The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Tugas yang menangguhkan dirinya untuk menunggu penyiapan I/O atau menunggu acara daripada nod lain dalam persekitaran teragih dipanggil tugas menyekat I/O. Teori penjadualan masa nyata keras konvensional menggunakan rangka kerja analisis monotonik kadar (RMA) untuk menjadualkan tugas menyekat I/O tersebut. Walau bagaimanapun, kebanyakan mereka adalah pesimis. Dalam makalah ini, kami mencadangkan algoritma berkesan yang boleh menjadualkan set tugasan yang mempunyai tugas menyekat I/O di bawah tugasan keutamaan dinamik. Kami membentangkan teorem segera kritikal baharu untuk set tugas berbilang bingkai di bawah tugasan keutamaan dinamik. Penjadualan dianalisis di bawah teorem segera kritikal yang baharu. Untuk analisis penjadualan, kertas ini membentangkan penjumlahan tepu yang digunakan untuk mengira fungsi gangguan maksimum (MIF). Dengan penjumlahan tepu, penjadualan set tugasan yang mempunyai tugas menyekat I/O boleh dianalisis dengan lebih tepat. Kami mencadangkan satu algoritma yang dipanggil Frame Laxity Monotonic Scheduling (FLMS). Algoritma genetik (GA) juga digunakan. Daripada eksperimen kami, kami boleh membuat kesimpulan bahawa FLMS boleh mengurangkan masa pengiraan dengan ketara, dan GA boleh meningkatkan nisbah penjadualan tugas lebih daripada yang mungkin dengan FLMS.
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Salinan
Shan DING, Hiroyuki TOMIYAMA, Hiroaki TAKADA, "Effective Scheduling Algorithms for I/O Blocking with a Multi-Frame Task Model" in IEICE TRANSACTIONS on Information,
vol. E92-D, no. 7, pp. 1412-1420, July 2009, doi: 10.1587/transinf.E92.D.1412.
Abstract: A task that suspends itself to wait for an I/O completion or to wait for an event from another node in distributed environments is called an I/O blocking task. Conventional hard real-time scheduling theories use framework of rate monotonic analysis (RMA) to schedule such I/O blocking tasks. However, most of them are pessimistic. In this paper, we propose effective algorithms that can schedule a task set which has I/O blocking tasks under dynamic priority assignment. We present a new critical instant theorem for the multi-frame task set under dynamic priority assignment. The schedulability is analyzed under the new critical instant theorem. For the schedulability analysis, this paper presents saturation summation which is used to calculate the maximum interference function (MIF). With saturation summation, the schedulability of a task set having I/O blocking tasks can be analyzed more accurately. We propose an algorithm which is called Frame Laxity Monotonic Scheduling (FLMS). A genetic algorithm (GA) is also applied. From our experiments, we can conclude that FLMS can significantly reduce the calculation time, and GA can improve task schedulability ratio more than is possible with FLMS.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.E92.D.1412/_p
Salinan
@ARTICLE{e92-d_7_1412,
author={Shan DING, Hiroyuki TOMIYAMA, Hiroaki TAKADA, },
journal={IEICE TRANSACTIONS on Information},
title={Effective Scheduling Algorithms for I/O Blocking with a Multi-Frame Task Model},
year={2009},
volume={E92-D},
number={7},
pages={1412-1420},
abstract={A task that suspends itself to wait for an I/O completion or to wait for an event from another node in distributed environments is called an I/O blocking task. Conventional hard real-time scheduling theories use framework of rate monotonic analysis (RMA) to schedule such I/O blocking tasks. However, most of them are pessimistic. In this paper, we propose effective algorithms that can schedule a task set which has I/O blocking tasks under dynamic priority assignment. We present a new critical instant theorem for the multi-frame task set under dynamic priority assignment. The schedulability is analyzed under the new critical instant theorem. For the schedulability analysis, this paper presents saturation summation which is used to calculate the maximum interference function (MIF). With saturation summation, the schedulability of a task set having I/O blocking tasks can be analyzed more accurately. We propose an algorithm which is called Frame Laxity Monotonic Scheduling (FLMS). A genetic algorithm (GA) is also applied. From our experiments, we can conclude that FLMS can significantly reduce the calculation time, and GA can improve task schedulability ratio more than is possible with FLMS.},
keywords={},
doi={10.1587/transinf.E92.D.1412},
ISSN={1745-1361},
month={July},}
Salinan
TY - JOUR
TI - Effective Scheduling Algorithms for I/O Blocking with a Multi-Frame Task Model
T2 - IEICE TRANSACTIONS on Information
SP - 1412
EP - 1420
AU - Shan DING
AU - Hiroyuki TOMIYAMA
AU - Hiroaki TAKADA
PY - 2009
DO - 10.1587/transinf.E92.D.1412
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E92-D
IS - 7
JA - IEICE TRANSACTIONS on Information
Y1 - July 2009
AB - A task that suspends itself to wait for an I/O completion or to wait for an event from another node in distributed environments is called an I/O blocking task. Conventional hard real-time scheduling theories use framework of rate monotonic analysis (RMA) to schedule such I/O blocking tasks. However, most of them are pessimistic. In this paper, we propose effective algorithms that can schedule a task set which has I/O blocking tasks under dynamic priority assignment. We present a new critical instant theorem for the multi-frame task set under dynamic priority assignment. The schedulability is analyzed under the new critical instant theorem. For the schedulability analysis, this paper presents saturation summation which is used to calculate the maximum interference function (MIF). With saturation summation, the schedulability of a task set having I/O blocking tasks can be analyzed more accurately. We propose an algorithm which is called Frame Laxity Monotonic Scheduling (FLMS). A genetic algorithm (GA) is also applied. From our experiments, we can conclude that FLMS can significantly reduce the calculation time, and GA can improve task schedulability ratio more than is possible with FLMS.
ER -