网络拓扑连通性中的故障与漏洞研究:逻辑和物理视角

IF 28 1区 计算机科学 Q1 COMPUTER SCIENCE, THEORY & METHODS
Carlos Pedroso, Aldri Santos
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引用次数: 0

摘要

拓扑连接在网络环境中是必不可少的,因为它能够在分布式设备之间有效地交换信息并提高服务可靠性。这些具有不同特征的设备相互连接,形成了作为基础设施的网络,促进了对社会福祉至关重要的多种服务的提供。在灾难等关键情况下,确保连接对于有效传输关键数据(如安全和公共交通通知)至关重要。这项调查强调了弹性拓扑连接的重要性,它可以在故障或中断的情况下保持网络节点之间的通信。首先,我们探讨了漏洞和故障带来的挑战,无论是良性的还是恶意的,物理的还是逻辑的,它们可能会破坏拓扑结构,导致诸如数据包丢失、传输延迟和服务可用性降低等问题。然后,我们回顾了文献,找出了在不同网络场景(如IoT、WSN和TSN)中提供拓扑连通性弹性的主要故障和解决方案。对解决方案进行分类,重点关注诸如抵抗、恢复、适应、吸收、主动和被动等策略,从而全面了解如何增强拓扑性能和可用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Survey on Faults and Vulnerabilities in Network Topological Connectivity: Logical and Physical Perspectives
Topological connectivity is essential in networked environments, as it enables the efficient exchange of information between distributed devices and increases service reliability. The devices’ interconnection with different characteristics allows the formation of networks that function as infrastructures, facilitating the provision of multiple services essential to social well-being. In critical scenarios such as disasters, ensuring connectivity is vital for the effective transmission of crucial data, such as security and public transport notifications. This survey highlights the importance of resilient topological connectivity, which maintains communication among network nodes despite faults or disruptions. First, we explore the challenges posed by vulnerabilities and faults, whether benign or malicious, physical or logical, that may disrupt the topology, resulting in problems such as packet loss, transmission delays, and reduced service availability. Then, we review the literature to identify the main faults and solutions developed to provide resilience to topological connectivity in different network scenarios, such as IoT, WSN, and TSN. Solutions are categorized with a focus on strategies such as resistance, recovery, adaptation, absorption, both active and reactive, offering a comprehensive understanding of how to strengthen topology performance and availability.
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来源期刊
ACM Computing Surveys
ACM Computing Surveys 工程技术-计算机:理论方法
CiteScore
33.20
自引率
0.60%
发文量
372
审稿时长
12 months
期刊介绍: ACM Computing Surveys is an academic journal that focuses on publishing surveys and tutorials on various areas of computing research and practice. The journal aims to provide comprehensive and easily understandable articles that guide readers through the literature and help them understand topics outside their specialties. In terms of impact, CSUR has a high reputation with a 2022 Impact Factor of 16.6. It is ranked 3rd out of 111 journals in the field of Computer Science Theory & Methods. ACM Computing Surveys is indexed and abstracted in various services, including AI2 Semantic Scholar, Baidu, Clarivate/ISI: JCR, CNKI, DeepDyve, DTU, EBSCO: EDS/HOST, and IET Inspec, among others.
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