计算机科学
调度(生产过程)
有向无环图
并行计算
分布式计算
最早截止时间优先安排
处理器调度
执行时间
计算
最坏情况执行时间
动态优先级调度
实时计算
单调速率调度
算法
数学优化
计算机网络
服务质量
数学
资源(消歧)
作者
Kankan Wang,Xu Jiang,Nan Guan,Di Liu,Weichen Liu,Qingxu Deng
摘要
Real-time and embedded systems are shifting from single-core to multi-core processors, on which the software must be parallelized to fully utilize the computation capacity of the hardware. Recently, much work has been done on real-time scheduling of parallel tasks modeled as directed acyclic graphs (DAG). However, most of these studies assume tasks to have implicit or constrained deadlines. Much less work considered the general case of arbitrary deadlines (i.e., the relative deadline is allowed to be larger than the period), which is more difficult to analyze due to intra-task interference among jobs. In this article, we study the analysis of Global Earliest Deadline First (GEDF) scheduling for DAG parallel tasks with arbitrary deadlines. We develop new analysis techniques for GEDF scheduling of a single DAG task and this new analysis techniques can guarantee a better capacity augmentation bound 2.41 (the best known result is 2.5) in the case of a single task. Furthermore, the proposed analysis techniques are also extended to the case of multiple DAG tasks under GEDF and federated scheduling. Finally, through empirical evaluation, we justify the out-performance of our schedulability tests compared to the state-of-the-art in general.
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