CMV: Clustered Majority Voting Reliability-Aware Task Scheduling for Multicore Real-Time Systems

This paper proposes a novel reliability-aware hard real-time task scheduling method for multicore systems along with a quantitative reliability model. The proposed method uses a heuristic clustered replication to maintain the desired reliability threshold with both minimum replication overhead and latency increase. It also minimizes intercore communication overhead of tasks. Both single and multiple soft errors are considered in this method. Simulation results showthat the efficiency of our proposed approach improves with larger network-on-chip sizes, higher reliability thresholds, and higher number of tolerating errors. The proposed method achieves near optimal replica overhead (up to 7.3% higher than optimal replica overhead) with up to 2500% time complexity improvement compared to exhaustive exploration. Experimental results also show that the feasibility of the proposed method is higher than the conventional replication method up to 9.3%. All experiments are performed on both synthetic random task graphs and PARSEC real application benchmarks. Obtained task mapping solutions with communication volume reduction and near optimal replica overhead impose negligible latency increase (up to 6.3%) in comparison with the space exploration approach.