文章基本信息

标题：A Design That Incorporates Adaptive Reservation into Mixed-Criticality Systems
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作者：Fei Guan ; Long Peng ; Luc Perneel 等
期刊名称：Scientific Programming
印刷版ISSN：1058-9244
出版年度：2017
卷号：2017
DOI：10.1155/2017/3403685
出版社：Hindawi Publishing Corporation
摘要：This paper presents a design and implementation of a Mixed-Criticality System (MCS) extended from C/OS III. It is based on a MCS model that uses an adaptive reservation mechanism to cope with the uncertainties in task execution times and to increase the resource utilization in MCS. The implementation takes advantage of the tasks’ recent execution records to predict their required computational resource in the near future and adjusts their reserved budget according to their criticality levels. The designed system focuses on soft real-time tasks. An overrun tolerance algorithm is used to limit the deadline miss ratios between a rise to the task’s actual consumption and the change to the amount of reservation. More than two criticality levels can be handled without introducing obvious additional overhead at each added level. The case study evaluation demonstrates that the reserved resource for each task is always close to its actual consumption; the tasks’ deadline misses are bounded by the different requirements specified by the criticality levels; during overload conditions, high-criticality tasks are guaranteed to have sufficient resource reservation. Although there is still room for improvement if it comes to processing overhead, this research brings some inspirations in both modelling and implementation aspects of MCS.