospective future. Through the adoption of environmentally friendly practices, cloud computing can persist in facilitating digital transformation while reducing ecological damage.

Keywords

Green Cloud Computing design execution utilization cloud infrastructures energy efficiency environmental sustainability cloud computing ecological damage

Citation of this Article

George Sebastian, Sanjay Menon, Deepak Nair, Ajith Kumar, & Varghese David. (2026). An Analytical Study on Green Cloud Computing for Reducing Carbon Footprint in Modern IT Infrastructure. International Current Journal of Engineering and Science (ICJES), 5(2), 10-14. Article DOI: https://doi.org/10.47001/ICJES/2026.502003

References

Buamona, N. Q., Hamid, M., & Gunawan, E. (2023). Analisis Dan Implmentasi Keamanan Jaringan Menggunakan Metode DHCP Snooping dan Swirch Port Security. Jurnal Teknik Informatika (J-Tifa), 6(1), 23-31.
Dave, D., Sawhney, G., Aggarwal, P., Silswal, N., & Khut, D. (2023). The new frontier of cybersecurity: emerging threats and innovations. 2023 29th International Conference on Telecommunications (ICT).
Doshi, R., Apthorpe, N., & Feamster, N. (2018). Machine learning DDoS detection for consumer internet of things devices. In IEEE Security and Privacy Workshops (SPW) (pp. 29-35).
Gupta, N., Jindal, V., & Bedi, P. (2023). A Survey on Intrusion Detection and Prevention Systems. SN Computer Science, 4(5), 439.
Li, X., Jiang, P., Chen, T., Luo, X., & Wen, Q. (2018). A survey on the security of blockchain systems. Future Generation Computer Systems, 87, 841-853.
Mallik, A., Ahsan, A., Shahadat, M. M., & Tsou, J. C. (2019). Man-in-the-middle-attack: Understanding in simple words. International Journal of Data and Network Science, 3(2), 77-92.
Nirwan, S., & Dhaliwal, B. K. (2023). A Comprehensive Study Cyber Attacks and Countermeasures. 2023 International Conference on Inventive Computation Technologies (ICICT).
Pandey, P. (2013). Prevention of ARP spoofing: A probe packet based technique. 2013 3rd IEEE international advance computing conference (IACC).
Prasad, A., & Chandra, S. (2022). Defending arp spoofing-based mitm attack using machine learning and device profiling. 2022 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS).
Salifu, W. (2012). Authentication protocols for computer and network security. International Journal of Computer Applications, 45(9), 17-24.
Scarfone, K., & Mell, P. (2007). Guide to intrusion detection and prevention systems (IDPS) (NIST Special Publication 800-94). National Institute of Standards and Technology.
Song, W., Beshley, M., Przystupa, K., Beshley, H., Kochan, O., Pryslupskyi, A., Pieniak, D., & Su, J. (2020). A software deep packet inspection system for network traffic analysis and anomaly detection. Sensors, 20(6), 1637.
Sowah, R. A., Ofori-Amanfo, K. B., Mills, G. A., & Koumadi, K. M. (2019). Detection and prevention of man-in-the-middle spoofing attacks in MANETs using predictive techniques in artificial neural networks. Journal of Computer Networks and Communications, 2019, 1-14.
Tamsir Ariyadi, T. (2022). Desain keamanan DHCP snooping untuk mengurangi serangan Local Area Network (LAN). DESAIN KEAMANAN DHCP SNOOPING UNTUK MENGURANGI SERANGAN LOCAL AREA NETWORK (LAN).
Tetteh, S. G. (2024). A Systematic Performance Review of Security Methods for the Cyberworld. Asian Journal of Research in Computer Science, 17(5), 10-18.
Thankappan, M., Rifà-Pous, H., & Garrigues, C. (2022). Multi-Channel Man-in-the-Middle attacks against protected Wi-Fi networks: A state of the art review. Expert Systems with Applications, 210, 118401.
Thankappan, M., Rifà-Pous, H., & Garrigues, C. (2024). A signature-based wireless intrusion detection system framework for multi-channel man-in-themiddle attacks against protected Wi-Fi networks. IEEE Access.

