Integration Of Wireless Networks Research Articles

Exploring Fault Tolerance Consensus for Wireless Sensor Networks: A Comprehensive Detailed Study

The integration of wireless networks into modern communication systems has revolutionized information exchange across various applications. However, achieving reliable agreement in these networks is significantly impeded by their unique properties, such as blurring, interruption, and transparency. A fundamental component of distributed systems, fault-tolerant consensus ensures that nodes in the network can agree on a consistent value even in the presence of malfunctioning or corrupted elements. This study explores both non-Byzantine and Byzantine fault-tolerant consensus approaches, with a focus on achieving agreement in the presence of benign faults. The importance of fault-tolerant consensus in wireless connections is underscored, particularly in applications like wireless blockchain, IoT, and vehicular networks. The research delves into wireless network-specific fault-tolerant consensus algorithms to address the specific challenges posed by networking environments. Furthermore, a comparative analysis of Byzantine Fault Tolerance mechanisms in distributed systems is provided to shed light on their features and benefits. It highlights the importance of ensuring system reliability and consistency in wireless networks to maintain seamless communication and data integrity. Moreover, the paper emphasizes the critical role of fault-tolerant consensus in enhancing system resilience and performance. It underscores the need for robust algorithms and protocols to detect and mitigate errors, ensuring reliable communication and coordination despite potential node failures. By providing insights into fault-tolerant consensus mechanisms tailored to dynamic conditions, the study aims to optimize system adaptation and effectively mitigate both Byzantine and non-Byzantine failures in wireless network environments.

Joint Caching, Communication, and Trajectory Optimization in Air-Ground Integrated Wireless Networks With Multiple UAVs and Multiple BSs

Joint Caching, Communication, and Trajectory Optimization in Air-Ground Integrated Wireless Networks With Multiple UAVs and Multiple BSs

A Survey Paper on IoTAgroFlow Advancing Agriculture with Smart Monitoring and Irrigation Systems

Precipitation and climate change have fluctuated over the past ten years. As a result, a large number of Indian farmers have recently embraced climate-smart farming practices known as "smart agriculture." Among the most significant uses of IOT is smart agriculture. This boosts yield while wasting less water and fertilizer. Smart agriculture refers to the application of Internet of Things (IoT)-based automated and controlled information technology. IOT is widely used in all wireless communication environments and is growing quickly. Based on the actual circumstances of the agricultural system, this project studied and investigated the integration of IOT technology, sensor technology, and wireless networks. soil temperature, relative humidity, and pH are measured by temperature, humidity, and pH sensors. a hybrid strategy combining wireless and Internet connectivity.

Dynamic resource management in integrated NOMA terrestrial–satellite networks using multi-agent reinforcement learning

The integration of terrestrial and satellite wireless communication networks offers a practical solution to enhance network coverage, connectivity, and cost-effectiveness. Moreover, in today’s interconnected world, connectivity’s reliable and widespread availability is increasingly important across various domains. This is especially more crucial for applications like the Internet of Things (IoT), remote sensing, disaster management, and bridging the digital divide. However, allocating the limited network resources efficiently and ensuring seamless handover between satellite and terrestrial networks present significant challenges. Therefore, this study introduces a resource allocation framework for integrated satellite–terrestrial networks to address these challenges. The framework leverages local cache pool deployments and non-orthogonal multiple access (NOMA) to reduce time delays and improve energy efficiency. Our proposed approach utilizes a multi-agent enabled deep deterministic policy gradient algorithm (MADDPG) to optimize user association, cache design, and transmission power control, resulting in enhanced energy efficiency. The approach comprises two phases: User Association and Power Control, where users are treated as agents, and Cache Optimization, where the satellite (Bs) is considered the agent. Through extensive simulations, we demonstrate that our approach surpasses conventional single-agent deep reinforcement learning algorithms in addressing cache design and resource allocation challenges in integrated terrestrial–satellite networks. Specifically, our proposed approach achieves significantly higher energy efficiency and reduced time delays compared to existing methods. This research highlights the importance and addresses the need for efficient resource allocation and cache design in integrated terrestrial–satellite networks, paving the way for enhanced connectivity and improved network performance in various applications.

