Proportionate progress: a notion of fairness in resource allocation
STOC '93 Proceedings of the twenty-fifth annual ACM symposium on Theory of computing
Static-Priority Scheduling on Multiprocessors
RTSS '01 Proceedings of the 22nd IEEE Real-Time Systems Symposium
An EDF-based Scheduling Algorithm for Multiprocessor Soft Real-Time Systems
ECRTS '05 Proceedings of the 17th Euromicro Conference on Real-Time Systems
Multiprocessor Scheduling with Few Preemptions
RTCSA '06 Proceedings of the 12th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications
An Optimal Real-Time Scheduling Algorithm for Multiprocessors
RTSS '06 Proceedings of the 27th IEEE International Real-Time Systems Symposium
A Hybrid Real-Time Scheduling Approach for Large-Scale Multicore Platforms
ECRTS '07 Proceedings of the 19th Euromicro Conference on Real-Time Systems
Portioned EDF-based scheduling on multiprocessors
EMSOFT '08 Proceedings of the 8th ACM international conference on Embedded software
Semi-partitioned Scheduling of Sporadic Task Systems on Multiprocessors
ECRTS '09 Proceedings of the 2009 21st Euromicro Conference on Real-Time Systems
Euromicro-RTS'00 Proceedings of the 12th Euromicro conference on Real-time systems
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Semi-partitioned scheduling is regarded as a viable alternative to partitioned or global scheduling approaches. Advantage of semi-partitioned scheduling is two-folds: it has reduced runtime overhead compared to global scheduling, and improved schedulability and system utilization factor compared to partitioned scheduling. This paper proposes a new semi-partitioned scheduling algorithm for real-time periodic task systems over multicore platforms. Our proposed algorithm works in two phases. In the first phase, each task from a feasible application task set is statically assigned to a specific processor. If a task can not be partitioned on any processor in the platform, it qualifies as migrating task. In the second phase, processors are clustered together such that, per cluster, the unused fragmented computation power equivalent to at most one processor is available. We provide schedulability analysis and experimental evaluation to support our proposition. Moreover, simulation results show an average difference of 18-folds in the number of task preemptions and 10-folds in the number of task migrations compared to multiprocessor optimal scheduling algorithm PD.