Cognitive radio in the context of internet of things using a novel future internet architecture called NovaGenesis

Alberti, Antônio Marcos; Mazzer, Daniel; Bontempo, M. M.; Oliveira, Lúcio H.; Righi, Rodrigo da Rosa; Sodr, Arismar Cerqueira

doi:10.1016/j.compeleceng.2016.07.008

Cited by 27 publications

(27 citation statements)

References 14 publications

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“…Nevertheless, EDs are generally susceptible to errors such as false alarms and misdetections, which often arise under noise uncertainty conditions in low signal‐to‐noise ratio (SNR) regimes (< 3 dB) . To minimize these errors, modern EDs use adaptive threshold estimation algorithms (ATAs) to estimate useful thresholds without prior knowledge of the noise level in the spectra . Adapting threshold values under noise uncertainty conditions describe the adaptation problem.…”

Section: Introductionmentioning

confidence: 99%

“…18 To minimize these errors, modern EDs use adaptive threshold estimation algorithms (ATAs) to estimate useful thresholds without prior knowledge of the noise level in the spectra. 19 Adapting threshold values under noise uncertainty conditions describe the adaptation problem. Furthermore, ATAs may need to adjust their parameter values automatically to improve performance under dynamic spectra conditions, and we refer to this requirement for auto-tuning as the autonomous problem.…”

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confidence: 99%

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Histogram partitioning algorithms for adaptive and autonomous threshold estimation in cognitive radio–based industrial wireless sensor networks

Onumanyi

Abu‐Mahfouz

Hancke

2019

Trans Emerging Tel Tech

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Modern energy detectors typically use adaptive threshold estimation algorithms to improve signal detection in cognitive radio–based industrial wireless sensor networks (CR‐IWSNs). However, a number of adaptive threshold estimation algorithms often perform poorly under noise uncertainty conditions since they are typically unable to auto‐adapt their parameter values per changing spectra conditions. Consequently, in this paper, we have developed two new algorithms to accurately and autonomously estimate threshold values in CR‐IWSNs under dynamic spectra conditions. The first algorithm is a parametric‐based technique termed the histogram partitioning algorithm, whereas the second algorithm is a fully autonomous variant termed the mean‐based histogram partitioning algorithm. We have evaluated and compared both algorithms with some well‐known methods under different CR sensing conditions. Our findings indicate that both algorithms maintained over 90% probability of detection in both narrow and wideband sensing conditions and less than 10% probability of false alarm under noise‐only conditions. Both algorithms are quick and highly scalable with a time complexity of O(V), where V is the total number of input samples. The simplicity, effectiveness, and viability of both algorithms make them typically suited for use in CR‐IWSN applications.

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Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

Histogram partitioning algorithms for adaptive and autonomous threshold estimation in cognitive radio–based industrial wireless sensor networks

Onumanyi

Abu‐Mahfouz

Hancke

2019

Trans Emerging Tel Tech

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“…O Jammingé definido como sendo a transmissão de um sinal de rádio com o intuito de interferir nas comunicações de uma rede de radiofrequência (RF) de forma intencional [Adamy 2004]. Existe uma outra forma de interferência conhecida como interferência de radiofrequência (em Inglês, RFI -radio frequency interference), que ocorre devido Em Alberti et al [Alberti et al 2017]é proposta uma arquitetura de rádio cognitivo que analisa e armazena as informações de uso do espectro de frequência da rede publicando assim os canais disponíveis e ocupados. Nossa proposta se baseia nesta arquitetura.…”

Section: Ataque Jammingunclassified

Uma Proposta de Contramedida ao Ataque Jamming em Redes IEEE 802.15.4 utilizando Rádio Cognitivo

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Bontempo

Santos

et al. 2019

Anais Do Workshop De Segurança Cibernética Em Dispositivos Conectados (WSCDC)

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As redes de sensores sem fio utilizam de meios de comunicação compartilhados para a transmissão de dados. Com isto, se torna fácil para um atacante interferir nas transmissõs destas redes através de ataques de negação de serviço conhecidos como Jamming. Estes ataques podem ser feitos através de dispositivos chamados de Jammers, que emitem sinais aleatórios de dados, visando derrubar as comunicações das redes de sensores. Neste artigo, estudamos as características do ataque de interferência Jamming sobre a rede IEEE 802.15.4 e propomos uma contramedida a esse ataque utilizando um sistema de rádio cognitivo definido por software para detectar e proteger a rede.

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“…It proposes an embedded and simplicity agreeable spectrum identifying arrangement, which has been probably completed. Additionally, Alberti et al [19] exhibited a dispersed programming-controlled sector aware spectrum distinguishing configuration to collect and dismember the range utilizes information. Finally, the proposed technique is joined to a future Internet configuration called NovaGenesis.…”

Section: Cognitive Iotmentioning

confidence: 99%

A Survey on Data Perception in Cognitive Internet of Things

Bhajantri¹,

Balugari

2019

JTIT

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A Cognitive Internet of Things (CIoT) is a brand of Internet of Things (IoT) with cognitive and agreeable mechanisms, which are incorporated to advance performance and accomplish insights into real world environments. CIoT can perceive present system’s conditions, analyze the apparent information, make smart choices, and increase the network performance. In this survey paper, we present classiﬁcations of data perception techniques used in CIoT. This paper also compares the data perception works against energy consumption, network life-time, resource allocation, and throughput, as well as quality of data and delay. In addition, simulation tools for IoT and their performance are discussed. Finally, we provide the model of cognitive agent-based data perception in CIoT for future research and development, which ensures the network performance in terms of reliability, energy eﬃcient, accuracy, scalable, fault tolerant, and quality of data.

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Cognitive radio in the context of internet of things using a novel future internet architecture called NovaGenesis

Cited by 27 publications

References 14 publications

Histogram partitioning algorithms for adaptive and autonomous threshold estimation in cognitive radio–based industrial wireless sensor networks

Histogram partitioning algorithms for adaptive and autonomous threshold estimation in cognitive radio–based industrial wireless sensor networks

Uma Proposta de Contramedida ao Ataque Jamming em Redes IEEE 802.15.4 utilizando Rádio Cognitivo

A Survey on Data Perception in Cognitive Internet of Things

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