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            "abstractNote": "In energy-constrained settings, most real-time operating\nsystems take the approach of minimizing the energy\nconsumption while meeting all the task deadlines.\nHowever, it is possible that the available energy budget is\nnot sufficient to meet all deadlines and some deadlines will\ninevitably have to be missed. In this paper, we present a\nframework through which the operating system can select\njobs for execution in order to achieve two alternative\nperformance objectives: 1) maximizing the number of\ndeadlines met , and 2) maximizing the total reward (utility)\nof jobs that meet their deadlines during the operation. We\npresent an optimal algorithm that achieves the first\nobjective. We prove that achieving the latter objective is\nNP-Hard and propose some fast heuristics for this problem.\nWe evaluate the performance of the heuristics through\nsimulation studies.",
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            "abstractNote": "Energy efficient system design is becoming increasingly important with the proliferation\nof portable, battery-operated appliances such as laptops, Personal Digital Assistants\n(PDAs) and cellular phones. Numerous dedicated hardware approaches for energy minimization\nhave been proposed while software energy efficiency has been relatively unexplored.\nSince it is the software that drives the hardware, decisions taken during software\ndesign can have a significant impact on system energy consumption. This thesis explores\navenues for improving system energy efficiency from application level to the operating\nsystem level. The embedded operating system can have a significant impact on system\nenergy by performing dynamic power management both in the active and passive states of\nthe device. Software controlled active power management techniques using dynamic voltage\nand frequency scaling have been explored. Efficient workload prediction strategies\nhave been developed that enable just-in-time computation. An algorithm for efficient realtime\noperating system task scheduling has also been developed that minimizes energy\nconsumption. Portable systems spend a lot of time in sleep mode. Idle power management\nstrategies have been developed that consider the effect of leakage and duty-cycle on system\nlifetime. A hierarchical shutdown approach for systems characterized multiple sleep\nstates has been proposed. Although the proposed techniques are quite general, their applicability\nand utility have been demonstrated using the MIT μAMPS wireless sensor node\nan example system wherever possible. To quantify software energy consumption, an estimation\nframework has been developed based on experiments on the StrongARM and\nHitachi processors. The software energy profiling tool is available on-line. Finally, in\nenergy constrained systems, we would like to have the ability to trade-off quality of service\nfor extended battery life. A scalable approach to application development has been\ndemonstrated that allows energy quality trade-offs.",
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            "extra": "Department of the Built Environment, Eindhoven University of Technology\nP.O. Box 513, 5600 MB, Eindhoven, the Netherlands",
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