rt-muse : measuring real-time characteristics of execution platforms
(2017) In Real-Time Systems 53(6). p.857-885- Abstract
Operating systems code is often developed according to principles like simplicity, low overhead, and low memory footprint. Schedulers are no exceptions. A scheduler is usually developed with flexibility in mind, and this restricts the ability to provide real-time guarantees. Moreover, even when schedulers can provide real-time guarantees, it is unlikely that these guarantees are properly quantified using theoretical analysis that carries on to the implementation. To be able to analyze the guarantees offered by operating systems’ schedulers, we developed a publicly available tool that analyzes timing properties extracted from the execution of a set of threads and computes the lower and upper bounds to the supply function offered by the... (More)
Operating systems code is often developed according to principles like simplicity, low overhead, and low memory footprint. Schedulers are no exceptions. A scheduler is usually developed with flexibility in mind, and this restricts the ability to provide real-time guarantees. Moreover, even when schedulers can provide real-time guarantees, it is unlikely that these guarantees are properly quantified using theoretical analysis that carries on to the implementation. To be able to analyze the guarantees offered by operating systems’ schedulers, we developed a publicly available tool that analyzes timing properties extracted from the execution of a set of threads and computes the lower and upper bounds to the supply function offered by the execution platform, together with information about migrations and statistics on execution times. rt-muse evaluates the impact of many application and platform characteristics including the scheduling algorithm, the amount of available resources, the usage of shared resources, and the memory access overhead. Using rt-muse, we show the impact of Linux scheduling classes, shared data and application parallelism, on the delivered computing capacity. The tool provides useful insights on the runtime behavior of the applications and scheduler. In the reported experiments, rt-muse detected some issues arising with the real-time Linux scheduler: despite having available cores, Linux does not migrate SCHED_RR threads which are enqueued behind SCHED_FIFO threads with the same priority.
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- author
- Maggio, Martina LU ; Lelli, Juri and Bini, Enrico LU
- organization
- publishing date
- 2017-11
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Linux kernel, Resource measurement, Supply functions, Tools
- in
- Real-Time Systems
- volume
- 53
- issue
- 6
- pages
- 857 - 885
- publisher
- Springer
- external identifiers
-
- wos:000412536700002
- scopus:85021762783
- ISSN
- 0922-6443
- DOI
- 10.1007/s11241-017-9284-5
- language
- English
- LU publication?
- yes
- id
- c45d1c70-5ff3-4b15-b711-3c8fdfe7b6d0
- date added to LUP
- 2017-07-19 07:58:54
- date last changed
- 2024-02-29 18:37:09
@article{c45d1c70-5ff3-4b15-b711-3c8fdfe7b6d0,
abstract = {{<p>Operating systems code is often developed according to principles like simplicity, low overhead, and low memory footprint. Schedulers are no exceptions. A scheduler is usually developed with flexibility in mind, and this restricts the ability to provide real-time guarantees. Moreover, even when schedulers can provide real-time guarantees, it is unlikely that these guarantees are properly quantified using theoretical analysis that carries on to the implementation. To be able to analyze the guarantees offered by operating systems’ schedulers, we developed a publicly available tool that analyzes timing properties extracted from the execution of a set of threads and computes the lower and upper bounds to the supply function offered by the execution platform, together with information about migrations and statistics on execution times. rt-muse evaluates the impact of many application and platform characteristics including the scheduling algorithm, the amount of available resources, the usage of shared resources, and the memory access overhead. Using rt-muse, we show the impact of Linux scheduling classes, shared data and application parallelism, on the delivered computing capacity. The tool provides useful insights on the runtime behavior of the applications and scheduler. In the reported experiments, rt-muse detected some issues arising with the real-time Linux scheduler: despite having available cores, Linux does not migrate SCHED_RR threads which are enqueued behind SCHED_FIFO threads with the same priority.</p>}},
author = {{Maggio, Martina and Lelli, Juri and Bini, Enrico}},
issn = {{0922-6443}},
keywords = {{Linux kernel; Resource measurement; Supply functions; Tools}},
language = {{eng}},
number = {{6}},
pages = {{857--885}},
publisher = {{Springer}},
series = {{Real-Time Systems}},
title = {{rt-muse : measuring real-time characteristics of execution platforms}},
url = {{http://dx.doi.org/10.1007/s11241-017-9284-5}},
doi = {{10.1007/s11241-017-9284-5}},
volume = {{53}},
year = {{2017}},
}