PROJECT TITLE :
Run-Time Management for Multicore Embedded Systems With Energy Harvesting
In this paper, we have a tendency to propose a completely unique framework for runtime energy and workload management in multicore embedded systems with solar energy harvesting and a periodic laborious real-time task set because the workload. Compared with previous work, our framework makes several novel contributions and possesses many advantages, including the subsequent: 1) a semidynamic scheduling heuristic that dynamically adapts to runtime harvested power variations without losing the consistency of periodic tasks; a pair of) a battery–supercapacitor hybrid energy storage module for a lot of efficient system energy management; 3) a coarse-grained core shutdown heuristic for additional energy saving; four) energy budget designing and task allocation heuristics with process variation tolerance; five) a novel twin-speed method specifically designed for periodic tasks to handle discrete frequency levels and dynamic voltage/frequency scaling switching overhead at the core level; and half dozen) an extension to prepare the system for thermal issues arising at runtime during extreme environmental conditions. The experimental studies show that our framework leads to a discount in task miss rate by up to 70% and task miss penalty by up to sixty five% compared with the simplest known previous work.
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