Please use this identifier to cite or link to this item: https://doi.org/10.1007/978-3-642-38827-9_28
DC FieldValue
dc.titleEstimating operating system process energy consumption in real time
dc.contributor.authorDutta, K.
dc.contributor.authorSingh, V.K.
dc.contributor.authorVanderMeer, D.
dc.date.accessioned2016-05-17T10:45:19Z
dc.date.available2016-05-17T10:45:19Z
dc.date.issued2013
dc.identifier.citationDutta, 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. <a href="https://doi.org/10.1007/978-3-642-38827-9_28" target="_blank">https://doi.org/10.1007/978-3-642-38827-9_28</a>
dc.identifier.isbn9783642388262
dc.identifier.issn03029743
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/124008
dc.description.abstractThe 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.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1007/978-3-642-38827-9_28
dc.sourceScopus
dc.subjectEnergy
dc.subjectOperating Systems
dc.subjectPower Meter
dc.subjectSVM Model
dc.typeConference Paper
dc.contributor.departmentINFORMATION SYSTEMS
dc.description.doi10.1007/978-3-642-38827-9_28
dc.description.sourcetitleLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.description.volume7939 LNCS
dc.description.page400-404
dc.identifier.isiutNOT_IN_WOS
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