A Survey of Decision-Theoretic Models for Cognitive Internet of Things (CIoT)

Zaheer, Khaqan; Othman, Мohamed; Rehmani, Mubashir Husain; Perumal, Thinagaran

doi:10.1109/access.2018.2825282

Cited by 26 publications

(14 citation statements)

References 80 publications

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“…Tabla 3: Descripción de las técnicas para toma de decisiones basadas en inteligencia artificial (CC=Complejidad computacional). (Darwish et al, 2018;Iftikhar et al, 2019;Luce y Raiffa, 1958;Ren y Wong, 2019;Rizk et al, 2018;Romero et al, 2019;Song et al, 2019;Zaheer et al, 2018) *Interferenci a en las redes *Intercambio de espectro *Redes eléctricas inteligentes *Computació n grid…”

Section: Comparación De Los Algoritmosunclassified

Algoritmos para Toma de Decisiones en Redes Inalámbricas Cognitivas: una Revisión

Giral¹,

Hernández²,

Sarmiento³

2019

Inf. tecnol.

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El objetivo de este artículo es presentar una revisión de técnicas basadas en inteligencia artificial para el proceso de toma de decisiones en redes de radio cognitiva. Las redes de radio cognitiva surgieron como una solución para resolver los problemas de asignación fija y de escasez del espectro, trabajan con un modelo de gestión que se denomina ciclo cognitivo, donde la toma de decisiones es clave, ya que permite seleccionar la oportunidad espectral más adecuada. A partir de literatura actualizada, se analizan estrategias que implementan máquinas de aprendizaje automático, algoritmos bioinspirados, teoría de juegos y algoritmos de consensos. Finalmente, el documento presenta los retos para el proceso de toma decisiones, donde se resalta la necesidad de seguir aprovechando los avances en inteligencia artificial para obtener mejores resultados. Sin embargo, las estrategias deben ser escalables para facilitar la carga computacional y poder resolver problemas de mayor complejidad.

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Section: Comparación De Los Algoritmosunclassified

Algoritmos para Toma de Decisiones en Redes Inalámbricas Cognitivas: una Revisión

Giral¹,

Hernández²,

Sarmiento³

2019

Inf. tecnol.

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“…With the development of IoT, energy efficiency and spectrum efficiency have been two essential concerns due to the rapidly growing number of IoT devices [3,4]. Since the technique of IoT spectrum sharing is able to make better use of the spectrum resource, many experts and scholars have a deep study on it then apply to IoT systems [5][6][7][8]. Some IoT spectrum-sharing protocols are proposed in [9][10][11].…”

Section: Introductionmentioning

confidence: 99%

“…Most existing works as mentioned above mainly discussed about designing a better system of spectrumsharing IoT [8,10,12] or EH-abled IoT [19,27,28]. e research studies about cooperative information exchange in EH-abled IoT with spectrum sharing are few.…”

Section: Introductionmentioning

confidence: 99%

Energy Harvesting and Information Transmission Mode Design for Cooperative EH-Abled IoT Applications in beyond 5G Networks

Gao

Zhang

et al. 2020

Wireless Communications and Mobile Computing

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Energy harvesting (EH) technology is considered to be a promising approach to provide enough energy for energy-constrained Internet of Things (IoT). In this paper, we propose an energy harvesting and information transmission mode for the spectrum sharing system with cooperative EH-abled IoT applications in beyond 5G networks. Different from most existing IoT spectrum-sharing research studies, in our system, both primary user (PU) and IoT devices (IDs) collect energy for their information transmission. In addition, for all IDs, they should realize two communication functions: working as relays to help the information transfer process of PU and completing their own information transmission. We analytically derive exact expressions for the throughput of the primary system and IoT system and then formulate two objective functions. It is easy to see that power splitting ratio, dynamic EH ratio, power sharing ratio, and relay selection should be optimized to get the best performance for different communication circumstances. Actually, it is a hybrid NP-hard problem to optimize these parameters and traditional algorithms cannot solve it well. Therefore, a novel algorithm-quantum whale optimization algorithm (QWOA) is proposed to obtain the best performance. Simulation results show the good performance of QWOA in different simulation scenarios.

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“…Kim proposed using CR techniques for IoT-based systems to manage the shortage of spectrum for IoT devices [10]. Zaheer and others provided a survey of the existing decision theoretic models and their usage for CIoT [11]; furthermore, an architectural CIoT framework was proposed to discuss the open issues and solution for potential challenges emerging in the CIoT research. Considering that spectrum decision by unlicensed users of CR is important in CR-based IoT in 5G and beyond networks, Akhtar described a scientific supported spectrum decision support framework for CR networks [12], in which the goal is the same as that reported in [8] and [9].…”

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confidence: 99%

“…Although a comprehensive study on recent advances in CR technology for IoT has been provided [8][9][10][11][12], many questions are yet to be explored, such as the attack and defense involved in CIoT. In [13], Chen and others investigated the vulnerability of the IoT infrastructure under intentional attacks by relating network resilience to percolation-based connectivity.…”

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confidence: 99%

Sequential fusion to defend against sensing data falsification attack for cognitive Internet of Things

Song

et al. 2020

ETRI Journal

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Internet of Things (IoT) is considered the future network to support wireless communications. To realize an IoT network, sufficient spectrum should be allocated for the rapidly increasing IoT devices. Through cognitive radio, unlicensed IoT devices exploit cooperative spectrum sensing (CSS) to opportunistically access a licensed spectrum without causing harmful interference to licensed primary users (PUs), thereby effectively improving the spectrum utilization. However, an open access cognitive IoT allows abnormal IoT devices to undermine the CSS process. Herein, we first establish a hard‐combining attack model according to the malicious behavior of falsifying sensing data. Subsequently, we propose a weighted sequential hypothesis test (WSHT) to increase the PU detection accuracy and decrease the sampling number, which comprises the data transmission status‐trust evaluation mechanism, sensing data availability, and sequential hypothesis test. Finally, simulation results show that when various attacks are encountered, the requirements of the WSHT are less than those of the conventional WSHT for a better detection performance.

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A Survey of Decision-Theoretic Models for Cognitive Internet of Things (CIoT)

Cited by 26 publications

References 80 publications

Algoritmos para Toma de Decisiones en Redes Inalámbricas Cognitivas: una Revisión

Algoritmos para Toma de Decisiones en Redes Inalámbricas Cognitivas: una Revisión

Energy Harvesting and Information Transmission Mode Design for Cooperative EH-Abled IoT Applications in beyond 5G Networks

Sequential fusion to defend against sensing data falsification attack for cognitive Internet of Things

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