Comparing algorithm for dynamic speed-setting of a low-power CPU
MobiCom '95 Proceedings of the 1st annual international conference on Mobile computing and networking
A Fault-Tolerant Dynamic Scheduling Algorithm for Multiprocessor Real-Time Systems and Its Analysis
IEEE Transactions on Parallel and Distributed Systems
Energy efficient CMOS microprocessor design
HICSS '95 Proceedings of the 28th Hawaii International Conference on System Sciences
Design and Evaluation of a Feedback Control EDF Scheduling Algorithm
RTSS '99 Proceedings of the 20th IEEE Real-Time Systems Symposium
Task Feasibility Analysis and Dynamic Voltage Scaling in Fault-Tolerant Real-Time Embedded Systems
Proceedings of the conference on Design, automation and test in Europe - Volume 2
Feedback EDF Scheduling Exploiting Dynamic Voltage Scaling
RTAS '04 Proceedings of the 10th IEEE Real-Time and Embedded Technology and Applications Symposium
Dual-Processor Design of Energy Efficient Fault-Tolerant System
ASAP '06 Proceedings of the IEEE 17th International Conference on Application-specific Systems, Architectures and Processors
Feedback-controlled reliability-aware power management for real-time embedded systems
Proceedings of the 45th annual Design Automation Conference
RTSS '08 Proceedings of the 2008 Real-Time Systems Symposium
Soft errors issues in low-power caches
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Proceedings of the 48th Design Automation Conference
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Primary-Backup (PB) model has been a widely used model for reliability in dual-processor real-time systems. In recent literature, there have been a few works focussing on minimizing energy consumption of periodic task sets executing on such systems. One of the major drawbacks of these works is that they ignore the effects of frequency-scaling on fault arrival rates. In this paper, we present a modified Primary-Backup model for dual-processor systems that aims to maintain the reliability when employing power management techniques to minimize the overall energy consumption. Furthermore, the proposed approach exploits the uncertainties in the execution time of real-time tasks to better predict the available slack for energy management. The proposed modified PB-based Reliability-Aware Power Management (RAPM) approach was tested with synthetic task sets on both homogeneous and heterogeneous dual-processor systems. Simulation results show that it can achieve up to 67% savings in expected energy consumption for low utilization task sets and up to 32% savings for high utilization task sets without any loss in reliability in heterogeneous dual-processor systems.