Please use this identifier to cite or link to this item: https://doi.org/10.1109/RTAS.2006.17
DC FieldValue
dc.titleEstimating the worst-case energy consumption of embedded software
dc.contributor.authorJayaseelan, R.
dc.contributor.authorMitra, T.
dc.contributor.authorLi, X.
dc.date.accessioned2013-07-04T08:39:28Z
dc.date.available2013-07-04T08:39:28Z
dc.date.issued2006
dc.identifier.citationJayaseelan, R.,Mitra, T.,Li, X. (2006). Estimating the worst-case energy consumption of embedded software. Proceedings of the IEEE Real-Time and Embedded Technology and Applications Symposium, RTAS 2006 : 81-90. ScholarBank@NUS Repository. <a href="https://doi.org/10.1109/RTAS.2006.17" target="_blank">https://doi.org/10.1109/RTAS.2006.17</a>
dc.identifier.isbn0769525164
dc.identifier.issn15453421
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/41939
dc.description.abstractThe evolution of battery technology is not being able to keep up with the increasing performance demand of mobile embedded systems. Therefore, battery life has become an important design constraint. As battery-operated embedded devices are deployed in mission critical systems, designers should ensure that the energy constraints are satisfied in addition to the timing constraints - the battery should not drain out before a critical task completes execution. Giving these guarantees requires the knowledge of the worst-case execution time and energy of a task. Significant progress has been made in estimating the worst-case execution time through static analysis. In contrast, existing energy estimation techniques use average-case execution profile of a program and as such cannot guarantee the satisfiability of energy constraints. In this paper, we present a static analysis technique to estimate the worst-case energy consumption of a task on complex micro-architectures. Estimating a bound on energy is non-trivial as it is unsafe to assume any direct correlation with the bound on execution time. Experimental evaluation with a number of benchmark programs indicates the accuracy of our worst-case energy consumption estimates. © 2006 IEEE.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1109/RTAS.2006.17
dc.sourceScopus
dc.typeConference Paper
dc.contributor.departmentCOMPUTER SCIENCE
dc.description.doi10.1109/RTAS.2006.17
dc.description.sourcetitleProceedings of the IEEE Real-Time and Embedded Technology and Applications Symposium, RTAS
dc.description.volume2006
dc.description.page81-90
dc.identifier.isiutNOT_IN_WOS
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