Journal
IEEE TRANSACTIONS ON SUSTAINABLE COMPUTING
Volume 3, Issue 3, Pages 167-181Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSUSC.2017.2711362
Keywords
Directed acyclic graph (DAG); dynamic voltage and frequency scaling (DVFS); energy-efficient; fault-tolerant scheduling; heterogeneous distributed embedded systems
Categories
Funding
- National Key Research and Development Plan of China [2016YFB0200405]
- National Natural Science Foundation of China [61672217, 61432005, 61379115, 61402170, 61370097, 61502162, 61502405]
- CERNET Innovation Project [NGII20161003]
- China Postdoctoral Science Foundation [2016M592422]
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Dynamic voltage and frequency scaling (DVFS) is a well-known energy consumption optimization technique in embedded systems and dynamically scaling down the voltage of a chip has been developed to achieve energy-efficient optimization. However, this operation may lead to a sharp rise in transient failures of processors and consequently weaken the reliability of systems. Reliability goal is an important functional safety requirement and must be satisfied for safety-critical applications. In this study, we aim to implement energy-efficient fault-tolerant scheduling for a reliable parallel application on heterogeneous distributed embedded systems, where the parallel application is described by a directed acyclic graph (DAG). An energy-efficient scheduling with a reliability goal (ESRG) algorithm is presented to reduce the energy consumption while satisfying the reliability goal for the parallel application. Considering that the application's reliability goal is unreachable if its reliability goal exceeds a certain threshold via ESRG, we further propose an energy-efficient fault-tolerant scheduling with a reliability goal (EFSRG) algorithm to reduce the energy consumption while satisfying the reliability goal based on an active replication scheme. Experimental results confirm that the energy consumption reduced by the proposed EFSRG algorithm is higher than those reduced by other approaches under different scale conditions.
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