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Summary: A Multiprocessor Server-Based Scheduler for
Soft Real-Time Tasks with Stochastic Execution Demand
Alex F. Mills
Department of Statistics and Operations Research
University of North Carolina
James H. Anderson
Department of Computer Science
University of North Carolina
Abstract
We utilize a multiprocessor server-based approach to sched-
ule a general class of soft real-time systems with stochas-
tic execution demands, when bounded average-case tardi-
ness is sufficient for schedulability. A key feature of the task
model considered here is that the stochastic execution-time
demands can have arbitrary amounts of dependence within
pre-specified time intervals of bounded length. This is an im-
portant practical step forward from requiring complete inde-
pendence of execution times between successive jobs of the
same task. Our main result does not require the scheduler
to know the execution time of each job in advance, and re-
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