Multiprocessor Online Scheduling of Hard-Real-Time Tasks
IEEE Transactions on Software Engineering
Scheduling Algorithms for Multiprogramming in a Hard-Real-Time Environment
Journal of the ACM (JACM)
Optimal Deadline Assignment for Scheduling Soft Aperiodic Tasks in Hard Real-Time Environments
IEEE Transactions on Computers
Deadline-based scheduling of periodic task systems on multiprocessors
Information Processing Letters
Fast scheduling of periodic tasks on multiple resources
IPPS '95 Proceedings of the 9th International Symposium on Parallel Processing
Efficient Object Sharing in Quantum-Based Real-Time Systems
RTSS '98 Proceedings of the IEEE Real-Time Systems Symposium
Multiple-Resource Periodic Scheduling Problem: how much fairness is necessary?
RTSS '03 Proceedings of the 24th IEEE International Real-Time Systems Symposium
IEEE Transactions on Computers
Fair scheduling of dynamic task systems on multiprocessors
Journal of Systems and Software - Special issue: Parallel and distributed 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
Work-Conserving Optimal Real-Time Scheduling on Multiprocessors
ECRTS '08 Proceedings of the 2008 Euromicro Conference on Real-Time Systems
Euromicro-RTS'00 Proceedings of the 12th Euromicro conference on Real-time systems
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We present a new scheduling algorithm, called PL that is work-conserving and in terms of schedulability, optimal on multiprocessors for a synchronous periodic task set. The PL algorithm is a laxity based algorithm and ensures execution of a task with approximate proportional fairness at each task's period. Existing optimal algorithms on multiprocessors may cause excessive scheduling decisions and preemptions or may not be applied in a discrete environment. The proposed algorithm can be applied in a discrete environment and reduce the number of scheduling decisions and preemptions compared with a Pfair algorithm.