Toward designing a dynamic CPU cap manager for timely dataflow platforms

In this work, we propose a control-based solution for the problem of CPU resource allocation in data-flow platform that considers the degradation of performance caused by running concurrent data-flow processes. Our aim is to cut the QoS violation incidents for applications belonging to the highest QoS class. The performance of the proposed solution is bench-marked with the famous round robin algorithm. The experimental results confirms that the proposed algorithm can decrease the latency of processing data records for applications by 48% compared to the round robin policy.