基于信息物理融合系统执行器输出事件的价值评价调度策略

对于信息物理融合系统状态转移实时过程会影响系统性能及其正确性的问题，针对执行器的输出事件驱动系统状态转移过程，提出一种基于信息熵与数据质量的执行器输出事件的价值评价调度策略——VE-IE&QoD。首先，以超致密时间模型表达事件的实时性，定义输出事件的自信息量、执行器的信息熵及其数据质量分别为价值评价的函数指标；然后，对执行器执行任务的过程进行价值评价，并考虑适当增加加权系数；最后，利用Ptolemy Ⅱ平台建立包含价值评价调度策略、传统最早截止时间优先（EDF）调度算法以及考虑信息熵的IE^*调度策略的离散事件模型。分析不同算法模型的运行情况，对比价值评价的变化以及执行时间，实验结果表明，价值评价调度策略可降低系统平均执行时间，提高内存使用效率与任务价值评价。该策略能在一定程度上提高系统性能及其正确性。

Scheduling strategy of value evaluation for output-event of actor based on cyber-physical system

The performances and correctness of system are affected by the state transition real-time process of the cyber-physical system. In order to solve the problem, aiming at the state transition process of actor's output-event driven system, a new scheduling strategy of value evaluation for output-event of actor named Value Evaluation-Information Entropy and Quality of Data (VE-IE&QoD) was proposed. Firstly, the real-time performance of event was expressed through the super dense time model. The self-information of the output-event, the information entropy of the actor and the quality of data were defined as the function indexes of value evaluation. Then, the value evaluation mission was executed for the process of the actor in performing task and it was considered about suitably increasing the weighting coefficient for parametric equation. Finally, the discrete event models which contain the proposed VE-IE&QoD scheduling strategy, the traditional Earliest Deadline First (EDF) scheduling algorithm and Information Entropy^* (IE^*) scheduling strategy were built by Ptolemy Ⅱ platform. The operation situation of different algorithm models was analyzed, the change of value evaluation and execution time of different algorithm models were compared. The experimental results show that, the VE-IE&QoD scheduling strategy can reduce the system average execution time, improve the memory usage efficiency and task value evaluation. The proposed VE-IE&QoD scheduling strategy can improve the system performance and correctness to some extent.