Motivated by real-world applications of satellites and wireless sensor networks, this paper models and evaluates a dynamic k-out-of-n phase-AND mission system (k/n-PAMS). The mission task conducted by a k/n-PAMS involves multiple consecutive phases; the mission is successful as long as the task is successful in any of the phases. Due to factors, such as scheduled maintenance, location changes in task execution during different phases, and resource sharing with other tasks, the total number of available components n for the considered mission task and the required number of working components k may change from phase to phase. In addition, due to varying load and working environments, component failure time distributions are also phase dependent. This paper proposes an analytical modeling approach based on multivalued decision diagrams (MDDs) for assessing reliability of the considered k/n-PAMS. The approach encompasses a new and fast MDD model generation algorithm that considers behaviors of all the mission phases simultaneously based on node labeling. As demonstrated through empirical studies on k/n-PAMSs with different sizes (different numbers of phases and different numbers of system components), the proposed algorithm is more efficient than the traditional phase-by-phase model generation method.

中文翻译：

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动态k-out-of-n相与任务系统的高效可靠性分析

受卫星和无线传感器网络实际应用的启发，本文对动态k - out -of- n相与任务系统 ( k/n- PAMS)进行建模和评估。k/n -PAMS执行的任务任务涉及多个连续的阶段；只要任务在任何阶段成功，任务就是成功的。由于计划维护、不同阶段任务执行的位置变化以及与其他任务的资源共享等因素，考虑的任务任务的可用组件总数n和所需的工作组件数 k可能会因阶段而异。此外，由于负载和工作环境的变化，组件故障时间分布也与相位有关。本文提出了一种基于多值决策图 (MDD) 的分析建模方法，用于评估所考虑的k/n -PAMS 的可靠性。该方法包含一种新的快速 MDD 模型生成算法，该算法基于节点标记同时考虑所有任务阶段的行为。通过对不同尺寸（不同相数和不同系统组件数）的k/n -PAMS 的实证研究表明，所提出的算法比传统的逐相模型生成方法更有效。