An Evaluation of Adaptive Partitioning of Real-Time Workloads on Linux

Type of publication
Publication in Conference Proceedings/Workshop
Authors

A. Stevanato, T. Cucinotta, L. Abeni, D. B. de Oliveira.

Conference / Journal
24th IEEE International Symposium on Real-Time Distributed Computing
Publisher
Proceedings of the 24th IEEE International Symposium on Real-Time Distributed Computing
Year of publication
2021
Place of publication
Daegu, South Korea
Citation

A. Stevanato, T. Cucinotta, L. Abeni, D. B. de Oliveira. "An Evaluation of Adaptive Partitioning of Real-Time Workloads on Linux," (to appear) in Proceedings of the 24th IEEE International Symposium on Real-Time Distributed Computing (IEEE ISORC 2021), June 1-3, 2021, Daegu, South Korea.

Presentation at the IEEE ISORC 2021 international conference
Abstract

This paper provides an open implementation and an experimental evaluation of an adaptive partitioning approach for scheduling real-time tasks on symmetric multicore systems. The proposed technique is based on combining partitioned EDF scheduling with an adaptive migration policy that moves tasks across processors only when strictly needed to respect their temporal constraints. The implementation of the technique within the Linux kernel, via modifications to the SCHED DEADLINE code base, is presented. An extensive experimentation has been conducted by applying the technique on a real multi-core platform with several randomly generated synthetic task sets. The obtained experimental results highlight that the approach exhibits a promising performance to schedule real-time workloads on a real system, with a greatly reduced number of migrations compared to the original global EDF available in SCHED DEADLINE.