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1.	Jiang, Xu, et al. (author) Semi-Federated Scheduling of Parallel Real-Time Tasks on Multiprocessors 2017 In: 2017 IEEE Real-Time Systems Symposium (RTSS). - : IEEE. - 9781538614143 ; , s. 80-91 Conference paper (peer-reviewed)abstract Federated scheduling is a promising approach to schedule parallel real-time tasks on multi-cores, where each heavy task exclusively executes on a number of dedicated processors, while light tasks are treated as sequential sporadic tasks and share the remaining processors. However, federated scheduling suffers resource waste since a heavy task with processing capacity requirement x + is an element of (where x is an integer and 0 < is an element of < 1) needs x+ 1 dedicated processors. In the extreme case, almost half of the processing capacity is wasted. In this paper we propose the semi-federate scheduling approach, which only grants x dedicated processors to a heavy task with processing capacity requirement x+ is an element of, and schedules the remaining is an element of part together with light tasks on shared processors. Experiments with randomly generated task sets show the semi-federated scheduling approach significantly outperforms not only federated scheduling, but also all existing approaches for scheduling parallel real-time tasks on multi-cores.

Jiang, Xu, et al. (author)
Semi-Federated Scheduling of Parallel Real-Time Tasks on Multiprocessors
2017
In: 2017 IEEE Real-Time Systems Symposium (RTSS). - : IEEE. - 9781538614143 ; , s. 80-91
Conference paper (peer-reviewed)abstract
- Federated scheduling is a promising approach to schedule parallel real-time tasks on multi-cores, where each heavy task exclusively executes on a number of dedicated processors, while light tasks are treated as sequential sporadic tasks and share the remaining processors. However, federated scheduling suffers resource waste since a heavy task with processing capacity requirement x + is an element of (where x is an integer and 0 < is an element of < 1) needs x+ 1 dedicated processors. In the extreme case, almost half of the processing capacity is wasted. In this paper we propose the semi-federate scheduling approach, which only grants x dedicated processors to a heavy task with processing capacity requirement x+ is an element of, and schedules the remaining is an element of part together with light tasks on shared processors. Experiments with randomly generated task sets show the semi-federated scheduling approach significantly outperforms not only federated scheduling, but also all existing approaches for scheduling parallel real-time tasks on multi-cores.

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