Performance Evaluation of an IEEE 802.11g Network in an Industrial Environment

Valadares, Dalton Cézane Gomes; Joseana, Araujo; Perkusich, Ângelo; Marco, Spohn; Elmar, Melcher; Costa, Alexandre Araújo; Felipe, Ramos; Natalia, Albuquerque

doi:10.1109/tla.2020.9082924

Cited by 3 publications

(4 citation statements)

References 17 publications

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“…The volume of data acquired at the received signal is measured by the time it requires for transfer of data in the method, which is referred to as throughput in eqn. (22).…”

Section: Throughputmentioning

confidence: 99%

“…Amount of data received to the users 𝐷𝑒𝑙𝑎𝑦 𝑜𝑓 𝑡𝑖𝑚𝑒 (22) Figure 7 compares the proposed technique's obtained throughput to current models for varied numbers of UAVs.…”

Section: 𝑇 =mentioning

confidence: 99%

“…Multi-UAV sets are built out of a network of different communication connections [21]. The IEEE 802.11 standard model has been used in the UAV system [22]. The IEEE 802.14.4 specification is suitable for UAV-to-UAV communications in cases when bandwidth is constrained [23].…”

Section: Introductionmentioning

confidence: 99%

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Novel Hybrid Deep Optimized Machine Learning Model for Energy Efficient Cluster Selection in Unmanned Aerial Vehicle Networks

Chandrashekhar Goswami

2024

jes

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Unmanned Aerial Vehicles (UAVs) have grown into a more powerful type of data transmission due to this rapid progress of evolution of wireless communication technology. In addition, UAVs have been proven to be effective in a variety of applications, including intelligent transport, disaster risk management, surveillance, and environmental monitoring. When UAVs are deployed randomly, however, they can effectively accomplish challenging tasks because of the UAVs’ has low battery capacity, quick mobility, and dynamic in nature orientation. Due to this reason, a new technique must be designed for an optimal energy efficient UAV clustering as well as data routing protocols. In this work proposes a new hybrid model of Emperor penguin-based Generalized Approximate Reasoning Based Intelligent Control (EP-GARIC) cluster-based network topology. Furthermore, the optimal routing function is achieved by the proposed Artificial Jellyfish Optimization (AJO). The implementation of this research is carried out using Network Simulator (NS2). The simulation results displays the effective performance of the suggested approach in terms of reduced energy consumption, improved packet delivery ratio, reduced loss, and so on over compared to the conventional approaches

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“…The volume of data acquired at the received signal is measured by the time it requires for transfer of data in the method, which is referred to as throughput in eqn. (22).…”

Section: Throughputmentioning

confidence: 99%

Section: 𝑇 =mentioning

confidence: 99%

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Novel Hybrid Deep Optimized Machine Learning Model for Energy Efficient Cluster Selection in Unmanned Aerial Vehicle Networks

Chandrashekhar Goswami

2024

jes

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“…A tecnologia IEEE802.11 por sua popularidade, vem sendo amplamente usada em aplicações na indústria (Valadares et al, 2020). Este padrão apresenta bons resultados em termos de cumprir os requisitos de atraso e perdas, mas ainda apresenta um alto consumo de energia nas versões mais comumente encontradas do mercado.…”

Section: Introductionunclassified

Redes sem fio no monitoramento de falhas de máquinas: uma comparação de tecnologias sem fio com baixa densidade de nodos

Fertig

Valle

Silva

et al. 2022

RBCA

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A utilização de redes sem fio em ambientes industriais vem se tornando cada vez mais uma realidade. As principais motivações são o baixo custo de implantação e manutenção, em contraposição às redes cabeadas. Dentro da miríade de aplicações na indústria, o monitoramento de máquinas é particularmente importante pois permite predizer ou detectar a ocorrência de falhas, mitigando custos devido a uma sequência de eventos disruptivos. Principalmente em sistemas legados, os sensores sem fio podem requerer baterias que possibilitem uma longa sobrevivência da rede. O padrão IEEE802.11 por sua popularidade, vem sendo usado no monitoramento de máquinas, apesar do alto consumo de energia. Uma das alternativas é a tecnologia unslotted IEEE802.15.4 e a variante determinista DSME, que, apesar de baixas taxas de transmissão, possuem um perfil de consumo de energia muito baixo. Este trabalho visa avaliar um cenário em topologia estrela, com um salto e com baixa densidade de sensores, comparando estas tecnologias em termos de taxa de pacotes recebidos e energia residual. A avaliação é por simulação e confirma o alto consumo IEEE802.11, porém mostra que as vantagens do DSME, não são tão evidentes, podendo ser melhorado se explorado nas suas características de multifrequência.

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Two-tier MPC architecture for AGVs navigation assisted by edge computing in an industrial scenario

Omena¹,

Santos²,

Perkusich³

et al. 2023

Internet of Things

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Performance Evaluation of an IEEE 802.11g Network in an Industrial Environment

Cited by 3 publications

References 17 publications

Novel Hybrid Deep Optimized Machine Learning Model for Energy Efficient Cluster Selection in Unmanned Aerial Vehicle Networks

Novel Hybrid Deep Optimized Machine Learning Model for Energy Efficient Cluster Selection in Unmanned Aerial Vehicle Networks

Redes sem fio no monitoramento de falhas de máquinas: uma comparação de tecnologias sem fio com baixa densidade de nodos

Two-tier MPC architecture for AGVs navigation assisted by edge computing in an industrial scenario

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