Dynamic partitioned scheduling of real-time tasks on ARM big.LITTLE architectures

Type of publication
Article in journal
Authors

Agostino Mascitti, Tommaso Cucinotta, Mauro Marinoni, Luca Abeni. Elsevier. 2021.

Conference / Journal
Elsevier Journal of Systems and Software (JSS), Vol. 173, March 2021.
Publisher
Elsevier
Year of publication
2021
Citation

Agostino Mascitti, Tommaso Cucinotta, Mauro Marinoni, Luca Abeni. Dynamic partitioned scheduling of real-time tasks on ARM big.LITTLE architectures.

Abstract

This paper presents Big-LITTLE Constant Bandwidth Server (BL-CBS), a dynamic partitioning approach to schedule real-time task sets in an energy-efficient way on multi-core platforms based on the ARM big.LITTLE architecture. BL-CBS is designed as an on-line and adaptive scheduler, based on a push/pull architecture that is suitable to be incorporated in the current SCHED_DEADLINE code base in the Linux kernel. It employs a greedy heuristic to dynamically partition the real-time tasks among the big and LITTLE cores aiming to minimize the energy consumption and the migrations imposed on the running tasks. The new approach is validated through the open-source RT-Sim simulator, which has been extended integrating an energy model of the ODROID-XU3 board, fitting tightly the power consumption profiles for the big and LITTLE cores of the board. An extensive set of simulations have been run with randomly generated real-time task sets, leading to promising results.

DOI
https://doi.org/10.1016/j.jss.2020.110886
ISSN number
0164-1212