Abstract The rapid evolution of the Internet of Nano Things (IoNT) and Fog Computing presents new opportunities for creating advanced smart systems that are both efficient and responsive. Integrating IoNT with Fog Computing offers a powerful paradigm that can address the limitations of cloud-centric architectures, particularly in terms of latency, bandwidth, and real-time processing. The paper explores the synergistic combination of IoNT and Fog Computing, focusing on the development of a hybrid architecture that leverages the proximity and computational capabilities of fog nodes to process data generated by nanoscale devices. Key challenges such as resource management, data processing efficiency, and security concerns are addressed in this study. The proposed architecture not only enhances the performance of smart systems by reducing latency and optimizing resource utilization but also ensures robust security and privacy for the vast amounts of generated data. A comprehensive dataset was generated to assess the integration of the IoNT with Fog Computing, focusing on environmental parameters such as Temperature, Humidity, and Wind Speed, as collected from five IoNT sensors. Python was employed to generate and augment this dataset, ensuring the accurate representation of varied environmental conditions. The data transmission between IoNT sensors and FogNode_1 successfully demonstrated the framework’s ability to capture and process real-time environmental information. Aggregated data from the fog and cloud layers confirmed the system’s efficiency in reducing latency and maintaining data integrity. Furthermore, the implementation of advanced communication protocols and effective resource management highlights the robustness of the integration, contributing to the real-time monitoring and decision-making processes in environmental applications. As well as, this study compares Fog Computing and Cloud Computing, concluding that Fog Computing offers significant advantages in areas like latency, bandwidth utilization, resource efficiency, security, privacy, real-time processing, and edge intelligence. These benefits make Fog Computing particularly suitable for applications requiring low latency, local data processing, enhanced security, and the ability to leverage edge intelligence. While Cloud Computing may have advantages in certain areas, Fog Computing’s overall performance and versatility make it a compelling choice for those seeking to optimize their computing infrastructure. This research aims to pave the way for more resilient and intelligent smart systems that can operate effectively in various domains, including healthcare, environmental monitoring, and industrial automation.

Abstract Recently, significant research has been conducted on magnetic metamaterials that exhibit negative permeability and operate within the GHz and MHz frequency ranges. These metamaterial structures can be utilized to improve the efficiency of near-field wireless power transfer systems, subterranean communication, and position sensors. However, in most cases, they are only designed to work for a single application. This study focuses on examining the transmission of magneto-inductive waves in magnetic metamaterial structures with ordered arrangements. This structure can be used simultaneously for wireless power transfer and near-field communications. The unit cell is formed by a spiral with five turns that is implanted on a FR-4 substrate. An external capacitor was used to regulate the resonant frequency of the magnetic metamaterial unit cell. The properties of magneto-inductive waves, including reflection, transmission response, and field distribution on the waveguide, have been extensively computed and simulated. The obtained results indicate that both 1-dimensional and 2-dimensional magnetic metamaterial configurations possess the ability to conduct electromagnetic waves and propagate magnetic field energy at a frequency of 13.56 MHz. The straight and cross path configurations were also investigated to identify the optimal configuration on the 2-dimensional metamaterial slab.

Abstract Non-Orthogonal Multiple Access (NOMA) and Cognitive Radio (CR) technologies present viable solutions to mitigate spectrum scarcity in wireless communication systems. This paper focuses on evaluating the performance of CR-NOMA networks, particularly for user devices operating under a Simultaneous Wireless Information and Power Transfer (SWIPT) framework. We derive explicit mathematical expressions for key performance metrics, including outage probability (OP) and system throughput, as they relate to various power allocation coefficients. Comprehensive simulations are conducted to validate our theoretical findings, revealing that appropriate power allocation significantly impacts user fairness and overall network throughput. The analysis covers a wide range of realistic channel conditions, including Rayleigh fading, to ensure robustness. Additionally, our study addresses the challenge of limiting interference to the primary network by optimizing the transmission power of secondary users while adhering to interference constraints. The results show that the primary user device (D 1 ) consistently outperforms the secondary user device (D 2 ), emphasizing the importance of strategic resource management. These contributions provide deeper insights into the factors affecting outage performance in CR-NOMA systems, offering effective solutions for enhancing the robustness, fairness, and efficiency of next-generation wireless communication networks.