Proceedings of the First International Conference on Science, Engineering and Technology Practices for Sustainable Development, ICSETPSD 2023, 17th-18th November 2023, Coimbatore, Tamilnadu, India

Research Article

Energy Efficient Coding Practices for Sustainable Software Development

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  • @INPROCEEDINGS{10.4108/eai.17-11-2023.2342635,
        author={R  Manimegalai and Srivatsan  Sandhanam and A Sunitha Nandhini and Priyam  Pandia},
        title={Energy Efficient Coding Practices for Sustainable Software Development},
        proceedings={Proceedings of the First International Conference on Science, Engineering and Technology Practices for Sustainable Development, ICSETPSD 2023, 17th-18th November 2023, Coimbatore, Tamilnadu, India},
        publisher={EAI},
        proceedings_a={ICSETPSD},
        year={2024},
        month={1},
        keywords={cloud computing energy-efficient coding standards sustainable software development},
        doi={10.4108/eai.17-11-2023.2342635}
    }
    
  • R Manimegalai
    Srivatsan Sandhanam
    A Sunitha Nandhini
    Priyam Pandia
    Year: 2024
    Energy Efficient Coding Practices for Sustainable Software Development
    ICSETPSD
    EAI
    DOI: 10.4108/eai.17-11-2023.2342635
R Manimegalai1,*, Srivatsan Sandhanam2, A Sunitha Nandhini1, Priyam Pandia2
  • 1: PSG Institute of Technology and Applied Research
  • 2: SAP Labs India
*Contact email: drrm@psgitech.ac.in

Abstract

Cloud computing has revolutionized the IT landscape, offering unparalleled scalability and flexibility to both businesses and end-users. But there's growing concern about how much electricity cloud data centers consume. The increasing need for cloud services has made it imperative to conduct research on maximizing energy efficiency in cloud computing. This research study compares two different applications to examine energy-efficient coding methods in cloud computing and provides an overview of current green data center architecture aspects. The goal of this effort is to pinpoint procedures that can drastically lower energy usage in cloud environments. The two main steps in the suggested methodology are as follows. Initially, the energy usage is evaluated for two distinct programs that are operating in a cloud environment. First, the energy consumption is assessed for two different applications running in a cloud environment: Application-A coded in JavaScript, which utilizes conventional coding practices, and Application-B coded in Java, which integrates advanced energy-efficient coding techniques. Both applications are subjected to a series of experiments to measure power consumption and performance metrics, to quantify the energy savings achieved by Application-B which employs energy efficient coding practices. Second, coding practices employed in each application are explored to identify key differences that contribute to their varying energy efficiency.