Soft and Hard Reliability-Aware Scheduling for Multicore Embedded Systems with Energy Harvesting

For multicore embedded systems powered by energy harvesting, it is necessary to develop intelligent resource allocation techniques that adjust the application execution strategy on-the-fly to adapt to changing energy supply from the harvesting system. To cope with the complexity of managing applications with data dependencies on such systems, we propose a hybrid design-time/run-time framework for resource allocation that takes into consideration variations in solar radiance and execution time, transient faults, and permanent faults due to aging effects. Our framework generates schedule templates at design-time with an emphasis on energy efficiency and uses lightweight online management schemes to react to run-time system dynamics. Experimental results indicate that our framework presents improvements in performance and adaptivity, with up to 23.2 percent miss rate reduction compared to prior work, 43.6 percent performance benefits from adaptive run-time workload management, and up to 24.5 percent expected system lifetime improvement with aging-aware allocation of workload partitions.