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Software applications and workloads, especially within the domains of Cloud computing and large-scale AI model training, exert considerable demand on computing resources, thus contributing significantly to the overall energy footprint of the IT industry. In this paper, we present an in-depth analysis of certain software coding practices that can play a substantial role in increasing the application’s overall energy consumption, primarily stemming from the suboptimal utilization of computing resources. Our study encompasses a thorough investigation of 16 distinct code smells and other coding malpractices across 31 real-world open-source applications written in Java and Python. Through our research, we provide compelling evidence that various common refactoring techniques, typically employed to rectify specific code smells, can unintentionally escalate the application’s energy consumption. We illustrate that a discerning and strategic approach to code smell refactoring can yield substantial energy savings. For selective refactorings, this yields a reduction of up to 13.1% of energy consumption and 5.1% of carbon emissions per workload on average. These findings underscore the potential of selective and intelligent refactoring to substantially increase energy efficiency of Cloud software systems.
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Roles of the Web in Commercial Energy Efficiency: IoT, Cloud Computing, and Opinion Mining
The overconsumption of energy in recent times has motivated many studies. Some of these explore the application of web technologies and machine learning models, aiming to increase energy efficiency and reduce the carbon footprint. This paper aims to review three areas that overlap between the web and energy usage in the commercial sector: IoT (Internet of Things), cloud computing and opinion mining. The paper elaborates on problems in terms of their causes, influences, and potential solutions, as found in multiple studies across these areas; and intends to identify potential gaps with the scope for further research. In the rapidly digitizing and automated world, these three areas can offer much contribution towards reducing energy consumption and making the commercial sector more energy efficient. IoT and smart manufacturing can assist much in effective production, and more efficient technologies as per energy usage. Cloud computing, with reference to its impact on green IT (information technology), is a major area that contributes towards the mitigation of carbon footprint and the reduction of costs on energy consumption. Opinion mining is significant as per the part it plays in understanding the feelings, requirements and demands of the consumers of energy as well as the related stakeholders, so as to help create more suitable policies and hence navigate towards more energy efficient strategies. This paper offers comprehensive analyses on the literature in the concerned areas to fathom the current status and explore future possibilities of research across these areas and the related multidisciplinary avenues.
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- Award ID(s):
- 2018575
- PAR ID:
- 10570636
- Publisher / Repository:
- ACM
- Date Published:
- Journal Name:
- ACM SIGWEB Newsletter
- Volume:
- 2023
- Issue:
- Autumn
- ISSN:
- 1931-1745
- Page Range / eLocation ID:
- 1 to 16
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1145/3631358.3631363
