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HLF-D*: An Approximate Greedy Policy for Age-based Information Freshness of Real-time Updates

机译:HLF-D *:用于基于年龄的信息的近似贪婪政策,实时更新的新鲜度

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In this work, we have considered an industrial cyber-physical system (ICPS) consisting of a symmetric wireless sensor-actuator network (WSAN), controlled by a centralized controller. Real-time sensor updates with variable deadlines are sent to the controller for remote monitoring and closed-loop control of the network. These samples get aperiodically replaced by fresh new samples having variable deadlines, once they fail to get service within their stipulated deadlines. This paper aims to accomplish both the objectives of maximum information freshness and minimum deadline misses of sample packets. For this purpose, a new low complexity greedy scheduling algorithm called Deadline-aware Highest Latency First Advanced (HLF-D*) is proposed in this paper. Through competitive analysis, it is found that the HLF-D* policy has an expected approximation ratio strictly greater than 0.6875. Moreover, the performance of HLF-D* has been compared with other popular deadline-aware scheduling policies through extensive simulations.
机译:在这项工作中,我们考虑了由由集中控制器控制的对称无线传感器 - 执行器网络(WSAN)组成的工业网络物理系统(ICP)。具有可变截止日期的实时传感器更新将发送到控制器,以进行网络的远程监控和闭环控制。这些样品通过新的新样本被具有变量截止日期的新鲜新样本取代,一旦他们未能在其规定的截止日期内获得服务。本文旨在实现最大信息新鲜度和最小截止日期的样本数据包的目标。为此目的,本文提出了一种新的低复杂性贪婪调度算法,称为截止日期感知最高延迟的最高延迟(HLF-D *)。通过竞争分析,发现HLF-D *政策的预期近似比严格大于0.6875。此外,通过广泛的模拟将HLF-D *的性能与其他流行的截止日期感知调度策略进行了比较。

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