Resilience of communication networks to random failures and disasters: An optimization perspective

Rak, Jacek; Heegaard, Poul E.; Helvik, Bjarne E.

doi:10.1002/net.21940

Cited by 8 publications

(4 citation statements)

References 10 publications

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“…The types of services provided by the communication network to people are constantly increasing and updating. It is playing a more and more important role in the whole human social economy, social activities, and daily life [1]. All these show that the communication network is no longer just a medium of mutual communication, but a distributed information processing platform that provides comprehensive services for human beings.…”

Section: Introductionmentioning

confidence: 99%

Electronic Communication Fault Signal Recognition Based on Data Mining Algorithm

Luo

2022

Wireless Communications and Mobile Computing

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In order to solve the technical problem of fault signal recognition in the field of communication, this paper proposes an electronic communication fault signal recognition method based on data mining algorithm. Firstly, the K-means clustering algorithm is used to determine the cluster number k according to some attributes or class characteristics of the communication class samples, and the communication sample types are classified into a certain class so that the communication sample data in the cluster can be closely distributed and the data within a certain class range can be calculated by Euclidean distance formula. Then, this paper clusters the data. In the clustering data, BP neural network model is used to train and calculate the obtained clustering data again, which can map and deal with the complex nonlinear relationship between the fault information data of different clustering categories. The results show that the final error accuracy can be raised to about 20% by using the method in this paper. Conclusion. The algorithm designed in this paper can quickly predict the factors affecting the communication and find the communication fault information.

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Section: Introductionmentioning

confidence: 99%

Electronic Communication Fault Signal Recognition Based on Data Mining Algorithm

Luo

2022

Wireless Communications and Mobile Computing

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“…There are several special issues of Networks that focus on resilient telecommunications networks. Rak and Sterbenz [175] describe the contributions made by papers in the issue “Optimization Issues in Resilient Network Design and Modeling.” Jonsson et al [122] describe the contributions made by papers in the issue “Design of Resilient Communications Networks.” Rak et al [176] describe the contributions made by papers in the issue “Resilience of Communication Networks to Random Failures and Disasters.” We refer the reader to these overviews for a more detailed discussion of the papers; here we provide a high‐level categorization of the papers across these special issues.…”

Section: Optimization Models and Network Robustnessmentioning

confidence: 99%

In search of network resilience: An optimization‐based view

et al. 2020

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Fifty years of research in Networks coincides with 50 years of advances in resilience theory and applications. The purpose of this review is to identify how these two technical communities influenced each other in the past and can bolster each other in the future. Advances in resilience theory show that there are at least four ways networks demonstrate resilience: robustness, rebound, extensibility, and adaptability. Research published in Networks and by the broader network optimization community has focused primarily on technical methods for robustness and rebound. We review this literature to organize seminal problems and papers on the ability of networks to manage increasing stressors and return to normal activities after a stressful event. In contrast, the Networks community has made less progress addressing issues for network extensibility and adaptability. Extensibility refers to the ability to stretch current operations to surprising situations and adaptability refers to the ability to sustain operations into the future. We discuss ways to harness existing network optimization methods to study these forms of resilience and outline their limitations. We conclude by providing a research agenda that ensures the Networks community remains central to future advances in resilience while being pragmatic about the limitations of network optimization for achieving this task.

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“…In the daily life of modern human beings, there are all kinds of networks around us, such as the transportation network that can provide human beings with a convenient travel and material exchange [1,2], and the communication network that can facilitate people to transmit information [3][4][5]. They facilitate our daily life all the time.…”

Section: Introductionmentioning

confidence: 99%

Robustness of probability routing strategy in interconnection networks

Ma,

Wei

2024

Eng. Res. Express

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With the rapid development of complex networks, the research on robustness has gradually attracted the attention of scholars. In this paper, the research mainly focuses on the analysis of the stability and vulnerability of probability routing strategy on interconnection networks. Firstly, random attacks or target attacks are carried out on the network, and then its maximum connected subgraph is calculated, and the routing strategy is applied to the maximum connected subgraph. This paper evaluates the strategy’s robustness by examining some network parameters. Simulation outcomes reveal that in comparison to effective routing and the shortest path routing strategies, the probability routing strategy demonstrates superior robustness, evidenced by its performance in terms of network traffic capacity and average path length.

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Resilience of communication networks to random failures and disasters: An optimization perspective

Cited by 8 publications

References 10 publications

Electronic Communication Fault Signal Recognition Based on Data Mining Algorithm

Electronic Communication Fault Signal Recognition Based on Data Mining Algorithm

In search of network resilience: An optimization‐based view

Robustness of probability routing strategy in interconnection networks

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