Embedded systems are driving an information revolution with their pervasion in our everyday lives. With more and more different types of FUs available, same type of operations can be processed by heterogeneous FUs with different costs, where the cost may relate to power, reliability, etc. Due to conditional operations, some tasks may not have fixed execution time. Therefore, how to assign a proper FU type to each operation of a system and generate a schedule that minimize the total costs while satisfying timing constraints with guaranteed confidence probabilities becomes a critical issue. This book, 1) proposed several efficient algorithms to solve the problem; 2) combined Dynamic Voltage Scaling (DVS) and soft real-time to solve the Voltage Assignment with Probability (VAP) Problem. 3) applied our efficient algorithms to dynamic adjust the working mode of sensors to save energy for sensor networks; 4) designed rotation scheduling algorithms for real-time applications that produce schedules consuming minimal energy; 5) combined data mining and prefetching to reduce energy consumptions; 6) improved performance and energy consumption for processors with multi-bank memory.
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Embedded systems are driving an information revolution with their pervasion in our everyday lives. With more and more different types of FUs available, same type of operations can be processed by heterogeneous FUs with different costs, where the cost may relate to power, reliability, etc. Due to conditional operations, some tasks may not have fixed execution time. Therefore, how to assign a proper FU type to each operation of a system and generate a schedule that minimize the total costs while satisfying timing constraints with guaranteed confidence probabilities becomes a critical issue. This book, 1) proposed several efficient algorithms to solve the problem; 2) combined Dynamic Voltage Scaling (DVS) and soft real-time to solve the Voltage Assignment with Probability (VAP) Problem. 3) applied our efficient algorithms to dynamic adjust the working mode of sensors to save energy for sensor networks; 4) designed rotation scheduling algorithms for real-time applications that produce schedules consuming minimal energy; 5) combined data mining and prefetching to reduce energy consumptions; 6) improved performance and energy consumption for processors with multi-bank memory.
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Zustand: New. Embedded systems are driving an informationrevolution with their pervasion in our everydaylives. With more and more different types of FUsavailable, same type of operations can be processedby heterogeneous FUs with different costs, where thecost may relate . Artikel-Nr. 4957031
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Taschenbuch. Zustand: Neu. Neuware - Embedded systems are driving an informationrevolution with their pervasion in our everydaylives. With more and more different types of FUsavailable, same type of operations can be processedby heterogeneous FUs with different costs, where thecost may relate to power, reliability, etc. Due toconditional operations, some tasks may not have fixedexecution time. Therefore, how to assign a proper FUtype to each operation of a system and generate aschedule that minimize the total costs whilesatisfying timing constraints with guaranteedconfidence probabilities becomes a critical issue.This book, 1) proposed several efficient algorithmsto solve the problem; 2) combined Dynamic VoltageScaling (DVS) and soft real-time to solve the VoltageAssignment with Probability (VAP) Problem. 3) appliedour efficient algorithms to dynamic adjust theworking mode of sensors to save energy for sensornetworks; 4) designed rotation scheduling algorithmsfor real-time applications that produce schedulesconsuming minimal energy; 5) combined data mining andprefetching to reduce energy consumptions; 6)improved performance and energy consumption forprocessors with multi-bank memory. Artikel-Nr. 9783639096194
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