电池支持的网络物理系统的鲁棒性分析
Robustness Analysis for Battery Supported Cyber-Physical Systems
AI总结：
本文提出一种新的分析方法，通过动态可调度性测试和自适应电池荷电状态阈值，量化电池支持的网络物理系统中调度与电池管理的鲁棒性。
摘要：
本文建立了一种新颖的分析方法，用于量化电池支持的网络物理系统中调度和电池管理的鲁棒性。引入动态可调度性测试，以确定任务在有限时间窗口内是否可调度。该测试通过评估在运行时破坏可调度性的计算时间扰动的强度，来衡量实时调度算法的鲁棒性。电池管理的鲁棒性通过自适应荷电状态阈值进行量化分析。该自适应阈值显著降低了电池管理算法在决定何时需要更换电池时的误报率。
英文摘要：
This paper establishes a novel analytical approach to quantify robustness of scheduling and battery management for battery supported cyber-physical systems. A dynamic schedulability test is introduced to determine whether tasks are schedulable within a finite time window. The test is used to measure robustness of a real-time scheduling algorithm by evaluating the strength of computing time perturbations that break schedulability at runtime. Robustness of battery management is quantified analytically by an adaptive threshold on the state of charge. The adaptive threshold significantly reduces the false alarm rate for battery management algorithms to decide when a battery needs to be replaced.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