[1] Buamona, N. Q., Hamid, M., & Gunawan, E. (2023). Analisis Dan Implmentasi Keamanan Jaringan Menggunakan Metode DHCP Snooping dan Swirch Port Security. Jurnal Teknik Informatika (J-Tifa), 6(1), 23-31.

[2] Dave, D., Sawhney, G., Aggarwal, P., Silswal, N., & Khut, D. (2023). The new frontier of cybersecurity: emerging threats and innovations. 2023 29th International Conference on Telecommunications (ICT).

[3] Doshi, R., Apthorpe, N., & Feamster, N. (2018). Machine learning DDoS detection for consumer internet of things devices. In IEEE Security and Privacy Workshops (SPW) (pp. 29-35).

[4] Gupta, N., Jindal, V., & Bedi, P. (2023). A Survey on Intrusion Detection and Prevention Systems. SN Computer Science, 4(5), 439.

[5] Li, X., Jiang, P., Chen, T., Luo, X., & Wen, Q. (2018). A survey on the security of blockchain systems. Future Generation Computer Systems, 87, 841-853.

[6] Mallik, A., Ahsan, A., Shahadat, M. M., & Tsou, J. C. (2019). Man-in-the-middle-attack: Understanding in simple words. International Journal of Data and Network Science, 3(2), 77-92.

[7] Nirwan, S., & Dhaliwal, B. K. (2023). A Comprehensive Study Cyber Attacks and Countermeasures. 2023 International Conference on Inventive Computation Technologies (ICICT).

[8] Pandey, P. (2013). Prevention of ARP spoofing: A probe packet based technique. 2013 3rd IEEE international advance computing conference (IACC).

[9] Prasad, A., & Chandra, S. (2022). Defending arp spoofing-based mitm attack using machine learning and device profiling. 2022 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS).

[10] Salifu, W. (2012). Authentication protocols for computer and network security. International Journal of Computer Applications, 45(9), 17-24.

[11] Scarfone, K., & Mell, P. (2007). Guide to intrusion detection and prevention systems (IDPS) (NIST Special Publication 800-94). National Institute of Standards and Technology.

[12] Song, W., Beshley, M., Przystupa, K., Beshley, H., Kochan, O., Pryslupskyi, A., Pieniak, D., & Su, J. (2020). A software deep packet inspection system for network traffic analysis and anomaly detection. Sensors, 20(6), 1637.

[13] Sowah, R. A., Ofori-Amanfo, K. B., Mills, G. A., & Koumadi, K. M. (2019). Detection and prevention of man-in-the-middle spoofing attacks in MANETs using predictive techniques in artificial neural networks. Journal of Computer Networks and Communications, 2019, 1-14.

[14] Tamsir Ariyadi, T. (2022). Desain keamanan DHCP snooping untuk mengurangi serangan Local Area Network (LAN). DESAIN KEAMANAN DHCP SNOOPING UNTUK MENGURANGI SERANGAN LOCAL AREA NETWORK (LAN).

[15] Tetteh, S. G. (2024). A Systematic Performance Review of Security Methods for the Cyberworld. Asian Journal of Research in Computer Science, 17(5), 10-18.

[16] Thankappan, M., Rifà-Pous, H., & Garrigues, C. (2022). Multi-Channel Man-in-the-Middle attacks against protected Wi-Fi networks: A state of the art review. Expert Systems with Applications, 210, 118401.

[17] Thankappan, M., Rifà-Pous, H., & Garrigues, C. (2024). A signature-based wireless intrusion detection system framework for multi-channel man-in-themiddle attacks against protected Wi-Fi networks. IEEE Access.