NeXT: Architecture, prototyping and measurement of a software-defined testing framework for integrated RF network simulation, experimentation and optimization

To support rigorous and repeatable experimental evaluation of wireless networked systems, the community has made significant efforts to develop experimentation platforms. However, existing platforms primarily focus on the data plane, i.e., the forwarding infrastructure, without explicitly considering the control plane. To fill this gap, in this work we develop NeXT, a software-defined playground with integrated wireless network simulation, experimentation and optimization capabilities. We first design the data plane, which integrates an event-driven broadband wireless network simulator called UBSim and a software-defined wireless network testing facility called RoboNet. We then design NeXT’s control plane, where a software toolchain is developed and deployed to support both traditional model-based optimization and new data-driven control techniques. We showcase the experimentation capability of NeXT considering a series of optimization and control problems in different wireless networks.

Performance Analysis of the WDM Schemes for RoF System with Various Bit Rate

Communication that combines the methodologies of the two communications can be considered as communication fiber optic communication and can be used in communication systems and wireless. The integration of optical and wireless networks can function to increase mobility and capacity as well as reduce costs in access networks. Radio over fiber (RoF) can be a solution for many problems because it can control many base stations (BS) connected to a central station (CS) with an optical fiber. The high bit error rate (BER) and low Q factor value are caused by the Rof signal head received in low quality, so the receiver may not operate on high data speed networks. The solution to different signal problems and can be done with single mode fiber is the Wavelength Division Multiplexing (WDM) network. BER must be reduced to a guaranteed value, and the Q factor must be increased. WDM-RoF probes with different fiber lengths at various channel distances will be: simulated using Optisystem software, and the performance of the RoF receiver is measured and analyzed depending on the obtained BER, Q-factor value, and eye aperture height. The effects of degradation factors such as attenuation and dispersion are very limited with the addition of EDFA amplifier to Single Mode Fiber (SMF). The higher the bit rate of a communication system, the lower the performance of the system. In this study, analysis of the WDM-Rof system with bit rate variations was carried out to determine the bit rate value that still met the standard. From the simulation results, the Q-Factor and BER values at a bit rate of 11 Gbps do not meet the standards, i.e 4.50508 and 2.5390e-006.

6G - SIXTH GENERATION MOBILE NETWORKS

<p style="text-align: justify;">In this paper, we will present mobile networks of the sixth generation, popularly called 6G. It is expected that this generation of mobile networks will cause a complete revolution in the world of technology but also the daily life of the people who use it. The 6G mobile network will not only be a continuation of the 5G mobile network, but will represent a completely new concept of integration of all existing and future segments of the idea of global networking. 6G networks are expected to reach significantly higher levels of heterogeneity than their predecessors and to support applications that are far more advanced than current mobile usage scenarios, such as virtual and augmented reality (VR/AR), ubiquitous instant communications, ubiquitous intelligence and Internet of Things (IoT). 6G should enable the full integration of wireless networks based on different technologies. A significant advantage of the 6G mobile network that will enable this is certainly the data rate, which will reach speeds of even 1TB/s. In addition, 6G mobile networks will enable extremely high coverage, negligible delay, high reliability and availability in almost all rural areas.</p>

UAV-Enabled Mobile-Edge Computing for AI Applications: Joint Model Decision, Resource Allocation, and Trajectory Optimization

