A Multiframe Model for Real-Time Tasks
IEEE Transactions on Software Engineering
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The well-known periodic task model of Liu and Layland assumes a worst-case execution time bound for every task and may be too pessimistic if the worst-case execution time of a task is much longer than the average. In this paper, we give a generalized real-time task model which allows the execution time of a task to vary from one instance to another by capturing the maximum total execution time of consecutive instances. We investigate the scheduleability problem for this model with the help of the multiframe task model we introduced earlier. We show that a significant improvement in the utilization bound can be established for the general model and the requirement of AM property in the multiframe model can be dropped.