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.
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.
Embedded systems are becoming one of the major driving forces in computer science. Furthermore, it is the impact of embedded information technology that dictates the pace in most engineering ...
Part I: Methods, Models and Tools.- 1. Extending UML for Electronic System Design: A Code Generation Perspective.- 2. Executable Specifications for Heterogeneous Embedded Systems: An Answer to the...
To satisfy the higher requirements of digitally converged embedded systems, this book describes heterogeneous multicore technology that uses various kinds of low-power embedded processor cores on a...
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