0000-0001-9542-652X, Singh, Amit Kumar and Indrusiak, Leandro Soares orcid.org/0000-0002-9938-2920 (2016) Feedback-based admission control for hard real-time task allocation under dynamic workload on many-core systems. Abstract. In hard real-time systems, a computationally expensive schedulability analysis has to be performed for every task. Fulfilling this requirement is particularly tough when system workload and service capacity are not available a priori and thus the analysis has to be conducted at runtime. This paper presents an approach for applying control-theorybased admission control to predict the task schedulability so that the exact schedulability analysis is performed only to the tasks with positive prediction results. In case of a careful fine-tuning of parameters, the proposed approach can be successfully applied even to many-core embedded systems with hard real-time constraints and other time-critical systems. The provided experimental results demonstrate that, on average, only 62% of the schedulability tests have to be performed in comparison with the traditional, open-loop approach. The proposed approach is particularly beneficial for heavier workloads, where the number of executed tasks is almost unchanged in comparison with the traditional open-loop approach. By our approach, only 32% of exact schedulability tests have to be conducted. Moreover, for the analysed industrial workloads with dependent jobs, the proposed technique admitted and executed 11% more tasks while not violating any timing constraints.
Authors of REF target embedded, hard, real-time systems and propose a feedback loop approach using control theory to regulate and fine-tune application admission.
Feedback-Based Admission Control for Hard Real-Time Task Allocation Under Dynamic Workload on Many-Core Systems
ARCS
Computer Science