The transition to 6th Generation (6G) cellular networks offers significant improvements over 5th Generation (5G), enhancing data transfer, reducing latency, and improving network reliability. Advanced Multiple-Input Multiple-Output (MIMO) technology in 6G boosts network efficiency, particularly benefiting Ultra-Reliable Low-Latency Communications (URLLC). This paper reviews literature on resource management in the Internet of Things (IoT) within the 6G context. We categorize the study into four segments: network-aware resource management, dynamic resource allocation, predictive resource distribution based on traffic and architecture, and energy-centric resource allocation considering IoT device mobility and location. We provide a detailed perspective on current research and highlight future research avenues. Key contributions include a comparative study of IoT resource management techniques, an overview of resource management across LTE, 5G, and 6G networks, insights into applications like Intelligent Transportation Systems (ITS), Industrial IoT (IIoT), and Mobile CrowdSensing (MCS), and an emphasis on upcoming challenges. We emphasize the crucial role of efficient resource management in IoT, particularly in the 6G landscape.

In recent years, the IoT has emerged as the most promising technology in the key evolution of industry 4.0/industry 5.0, smart home automation (SHA), smart cities, energy savings and many other areas of wireless communication. There is a massively growing number of static and mobile IoT devices with a diversified range of speed and bandwidth, along with a growing demand for high data rates, which makes the network denser and more complicated. In this context, the next-generation communication technology, i.e., sixth generation (6G), is trying to build up the base to meet the imperative need of future network deployment. This article adopts the vision for 6G IoT systems and proposes an IoT-based real-time location monitoring system using Bluetooth Low Energy (BLE) for underground communication applications. An application-based analysis of industrial positioning systems is also presented.

This paper addresses the current technical challenge of an impedance mismatch between the requirements of smart connected object applications within the sensing environment and the characteristics of today's cloud infrastructure. We investigate the possibility to offload cloud tasks, such as storage and data signal processing to the edge of the network, thus decreasing the latency associated with performing those tasks within the cloud. The research scenario is an e-Health laboratory implementation where the real-time processing is performed by the home PC, while the extracted metadata is sent to the cloud for further processing.

Recent revolutionary advancements in the services as observed with the use cases of Industry 5.0, consumer electronics 2.0/smart devices 2.0, digital healthcare ecosystem, Internet-of-Things (IoT), advanced digital finance/currency, and Non-Terrestrial Network (NTN) expansion, to name a few, have resulted in a spectacular growth in the number of wireless-connected devices. Subsequently, this has drastically increased the demands for network capacity, channel capacity, reliability, privacy, and security provisions. Despite that, the 5 ^th Generation (5 G) of wireless communication networks has introduced various innovative services such as Ultra-Reliable Low Latency Communication (URLLCs), Massive Machine Type Communication (mMTCs), and Enhanced Mobile Broadband (eMBB). These services only support isolated operations and the requisite reliable service delivery remains a challenge. The Beyond 5 G (B5G)/6 ^th Generation (6 G) wireless networks aim at simultaneously providing multiple integrated services through intelligent network operations with ultra-high speed and reliability supporting integrated NTN and terrestrial networks. However, the prospect of such an extensively connected decentralized 3D wireless network also foresees security concerns, underscoring the necessity for seamless and infrastructure-free (decentralized) security solutions. The conventional security mechanisms are considered inadequate to ensure the security provisions of such extensive, decentralized, and heterogeneous networks. Physical Layer Security (PLS) is a promising technique to extend seamless and infrastructure-less security solutions, ensuring the availability, confidentiality, and integrity of legitimate transmissions. This paper provides a comprehensive overview with tutorials and presents the state-of-the-art of PLS, focusing mainly on NTN wireless communications. Furthermore, current research challenges, open issues, and future research directions are also thoroughly discussed in an amalgamation of various emerging 6 G technologies. Finally, we provide an overview of implementation challenges in NTN and potential solutions to support the standardization progression of NTN in upcoming releases of 3 ^rd Generation Partnership Project (3GPP).

Despite of their energy efficiency, most of WSN’s cluster-based routing protocols are vulnerable to security threats. Selective forwarding and black hole attacks are ranked among the most devastating attacks which they target this class of routing protocols. In this paper, a new centralized intrusion detection system is proposed to detect selective forwarding and black hole attacks in cluster-based wireless sensors networks. The main idea is the use of a centralized detection approach, where the base station decides on potential intrusions based on control packets sent from the cluster heads. The proposed intrusion detection technique is simple and energy efficient, it is thus suitable for sensor nodes with resource constrained. The simulation results confirm the expected performance of the proposed IDS in terms of security and energy efficiency.