Feedback-based admission control for task allocation

This paper presents early exploration of the feedback admission control for high-performance computing clusters executing real-time tasks using controlled values to dynamic task allocation. A number of controller variants with different architectures and relying on various metrics have been proposed. Simulation models of both open- and closed-loop systems have been prepared and compared. The obtained experimental results show that the proposed approach leads to executing almost five times more tasks before their deadlines in case of periodic uniform workload, and about 16% more for bursty workloads with large computation time variance.