2024, Vol. 5, Issue 1, Part A
Carbon footprint reduction in cloud computing: Best practices and emerging trends
Author(s): Meesam Raza, Sakila KS, Sreekala K and Asmaa Mohamad
Abstract: As cloud computing becomes increasingly integral to modern digital infrastructure, its environmental impact, particularly its carbon footprint, has come under scrutiny. This review paper explores best practices and emerging trends aimed at reducing the carbon footprint of cloud computing. The paper begins with an overview of the environmental challenges posed by the energy-intensive nature of data centres, which form the backbone of cloud services. It then delves into effective strategies for mitigating these impacts, including optimizing cooling systems, leveraging renewable energy sources, enhancing server utilization through virtualization, and implementing energy-efficient hardware and software. Furthermore, the paper examines cutting-edge developments such as artificial intelligence for energy management, edge computing, blockchain technology for energy transparency, and the design of sustainable data centres. Case studies from leading tech companies and innovative startups illustrate the practical application of these strategies. Additionally, the review addresses the challenges and barriers to adopting greener cloud practices, including technical, economic, and regulatory hurdles. The paper concludes by highlighting future directions for research and policy recommendations to support sustainable cloud computing. By adopting the discussed best practices and staying abreast of emerging trends, stakeholders can significantly reduce the environmental impact of cloud computing, contributing to broader global efforts to combat climate change.
DOI: 10.33545/27075907.2024.v5.i1a.58Pages: 25-33 | Views: 166 | Downloads: 115Download Full Article: Click Here
How to cite this article:
Meesam Raza, Sakila KS, Sreekala K, Asmaa Mohamad.
Carbon footprint reduction in cloud computing: Best practices and emerging trends. Int J Cloud Comput Database Manage 2024;5(1):25-33. DOI:
10.33545/27075907.2024.v5.i1a.58