Peng, Z., Barzegar, B., Yarahmadi, M., Motameni, H. and Pirouzmand, P. (2020) Energy-Aware Scheduling of Workflow Using a Heuristic Method on Green Cloud. Scientific Programming, 2020, Article ID: 8898059.
https://doi.org/10.1155/2020/8898059

has been cited by the following article:

• TITLE: Green Software Engineering: A Study on Energy-Efficient Design and Deployment in Cloud Infrastructure

  AUTHORS: Jianian Jin, Enkai Ji, Qun Zhang

  KEYWORDS: Green Software Engineering, Energy-Efficient Design, Cloud Infrastructure, Sustainability, Resource Management, Cloud Computing, Energy Consumption, Eco-Friendly Software, Green IT

  JOURNAL NAME: Journal of Data Analysis and Information Processing, Vol.13 No.3, July 28, 2025

  ABSTRACT: In the face of growing concerns over environmental sustainability, green software engineering has emerged as a crucial discipline within cloud computing to reduce energy consumption and minimize environmental impact. Cloud data centers, which host a large portion of modern computing infrastructure, are significant contributors to global energy consumption. As cloud adoption increases, so does the need for energy-efficient systems. This paper reviews energy-efficient design and deployment strategies within cloud infrastructure, focusing on how green software engineering practices can optimize resource usage and reduce carbon footprints. The paper explores various energy-saving technologies, including virtualization, dynamic resource allocation, and energy-aware scheduling, and evaluates their effectiveness in reducing cloud infrastructure energy demands. The challenges and limitations of implementing green software engineering practices in cloud systems are also discussed, with insights into future research directions for more sustainable cloud computing.