Adaptive stochastic manpower scheduling
Proceedings of the 30th conference on Winter simulation
Optimal stochastic scheduling in multiclass parallel queues
SIGMETRICS '99 Proceedings of the 1999 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Sequencing Jobs with Stochastic Task Structures on a Single Machine
Journal of the ACM (JACM)
Approximation in preemptive stochastic online scheduling
ESA'06 Proceedings of the 14th conference on Annual European Symposium - Volume 14
Preemptive stochastic online scheduling on two uniform machines
Information Processing Letters
Analysis of round-robin variants: favoring newly arrived jobs
SpringSim '09 Proceedings of the 2009 Spring Simulation Multiconference
On the Gittins index in the M/G/1 queue
Queueing Systems: Theory and Applications
A modeling framework for optimizing the flow-level scheduling with time-varying channels
Performance Evaluation
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An analytic model of a single processor scheduling problem is investigated. The scheduling objective is to minimize the total loss incurred by a finite number of initially available requests when each request has an associated linear loss function. The assumptions of the model are that preemption is allowed with negligible loss of processor time, and that the distribution of actual service times is known for each class of requests. A request is associated with a class by any of its characteristics except its actual service time. A contrived example demonstrates that one reasonable scheduling rule does not always minimize expected total loss. The major results of the paper are the definition of a new scheduling rule based on the known service time distributions, and the proof that expected total loss is always minimized by using this new rule. Brief consideration is given to generalizations of the model in which new requests arrive randomly, and preemption requires a non-negligible amount of processor time.