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Software Greenability: A Case Study of Cloud-Based Business Applications Provisioning

Abstract : The emission of CO2 due to ICT (Information and Communication Technologies) is found as equivalent to aviation sector. Although the energy consumption in ICT is due both to hardware and software. In recent decade, the energy efficiency studies focus on the hardware part, especially with the development of cloud computing. Indeed, it is the software application that is responsible for executing tasks, that indirectly affects the hardware energy consumption. This work focus on software energy consumption. We introduce a methodology which evaluates and improves the software greenability by considering its energy consumption, performance and readability. Contrary to existing methodologies, we associate the effect of several components (CPU, memory, disk and network) when estimating software energy consumption instead of considering only the CPU as it is the case in literature. Moreover, the proposed framework can dynamically examine source code to integrate some measurement functionality. A Tool to Estimate Energy Consumption (TEEC) is implemented and its applicability is demonstrated on the case of cloud-based business application provisioning software, called MADONA. MADONA allows dynamically generating service-oriented business applications by automatically composing business services and automatically deploying the generated applications on cloud environment.
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Contributor : Catarina Ferreira da Silva Connect in order to contact the contributor
Submitted on : Wednesday, October 3, 2018 - 3:46:37 PM
Last modification on : Saturday, September 11, 2021 - 3:18:56 AM
Long-term archiving on: : Friday, January 4, 2019 - 3:07:30 PM


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Hayri Acar, Hind Benfenatki, Jean-Patrick Gelas, Catarina Ferreira da Silva, Gülfem Alptekin, et al.. Software Greenability: A Case Study of Cloud-Based Business Applications Provisioning. CLOUD 2018 - IEEE 11th International Conference on Cloud Computing, Jul 2018, San Francisco, CA, United States. pp.875-878, ⟨10.1109/CLOUD.2018.00125⟩. ⟨hal-01887065⟩



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