Due to the flexible mobility and agility, unmanned aerial vehicles (UAVs) are expected to be deployed as aerial base stations (BSs) in future air-ground integrated wireless networks, providing temporary and controllable coverage and additional computation capabilities for ground Internet of Things (IoT) devices with or without infrastructure support. Meanwhile, with the breakthrough of artificial intelligence (AI), more and more AI applications relying on AI methods such as deep neural networks (DNNs) are expected to be applied in various fields such as smart homes, smart factories and smart cities to improve our lifestyles and efficiency dramatically. However, AI applications are generally computation-intensive, latency-sensitive, and energy-consuming, making resource-constrained IoT devices unable to benefit from AI anytime and anywhere. In this paper, we study mobile edge computing (MEC) for AI applications in air-ground integrated wireless networks. Our goal is to minimize the service latency while ensuring the learning accuracy requirements and energy consumption. To achieve that, we take DNN as the typical AI application and formulate an optimization problem that optimizes the DNN model decision, computation and communication resource allocation, and UAV trajectory control, subject to the energy consumption, latency, computation and communication resource constraints. Considering the formulated problem is non-convex, we decompose it into multiple convex subproblems and then alternately solve them till they converge to the desired solution. Simulation results show that the proposed algorithm significantly improves the system performance for AI applications.

Development of a Smart Agriculture Robot using IOT

Development of a Smart Agriculture Robot using IOT is presented in this final year project’s student’s paper. In this paper, we present the recent developments of the works. Climate changes and rainfall has been erratic over the past decade. Due to this in recent era, climate-smart methods called as smart agriculture is adopted by many Indian farmers. Smart agriculture is an automated and directed information technology implemented with the IOT (Internet of Things). IOT is developing rapidly and widely applied in all wireless environments. In this paper, sensor technology and wireless networks integration of IOT technology has been studied and reviewed based on the actual situation of agricultural system. A combined approach with internet and wireless communications, Remote Monitoring System (RMS) is proposed. Major objective is to collect real time data of agriculture production environment that provides easy access for agricultural facilities such as alerts through Short Massaging Service (SMS) and advices on weather pattern, crops etc.

Infectious Probability Analysis on COVID-19 Spreading With Wireless Edge Networks

The emergence of infectious disease COVID-19 has challenged and changed the world in an unprecedented manner. The integration of wireless networks with edge computing (namely wireless edge networks) brings opportunities to address this crisis. In this paper, we aim to investigate the prediction of the infectious probability and propose precautionary measures against COVID-19 with the assistance of wireless edge networks. Due to the availability of the recorded detention time and the density of individuals within a wireless edge network, we propose a stochastic geometry-based method to analyze the infectious probability of individuals. The proposed method can well keep the privacy of individuals in the system since it does not require to know the location or trajectory of each individual. Moreover, we also consider three types of mobility models and the static model of individuals. Numerical results show that analytical results well match with simulation results, thereby validating the accuracy of the proposed model. Moreover, numerical results also offer many insightful implications. Thereafter, we also offer a number of countermeasures against the spread of COVID-19 based on wireless edge networks. This study lays the foundation toward predicting the infectious risk in realistic environment and points out directions in mitigating the spread of infectious diseases with the aid of wireless edge networks.

Study on Integration and Application of Artificial Intelligence and Wireless Network in Piano Music Teaching.

Until 2019, most people had never faced the situation that would be their life-changing moment. Most universities are conducting classes for their students with the help of virtual classrooms indicating massive technological growth. However, this development does not take enough time to reach the students and the teaching person. Within five to six months of successful projects, most application producers have launched their official sites to conduct online classes and test ways for students. The introduction of virtual classes is not the only example of technological advancement; cloud computing, artificial intelligence, and deep learning have collaborated to produce appropriate, fine, and less error-prone results in all such fields of teaching. These technological advancements have given way to design models created with the wireless networks that are being made, particularly for music-related courses. The Quality-Learning (Q-Learning) Algorithm (QLA) is a pillar study for improving the implementation of artificial intelligence in music teaching in this research. The proposed algorithm aids in improving the accuracy of music, its frequency, and its wavelength when it passes. The proposed QLA is compared with the existing K-Nearest Neighbour (KNN) algorithm, and the results show that QLA has achieved 99.23% accuracy in intelligent piano music teaching through wireless network mode.

