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dc.contributor.authorChen, Jheng-Mingen_US
dc.contributor.authorWang, Kuochenen_US
dc.contributor.authorLin, Ming-Hamen_US
dc.date.accessioned2014-12-08T15:10:38Z-
dc.date.available2014-12-08T15:10:38Z-
dc.date.issued2007en_US
dc.identifier.isbn978-3-540-77091-6en_US
dc.identifier.issn0302-9743en_US
dc.identifier.urihttp://hdl.handle.net/11536/8135-
dc.description.abstractIn spite of numerous inter-task dynamic voltage scaling (DVS) algorithms of real-time systems with either periodic tasks or aperiodic tasks, few of them were aimed at the mixed workload of both kind of tasks. A DVS algorithm for mixed workload real-time systems should not only focus on energy saving, but also should consider low response time of aperiodic tasks. In this paper, we develop an on-line energy efficient scheduling, called Slack Stealing for DVS (SS-DVS), to reduce CPU energy consumption for mixed workload real-time systems under the earliest deadline first (EDF) scheduling policy. The SS-DVS is based on the concept of slack stealing to serve aperiodic tasks and to save energy by using the dynamic reclaiming algorithm (DRA). Unlike other existing approaches, the SS-DVS does not need to know the workload and the worst case execution time of aperiodic tasks in advance. Experimental results show that the proposed SS-DVS obtains better energy reduction (17% similar to 22%) while maintaining the same response time compared to existing approaches.en_US
dc.language.isoen_USen_US
dc.subjectmixed workload real-time systemen_US
dc.subjectinter-task dynamic voltage scalingen_US
dc.subjectslack timeen_US
dc.subjectactual workloaden_US
dc.subjectworst case-execution timeen_US
dc.titleEnergy efficient scheduling for real-time systems with mixed workloaden_US
dc.typeProceedings Paperen_US
dc.identifier.journalEMBEDDED AND UBIQUITOUS COMPUTING, PROCEEDINGSen_US
dc.citation.volume4808en_US
dc.citation.spage33en_US
dc.citation.epage44en_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.identifier.wosnumberWOS:000252267400004-
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