An Adaptive Overload Management Strategy for Periodic Real-Time Tasks

被引：0

作者：

Xia, Jiali ^{[1
]}

Han, Zengbo ^{[1
]}

Chen, Hui ^{[1
]}

Mao, Chengying ^{[1
]}

机构：

[1] Jiangxi Univ Finance & Econ, Sch Software, Nanchang 330013, Peoples R China

来源：

2009 IEEE INTERNATIONAL CONFERENCE ON GRANULAR COMPUTING ( GRC 2009) | 2009年

关键词：

D O I：

10.1109/GRC.2009.5255050

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

By analyzing the relationships of preemption and abortion among the jobs of the real-time tasks, the overload management strategy (OMS) divides the jobs into two types: steady-finished-jobs and absolute-aborted-jobs. While scheduling the jobs, the steady-finished-jobs are released and the absolute-aborted-jobs are rejected. In this way, the cascaded preemption among the jobs could be avoided. Also, the system resource could be efficiently utilized. The results of the simulation show that, the OMS could adaptively deal with the static or dynamic task set. Additionally, by applying OMS, the scheduling algorithms can obviously improve the performance of the real-time system.

引用

页码：602 / 607

页数：6

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