AFSOS: An Auction Framework and Stackelberg Game Oriented Optimal Network’s Resource Selection Technique in Cognitive Radio Networks

The upcoming 5G and beyond wireless networking technologies are intended to coexist with different communication networks to solve the spectrum scarcity problem. The seamless roaming across integrated wireless networks and an optimal network’s resource allocation would be a doable challenge for designing futuristic networks. The cognitive radio (CR) networks, with the inclusion of game theory, can handle spectrum scarcity issues by permitting spectrum access to the secondary user (SU) in the absence of a primary user (PU). This work proposes an AFSOS (an Auction Framework and Stackelberg game oriented Optimal network’s resource Selection) technique to achieve a maximum payoff and acceptable interference power restraint in CR networks. The contest among candidate networks can be modeled as a Stackelberg game, and the contest between CR nodes and candidate networks can be modeled as an auction framework. As a schema for the realization and capabilities evaluations, the CR networks consisting of LTE cellular network interworking with Wi-Fi network for multiple access points (APs)/single vehicle (low traffic environment) is analyzed. This framework is further analyzed for single AP/multiple CR nodes (high traffic environment). The equilibrium for the Stackelberg game is achieved, and the proposed AFSOS technique is analyzed with numerical examples. The results show that the proposed AFSOS technique is more operative to obtain maximum payoff.

Techno-Economic Analysis of 5G Non-Public Network Architectures

The adoption of private 5G networks or Non-Public Networks (NPN) by industry verticals is igniting a digital transformation across various sectors and also leading to industry 4.0. This impetus comes from the integration of private wireless networks with 5G capabilities. Currently, a range of innovative applications and use cases are emerging and resulting in improved enterprise performance and solutions. The potential to boost revenue, stimulate cost reduction, and accelerate Return Of Investment (ROI) makes 5G NPN adoption attractive to industry verticals, network operators and other third-party stakeholders. However, a significant infrastructure upgrade is required, which demands understanding of the complexities of 5G NPN deployment scenarios and their economic implications. This paper addresses these needs by conducting a detailed techno-economic analysis on 5G NPN deployment. The study formulates a techno-economic model that focuses on; (i) Cost savings in support of ROI achieved by enabling Network Function Virtualization (NFV) technology and Neutral Host (NH) concept; (ii) The trade-off study between enterprise goals (cost vs deployment technologies) with a multi-objective sensitive analysis; And (iii) the trends of 5G NPN adoption worldwide. Analytical results confirm savings of up to 53% in Total Cost of Ownership (TCO) reflecting a significant reduction in Capital and Operation Expenditures (Capex and Opex). Simulation analysis identifies a ranking order of deployment parameters, which prioritise the use of Cost saving strategies and Deployment type. And finally, it offers a prediction of a starting annual average worldwide adoption rate of 82.2% with an expected height by 2026.

Information Fusion Method of Power Internet of Things Based on Low-Voltage Power Line and Micro-Power Wireless Communication

In order to improve the coverage and reliability of the information perception layer of the power Internet of things, a method of constructing a cross layer fusion network of low-voltage power line and micro-power wireless communication (CPW) is proposed. Firstly, a unified medium access control (MAC) layer model of CPW is established to provide basic support for realizing the integration of CPW network layers; then an improved ant colony algorithm combining Brownian motion and local convergence times control is proposed to complete the networking process of CPW; Distribute the sub-service flow of CPW, and propose the bit error rate requirement factor in the service distribution, and accomplish the cross-layer integration of low-voltage power line and micro-power wireless communication network. The simulation results show that the communication link service quality of the cross-layer fusion network is better than that of the power line and wireless dual-mode or cascaded communication networks. The communication efficiency of CPW is improved to 398.20kbits/s. The coverage of the power line and wireless communication fusion network can be expanded by setting corresponding bit error rate demand factors according to different services. It takes into account the balance of communication link quality and network load.

