A Flattened Priority Framework for Mixed-Criticality Systems

IEEE Transactions on Industrial Electronics(2020)

引用 4|浏览119
暂无评分
摘要
The ever-increasing integrated services in industrial control systems lead to diverse performance objectives and multiple traffic characteristics. Such systems are called mixed-criticality systems (MCSs). Priority-based scheduling is a commonly used mechanism to achieve differential QoS in MCS. While MCSs have supported prioritization as a standard feature, traditional priority-based schedulers incur significant complexity, especially due to the widespread adoption of mixed-criticality applications in embedded systems. It is desirable to lower the complexity of MCSs under the limited computing resource of smart devices. This article presents a novel technique to design resource-efficient priority schedulers for MCSs. We propose a flattened-priority framework to transform an unprioritized scheduler into a priority-based one. The framework works iteratively based on feedback loops. For $P$ priorities, the transformed scheduler converges in $P$ iterations in the worst case. With the proposed framework, the design of priority schedulers is simplified into the design of nonpriority schedulers. Such a simplification dramatically lowers the design effort and system complexity. A case study was performed on an FPGA-based Industrial Ethernet switch that is a typical MCS. Compared with the previous priority schedulers, the transformed priority scheduler by the proposed framework achieves a 30%–50% reduction in the resource usage of lookup tables without performance loss of forwarding delay.
更多
查看译文
关键词
Task analysis,Job shop scheduling,Quality of service,Complexity theory,Switches,Transforms,Smart devices
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要