A hard real-time system is usually subject to stringent reliability and timing constraints due to the fact that failure to produce correct results in a timely manner may lead to a disaster. Almost all fault-tolerant s...
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A hard real-time system is usually subject to stringent reliability and timing constraints due to the fact that failure to produce correct results in a timely manner may lead to a disaster. Almost all fault-tolerant schedulingalgorithms at present are designed to deal with hardware faults, while less of those take possible software faults into account. Presented in this paper is a new software fault-tolerant real-time schedulingalgorithm that is similar to EOF, called EBPA (expectation-based probing algorithm). The important contributions of the algorithm are probing a certain steps during the executions of primaries, which leads to improving the predictive quality of canceling ineffective primaries when heavy workload occurs and preventing early failures in execution from triggering failures in the subsequent primary executions as soon as possible. Therefore, the algorithm increases the successful percentage of tasks' completion, and meanwhile decreases the wasted CPU time slots. The simulation experiments show that the algorithm has a better trade-offs between scheduling costs and scheduling performance than the well-known algorithms so far. Moreover, some experimental parameters, such as the number of probing steps and failure probability, are also taken into account.
It is shown that the problem of maximising the total reward of online tasks can be solved by finding the minimum of the maximum derivatives of the reward functions. Based on the modified approach and a close observati...
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It is shown that the problem of maximising the total reward of online tasks can be solved by finding the minimum of the maximum derivatives of the reward functions. Based on the modified approach and a close observation of task arrival characteristics, a heuristic algorithm with average complexity close to O(N) is presented.
This research addresses the timeliness of task execution in real-time systems. Specifically, we investigate the dynamicscheduling of tasks with well-defined timing constraints. We present a dynamic uniprocessor sched...
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This research addresses the timeliness of task execution in real-time systems. Specifically, we investigate the dynamicscheduling of tasks with well-defined timing constraints. We present a dynamic uniprocessor schedulingalgorithm with an O(n log n) worst case complexity. The preemptive scheduling performed by our algorithm is shown to be of higher efficiency than that of other known algorithms. Furthermore, tasks may be related by precedence constraints, and they may have arbitrary deadlines and start times (which need not equal their arrival times). An experimental evaluation or the algorithm compares its average case behavior to the worst case. An analytic model also presented in this paper is used for explanation of the experimental results and is validated with actual system measurements. The dynamic scheduling algorithm is the basis of a real-time multiprocessor operating system kernel developed in conjunction with this research. Specifically, this algorithm is used. at the lowest, threads-based layer of the kernel whenever threads are created.
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