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https://doi.org/10.1007/978-3-642-38827-9_28
Title: | Estimating operating system process energy consumption in real time | Authors: | Dutta, K. Singh, V.K. VanderMeer, D. |
Keywords: | Energy Operating Systems Power Meter SVM Model |
Issue Date: | 2013 | Citation: | Dutta, K.,Singh, V.K.,VanderMeer, D. (2013). Estimating operating system process energy consumption in real time. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 7939 LNCS : 400-404. ScholarBank@NUS Repository. https://doi.org/10.1007/978-3-642-38827-9_28 | Abstract: | The power consumption in data centers due to Information and Communication Technologies (ICT) is significant across the globe. With recent developments in Service Oriented Architecture (SOA), we notice a paradigm shift in computing. Desktops (PCs) and laptops are being replaced by smart phones and tablets. A major impact of this architecture is a shift of computing resources from personal desktops and laptops to centralized server farms. This implies increases in power consumption in the large-scale servers used in these infrastructures. In such a scenario, optimizing the IT resources for power consumption is a necessity. The first step of such an optimization at the application level is the knowledge of how much energy the application is consuming. A major challenge in this domain is to develop a software-based energy metering tool that can measure the energy consumptions at the OS process level. We have developed an OS process-level power metering tool that can accurately estimate the energy usage based on system resource usages, and demonstrated that our tool provides energy measurement for complex e-business applications with greater than 95% accuracy. © 2013 Springer-Verlag. | Source Title: | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | URI: | http://scholarbank.nus.edu.sg/handle/10635/124008 | ISBN: | 9783642388262 | ISSN: | 03029743 | DOI: | 10.1007/978-3-642-38827-9_28 |
Appears in Collections: | Staff Publications |
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