Faulty RJ45 connectors detection on radio base station using deep learning

Dantas, Marrone; Leuchtenberg, Pedro Henrique Dreyer; Souza, Gabriel Fonseca Reis de; Bezerra, Daniel; Souza, Ricardo; Lins, Silvia; Kelner, Judith; Sadok, Djamel

doi:10.1007/s11042-022-12694-6

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2023

2024

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Cited by 2 publications

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“…The quantity of data that can pass through a damaged copper, cable, or fiber-optic cable without packet loss will likely be reduced. The manuscript by Dantas, M. S. M., et al (2022) examines missing or unplugged connectors and detects them in classification.…”

Section: Introductionmentioning

confidence: 99%

Simulation-Based Network Fault Injection in the Cloudsim Plus Cloud Simulation Environment

Asadova¹,

Kertész²,

Lovas³

2023

AzJHPC

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One effective method for assessing the dependability of computer systems is fault injection. This deliberate technique introduces faults into a system to assess its resilience and ability to handle abnormal conditions. Therefore, this study investigates and simulates the different network problems in the CloudSim Plus environment. CloudSim Plus is a simulation framework that enables the modeling and simulation of cloud computing environments, allowing researchers and practitioners to evaluate the performance and behavior of cloud-based systems and algorithms. Network fault detection and its management are essential duties in cloud systems. Moreover, the feasibility of manual monitoring and involvement has decreased as these infrastructures expand and change. This paper briefly introduces network problems and fault injection outcomes in CloudSim Plus nodes.

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Section: Introductionmentioning

confidence: 99%