TA-HRT: A Temperature-Aware Scheduler for Heterogeneous Real-Time Multicore Systems

Abstract

Over the years, the nature of processing platforms is witnessing a significant shift in most of the battery supported real-time systems, which currently underpins a blend of specific multicores to satisfy the needs of present day applications. Devising temperature-aware schedulers has become a critical issue for such kind of systems. Hence, this research presents a heuristic strategy named TA-HRT, for temperature-aware scheduling of a set of real-time periodic tasks on a heterogeneous multicore platform. The presented strategy operates in three stages, namely Deadline Partitioning, Core Clustering and Temperature-Aware Task Scheduling. Our experimental analysis shows that the presented strategy not only improves upon the state-of-the-art [1] in terms of resource utilisation (as high as 10.71%) but also reduces average temperatures of cores in the system.