An MIH-enhanced fully distributed mobility management (MF-DMM) solution for real and non-real time CVBR traffic classes in mobile internet

The integration of wireless access networks has progressed rapidly in recent years. Within the mobile communication environment, the operator provides multiple interface options for the mobile node (MN) to switch its connection to any access network during mobility to achieve the quality of service (QoS) for various traffic classes. The conventional centralised mobility management (CMM) scheme lacks reliability, dynamic anchoring and a single point of failure. This stimulates the distributed mobility management (DMM) scheme to handle mobility at the access network rather in a centralised manner. Therefore, in this paper, an IEEE 802.21 media independent handover (MIH) enhanced fully DMM (MF-DMM) solution is proposed for real- and non-real-time constant and variable bit rate (CVBR) traffic classes for mobile internetworking applications. The performance factors of handover delay, packet loss rate, throughput and signalling overheads are compared with the existing CMM scheme. The simulation results prove that the presented MF-DMM technique considerably reduces the handover delay while switching to different access technologies and, thus, achieves seamless connection by managing mobile internet protocol (IP) traffic locally.

Computer wireless network integration technology in equipment state data collection

The paper introduces a handheld integrated power data acquisition and analysis equipment based on a computer wireless network mobile platform, an intelligent transportation inspection box. The intelligent transportation inspection box acts as a bridge between the transportation inspection work site side and the power grid company center to realize data and resource sharing between the site and center sides. The application of intelligent operation and inspection boxes based on computer wireless network integration technology is essential for improving the professional and intelligent level of on-site operation and maintenance, improving the efficiency of operation and inspection work and the ability to control equipment status, strengthening state maintenance and auxiliary decision-making, and promoting the construction of smart grids significance.

Blockchain-Based Decentralized Lightweight Control Access Scheme for Smart Grids

The integration of wireless networks and Internet of things (IoT)-enabled communication between smart grid entities to address the challenges in supply chain including mutual authentication and privacy persistence, and control access scheme is critical in smart grids. In the last decade, numerous control access schemes have been presented. However, existing schemes are not reliable in terms of security and privacy and they involve third parties and central management system that leads the smart grid toward untrustworthiness and single-point failure. In addition, smart meters are managed through a central entity called service provider, and due to centralization, it involves single-point failure. Moreover, IoT-based smart meters are vulnerable due to untrusted environment; thus, it requires to establish trusted control access between entities of network to exchange messages. To overcome these issues, this paper proposes a decentralized trusted control access scheme by leveraging blockchain technology to ensure trusted communication between entities of smart grid by protecting data transmission requests which are sent/received by smart meter to network. In conclusion, an analysis in the context of security and performance is presented. The analysis depicts that the proposed scheme is effective in terms of computational and storage cost.

Smart grid wireless communications: a cyber-physical system perspective

It is widely accepted that wireless communications play an important role in smart grid. However, wireless communication usually lacks sufficient quality, security, and reliability that are critically demanded by power grid. Thus, it is indispensable to study the applicability of wireless communications for smart grid. In this paper, interactions between a wireless communication network and smart grid are characterised from the perspective of a cyber-physical system (CPS). Based on this CPS framework, integration of smart grid and wireless networks is categorised into two scenarios: loosely-coupled CPS and tightly-coupled CPS. The features of both scenarios are discussed and compared, which leads to clear guidelines on the design of a smart grid wireless communication system. To concretely demonstrate these guidelines, two examples are presented to show different roles of wireless communications in loosely-coupled CPS and tightly-coupled CPS. Following these examples, remaining research challenges and potential solutions are discussed.

Study of blockchain-based 6G wireless network integration and consensus mechanism

The sixth-generation (6G) system is a future standard of wireless networks and will be expected to deploy with the full support of blockchain. Blockchain technology is a Distributed Ledger Technology (DLT) to store and refer to the data. In this paper, firstly, we discuss the consensus protocol in 6G and then study the applications of blockchain in 6G. As a result, it has been observed that 27.5% of texts rely on PoW, 22.5% of texts are related to PoS, 17.5% of texts are based on DPOS and PBFT consensus protocol. Blockchain technologies in the state-of-the-art results with 6G, offer various applications such as spectrum management, trusted database, service level agreement, fair access through a smart contract. However, this integration suffers resource utilisation problems, computational loads, delays and bandwidth overhead, leading to a new set of issues that can be solved with the integration of blockchain, IoT and AI with 6G.

Study of blockchain-based 6G wireless network integration and consensus mechanism

Study of blockchain-based 6G wireless network integration and consensus mechanism