利用遍历树构建基于节点对选择的可靠物联网网络

IF 1.5 4区 计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING
Yongqin Zhu, Bojiang Xie
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引用次数: 0

摘要

通过连通性等传统指标来衡量,加强整合新链路的过程,以增强物联网网络的弹性,这是一种流行的做法。然而,即使在相对较小的网络中,试图通过添加每个潜在链接来连接每个预期分离的两个部分被证明是不可行的。因为要考虑的潜在环节的数量将远远大于现有的环节。在实际应用中,草率的方法通常会导致非常不满意的结果。我们设计了一种表示所有有关部门的简化方法。这种方法依赖于定义修剪过的结构和划分之间的关系。随后,它可以识别包含所有已识别的分割的几乎最优的切割集。因此,这使我们能够确定最优的链接集,以提高连接性。在对基准网络模型的测试中,结果表明,与最优方法相比,该方法可以获得显著的改进。值得注意的是,与理想策略相比,处理时间最多可以减少一百万倍,而添加的链接数量仅略有增加。通常使用的经验法则在保护这些系统方面基本上是无效的,与之相比,所提出的方法在大型网络中产生了几乎完美的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Leveraging Traversal Tree for Node Pair Selection-Based Reliable IoT Network Construction

It is a popular practice to enhance the process of integrating new links for the purpose of strengthening IoT network resilience, as measured by traditional indicators like connectivity. Nevertheless, even in relatively small-scale networks, attempting to connect the two parts of every intended separation by adding every potential link proves to be unfeasible. Since the quantity of potential links to be taken into account will be far greater than the existing links. In practical applications, hasty methods usually lead to very unsatisfactory outcomes. We have devised a simplified approach for representing all relevant divisions. This approach relies on defining the relationship between trimmed structures and divisions. Subsequently, it can identify the nearly optimal set of cuts that encompass all recognized divisions. Consequently, this allows us to determine the optimal set of links to improve connectivity. In tests on benchmark network models, the results demonstrated that this method can attain significant improvements comparable to the optimal method. Notably, the processing time can be decreased by up to a million times in contrast to the ideal strategy, with only a slight increment in the number of added links. When contrasted with commonly used rule-of-thumb methods, which are largely ineffective in safeguarding these systems, the proposed method yields nearly flawless results in large networks.

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来源期刊
Concurrency and Computation-Practice & Experience
Concurrency and Computation-Practice & Experience 工程技术-计算机:理论方法
CiteScore
5.00
自引率
10.00%
发文量
664
审稿时长
9.6 months
期刊介绍: Concurrency and Computation: Practice and Experience (CCPE) publishes high-quality, original research papers, and authoritative research review papers, in the overlapping fields of: Parallel and distributed computing; High-performance computing; Computational and data science; Artificial intelligence and machine learning; Big data applications, algorithms, and systems; Network science; Ontologies and semantics; Security and privacy; Cloud/edge/fog computing; Green computing; and Quantum computing.
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