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|Title:||Estimating the energy consumption of executing software processes||Authors:||Singh, V.K.
|Issue Date:||2013||Citation:||Singh, V.K.,Dutta, K.,VanderMeer, D. (2013). Estimating the energy consumption of executing software processes. Proceedings - 2013 IEEE International Conference on Green Computing and Communications and IEEE Internet of Things and IEEE Cyber, Physical and Social Computing, GreenCom-iThings-CPSCom 2013 : 94-101. ScholarBank@NUS Repository. https://doi.org/10.1109/GreenCom-iThings-CPSCom.2013.40||Abstract:||Power consumption in data centers is significant across the globe. The use of cloud-based services, e.g., infrastructure as a service and software as a service (such as Google Docs, Microsoft Office 365, Salesforce.com), is becoming a standard practice in modern IT frameworks. This paradigm shift in the IT industry indicates that the demand for data-center-based services will continue to increase in the future, with concomitant increases in power consumption. In such a scenario, optimizing the IT resources to improve energy efficiency is a necessity. The first step of such an optimization at the application level is knowing how much energy an application is consuming. One of the main challenges in this domain is developing a software-based energy metering tool that can measure an OS processes' energy consumption. Many existing solutions depend on an external watt-meter or other hardware-based enhancements, these are not practical for real-world use in data centers. To overcome the limitations of existing solutions, we have developed an OS process-level power metering tool that can accurately estimate the energy usage of each OS process running on a Linux server without an online watt-meter. Based on a set of experiments, we demonstrated that our method and implementation provides energy consumption estimation for complex e-business applications with above 95% accuracy. © 2013 IEEE.||Source Title:||Proceedings - 2013 IEEE International Conference on Green Computing and Communications and IEEE Internet of Things and IEEE Cyber, Physical and Social Computing, GreenCom-iThings-CPSCom 2013||URI:||http://scholarbank.nus.edu.sg/handle/10635/128457||ISBN:||9780769550466||DOI:||10.1109/GreenCom-iThings-CPSCom.2013.40|
|Appears in Collections:||Staff Publications|
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