Publication details

A. Mascitti, T. Cucinotta. "Dynamic Partitioned Scheduling of Real-Time DAG Tasks on ARM big.LITTLE Architectures," in Proceedings of the 29th International Conference on Real-Time Networks and Systems (RTNS 2021), April 7-9, 2021, Nantes, France.

Abstract

This paper evaluates the combination of a Directed Acyclic Graph (DAG) task splitting technique already proposed in the literature and the state-of-the-art, energy-aware version of the well-known CBS server (BL-CBS), which dynamically partitions and schedules real-time task sets in an energy-efficient way on multi-core plat- forms based on the ARM big.LITTLE architecture. The approach is designed to be used with any DAG in a transparent way as an on-line and adaptive scheduler supporting “open” systems. The ap- proach is validated and evaluated through the open-source RTSim simulator, which has been extended integrating an energy model of the ODROID-XU3 board and the code-base needed to perform the DAG task decomposition and scheduling. Simulations on randomly generated DAGs show that the approach leads to promising results.

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DOI: 10.1145/3453417.3453442

BibTeX entry:

@inproceedings{Mascitti2021,
	doi = {10.1145/3453417.3453442},
	url = {https://doi.org/10.1145%2F3453417.3453442},
	year = 2021,
	month = apr,
	publisher = {{ACM}},
	author = {Agostino Mascitti and Tommaso Cucinotta},
	title = {Dynamic Partitioned Scheduling of Real-Time {DAG} Tasks on {ARM} big.{LITTLE} Architectures{\ast}},
	booktitle = {29th International Conference on Real-Time Networks and Systems}
}

Last updated on
07 November 2024