Particle swarm optimization based task scheduling for multi-core systems under aging effect

As the size of the transistor continues to shrink, a number of reliability issues have emerged in network-on-chip (NoC) design. Taking into account the performance degradation induced by Negative Bias Temperature Instability (NBTI) aging effect, this paper proposes an aging-aware task scheduling framework for NoC-based multi-core systems. This framework relies on a NBTI aging model to evaluate the degradation of core's operating frequency to establish the task scheduling model under aging effect. Then, we develop a particle swarm optimization (PSO)-based heuristic to solve the scheduling problem with an optimization objective of total task completion time, and finally obtain a scheduling result with higher efficiency compared with traditional scheduling algorithms without considering of NBTI aging effect. Experiments show that the proposed aging-aware task-scheduling algorithm achieves not only shorter makespan and higher throughput, but also better reliability over non-aging-aware ones.