7,586 research outputs found

    Un nuevo esquema de agrupación para redes sensoras inalámbricas de radio cognitivas heterogéneas

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    Introduction: This article is the product of the research “Learning-based Spectrum Analysis and Prediction in Cognitive Radio Sensor Networks”, developed at Sejong University in the year 2019. Problem: Most of the clustering schemes for distributed cognitive radio-enabled wireless sensor networks consider homogeneous cognitive radio-enabled wireless sensors. Many clustering schemes for such homogeneouscognitive radio-enabled wireless sensor networks waste resources and suffer from energy inefficiency because of the unnecessary overheads. Objective: The objective of the research is to propose a node clustering scheme that conserves energy and prolongs network lifetime. Methodology: A heterogeneous cognitive radio-enabled wireless sensor network in which only a few nodes have a cognitive radio module and the other nodes are normal sensor nodes. Along with the hardware cost, theproposed scheme is efficient in energy consumption. Results: We simulated the proposed scheme and compared it with the homogeneous cognitive radio-enabled wireless sensor networks. The results show that the proposed scheme is efficient in terms of energyconsumption. Conclusion: The proposed node clustering scheme performs better in terms of network energy conservation and network partition. Originality: There are heterogeneous node clustering schemes in the literature for cooperative spectrum sensing and energy efficiency, but to the best of our knowledge, there is no study that proposes a non-cognitiveradio-enabled sensor clustering for energy conservation along with cognitive radio-enabled wireless sensors. Limitations: The deployment of the proposed special device for cognitive radio-enabled wireless sensors is complicated and requires special hardware with better battery powered cognitive sensor nodes

    Byzantine Attack and Defense in Cognitive Radio Networks: A Survey

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    The Byzantine attack in cooperative spectrum sensing (CSS), also known as the spectrum sensing data falsification (SSDF) attack in the literature, is one of the key adversaries to the success of cognitive radio networks (CRNs). In the past couple of years, the research on the Byzantine attack and defense strategies has gained worldwide increasing attention. In this paper, we provide a comprehensive survey and tutorial on the recent advances in the Byzantine attack and defense for CSS in CRNs. Specifically, we first briefly present the preliminaries of CSS for general readers, including signal detection techniques, hypothesis testing, and data fusion. Second, we analyze the spear and shield relation between Byzantine attack and defense from three aspects: the vulnerability of CSS to attack, the obstacles in CSS to defense, and the games between attack and defense. Then, we propose a taxonomy of the existing Byzantine attack behaviors and elaborate on the corresponding attack parameters, which determine where, who, how, and when to launch attacks. Next, from the perspectives of homogeneous or heterogeneous scenarios, we classify the existing defense algorithms, and provide an in-depth tutorial on the state-of-the-art Byzantine defense schemes, commonly known as robust or secure CSS in the literature. Furthermore, we highlight the unsolved research challenges and depict the future research directions.Comment: Accepted by IEEE Communications Surveys and Tutoiral
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