.png){kind=icon}
返回
A Novel Convolution-Based Algorithm for the Acyclic Network Symbolic Reliability Function Problem
.png){kind=icon}
OA
AI
DOI：10.1109/ACCESS.2020.2995771.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Acyclic (binary-state) networks are commonly implemented in many diverse disciplines and applications, including information systems, processes management, project management. These networks owe their popularity to the fact that they do not use directed cycles. Network reliability is the most commonly used tool for evaluating and managing systems modeled on acyclic networks, and minimal paths (MPs) play a signicant role in evaluating this reliability. This study therefore proposes a new algorithm based on a novel convolution concept for evaluating acyclic network reliability. The proposed algorithm is able to nd all convolution-based MP sets within polynomial time, and then obtain the symbolic function of the acyclic network reliability in terms of those convolution-based MP sets based on the pivotal decomposition. Its total time complexity is O(2n), which is the best among all existing MP algorithms which are at least O(2jPj), where O(jPj) D O(2n), and n and jPj are the number of nodes and MPs, respectively. The correctness and time complexity of the proposed algorithm is proven and examined. An example is used to display the novel convolution-based algorithm is implemented to solve the acyclic network reliability problem.
Keyword:
Reliability
Computer network reliability
Time complexity
Convolution
Tools
Licenses
Network reliability
acyclic network
minimal path (MP)
convolution
the pivotal decomposition
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3.6
论文数:
9.8W
被引数:
29.4W
机构
引用论文
.png){kind=icon}
分享收藏分享收藏
查看更多内容