TY - GEN
T1 - Virtually-Federated Scheduling of Parallel Real-Time Tasks
AU - Jiang, Xu
AU - Guan, Nan
AU - Liang, Haochun
AU - Tang, Yue
AU - Qiao, Lei
AU - Yi, Wang
N1 - Publisher Copyright:
©2021 IEEE
PY - 2021
Y1 - 2021
N2 - Federated scheduling is a promising approach to schedule parallel real-time tasks, where each task exclusively executes on a set of dedicated processors. However, federated scheduling suffers significant resource wasting since a task typically only uses part of the processing capacity allocated to it, while the unused part cannot be shared with other tasks. To solve this problem, we present a virtually-federated scheduling approach, which both enjoys the good analyzability of federated scheduling and allows tasks to efficiently share processors with others. The main idea is to construct virtual processors on physical processors, and let a task exclusively execute on a set of virtual processors. As a physical processor is shared by virtual processors, tasks effectively share processors with each other. On the other hand, as each task exclusively executes on its own virtual processor set, the good analyzability of federated scheduling can be carried into to our virtually-federated scheduling approach. We conduct comprehensive performance evaluation to compare our proposed approach with existing methods of different types. Experiment results show that our approach consistently outperforms existing methods to a considerable extent under a wide range of parameter settings.
AB - Federated scheduling is a promising approach to schedule parallel real-time tasks, where each task exclusively executes on a set of dedicated processors. However, federated scheduling suffers significant resource wasting since a task typically only uses part of the processing capacity allocated to it, while the unused part cannot be shared with other tasks. To solve this problem, we present a virtually-federated scheduling approach, which both enjoys the good analyzability of federated scheduling and allows tasks to efficiently share processors with others. The main idea is to construct virtual processors on physical processors, and let a task exclusively execute on a set of virtual processors. As a physical processor is shared by virtual processors, tasks effectively share processors with each other. On the other hand, as each task exclusively executes on its own virtual processor set, the good analyzability of federated scheduling can be carried into to our virtually-federated scheduling approach. We conduct comprehensive performance evaluation to compare our proposed approach with existing methods of different types. Experiment results show that our approach consistently outperforms existing methods to a considerable extent under a wide range of parameter settings.
UR - https://www.scopus.com/pages/publications/85124535911
U2 - 10.1109/RTSS52674.2021.00050
DO - 10.1109/RTSS52674.2021.00050
M3 - 会议稿件
AN - SCOPUS:85124535911
T3 - Proceedings - Real-Time Systems Symposium
SP - 482
EP - 494
BT - Proceedings - 2021 IEEE 42nd Real-Time Systems Symposium, RTSS 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 42nd IEEE Real-Time Systems Symposium, RTSS 2021
Y2 - 7 December 2021 through 10 December 2021
ER -