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Reducing job migrations is essential for any global multiprocessor scheduling algorithm. In this letter, we present a global, dynamic-priority, laxity-based algorithm that reduces the number of migrations on multiprocessor embedded systems by leveraging information theory principles. A simplification of the proposed scheduling theory is presented to reduce the overhead caused by using information...
The purpose of this paper is to present a scheduling solution based on information theory principles to schedule real-time tasks. We propose the mathematical background for using information as a parameter in real-time systems as well as the relationship between information and utilization. We present a new dynamic priority scheduling solution that selects the task with the highest amount of information...
The purpose of this paper is to present the mathematical background for using entropy in real-time scheduling as well as the relationship between entropy and utilization. We present a new scheduling algorithm based on entropy to schedule tasks in real-time systems. The goal is to minimize the uncertainty of the scheduling problem by executing the task with the highest entropy first without missing...
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