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Dr. Dheeraj Mandal
Independent Researcher
Delhi, India
Abstract
In recent years, the rapid growth of data has necessitated the development of sustainable cloud architectures that can effectively handle large-scale data solutions. This paper explores the critical components of building such architectures, focusing on sustainability principles, energy efficiency, scalability, and cost-effectiveness. We analyze existing literature and case studies, identifying best practices and innovative approaches to cloud architecture design. A statistical analysis of current cloud infrastructure usage demonstrates the impact of sustainable practices on performance and cost. The findings highlight the importance of integrating sustainability into cloud strategies, offering a framework for organizations aiming to optimize their data solutions while minimizing environmental impact.
Keywords
Sustainable cloud architectures, large-scale data solutions, energy efficiency, cloud computing, data management, scalability.
References
- Sandeep Dommari. (2023). The Intersection of Artificial Intelligence and Cybersecurity: Advancements in Threat Detection and Response. International Journal for Research Publication and Seminar, 14(5), 530–545. https://doi.org/10.36676/jrps.v14.i5.1639
- Buyya, R., Ilager, S., & Arroba, P. (2023). Energy-Efficiency and Sustainability in New Generation Cloud Computing: A Vision and Directions for Integrated Management of Data Centre Resources and Workloads. arXiv preprint arXiv:2303.10572. org
- Wang, S., Sun, Y., Shi, X., Zhu, S., Ma, L.-T., Zhang, J., Zheng, Y., & Liu, J. (2023). Full Scaling Automation for Sustainable Development of Green Data Centers. arXiv preprint arXiv:2305.00706. org
- Tuli, S., Gill, S. S., Xu, M., Garraghan, P., Bahsoon, R., Dustdar, S., Sakellariou, R., Rana, O., Buyya, R., Casale, G., & Jennings, N. R. (2021). HUNTER: AI-based Holistic Resource Management for Sustainable Cloud Computing. arXiv preprint arXiv:2110.05529. org
- Gill, S. S., & Buyya, R. (2017). A taxonomy and future directions for sustainable cloud computing: 360 degree view. arXiv preprint arXiv:1712.02899. org
- Beloglazov, A., Abawajy, J., & Buyya, R. (2012). Energy-aware resource allocation heuristics for efficient management of data centers for cloud computing. Future Generation Computer Systems, 28(5), 755–768. https://doi.org/10.1016/j.future.2011.04.017 net
- Sun, H., Stolf, P., Pierson, J.-M., & Da Costa, G. (2014). Energy-efficient and thermal-aware resource management for heterogeneous datacenters. arXiv preprint arXiv:1410.3104. org
- Buyya, R., Beloglazov, A., & Abawajy, J. (2010). Energy-efficient management of data center resources for cloud computing: A vision, architectural elements, and open challenges. arXiv preprint arXiv:1006.0308. org
- Liu, N., Li, Z., Xu, Z., Xu, J., Lin, S., Qiu, Q., Tang, J., & Wang, Y. (2017). A hierarchical framework of cloud resource allocation and power management using deep reinforcement learning. arXiv preprint arXiv:1703.04221. org
- Nguyen Quang-Hung, Thoai, N., & Nguyen Thanh Son. (2013). EPOBF: Energy efficient allocation of virtual machines in high performance computing cloud. arXiv preprint arXiv:1310.7801. org
- Acun, B., Lee, B., Kazhamiaka, F., Maeng, K., Chakkaravarthy, M., Gupta, U., Brooks, D., & Wu, C.-J. (2022). Carbon Explorer: A holistic approach for designing carbon aware datacenters. arXiv preprint arXiv:2201.10036. org