Wireless Network Applications Research Articles

Task offloading strategy with emergency handling and blockchain security in SDN-empowered and fog-assisted healthcare IoT

With the rapid advancement of the Internet of Things (IoT), the typical application of wireless body area networks (WBANs) based smart healthcare has drawn wide attention from all sectors of society. To alleviate the pressing challenges, such as resource limitations, low-latency service provision, mass data processing, rigid security demands, and the lack of a central entity, the advanced solutions of fog computing, software-defined networking (SDN) and blockchain are leveraged in this work. On the basis of these solutions, a task offloading strategy with a centralized low-latency, secure and reliable decision-making algorithm having powerful emergency handling capacity (LSRDM-EH) is designed to facilitate the resource-constrained edge devices for task offloading. Additionally, to well ensure the security of the entire network, a comprehensive blockchain-based two-layer and multidimensional security strategy is proposed. Furthermore, to tackle the inherent time-inefficiency problem of blockchain, we propose a blockchain sharding scheme to reduce system time latency. Extensive simulation has been conducted to validate the performance of the proposed measures, and numerical results verify the superiority of our methods with lower time-latency, higher reliability and security.

Enabling mmWave Wireless Rack Area Networks: Channel Characterization Within a Server Rack

This letter presents 60 GHz radio measurements and channel characterization for wireless rack area network (WRAN) application within a networking enclosure, commonly known as a server rack. The propagation characterization is conducted with wideband and narrowband measurements to characterize the propagation phenomena and investigate the feasibility of a reflected non-line-of-sight (RNLoS) link. The impact of obstruction by networking cables and a human hand is also investigated to extract the fading depth, fading rate, and the time varying shadowing. The implications on WRAN system design are accordingly deduced. It is found that optimal RNLoS channel response is characterized by a clustering effect with a 7.82 dB reflection loss. The obstruction by networking cables introduces significant channel dispersion and contributes to significant fading depth and fading rate values.

Frequency reconfigurable circular microstrip patch antenna with slots for cognitive radio

In this paper, a novel multi-frequency microstrip antenna with complementary ring slot resonator (CRSR) structure that satisfies Bluetooth, worldwide interoperability for microwave access (WiMAX), and wireless local area network (WLAN) applications is proposed. The conventional antenna consists of a circular microstrip patch at a resonance frequency band of 2.5 GHz. By loading two CRSR at the radiating element, three operating frequency bands 2.5 GHz, 3.6 GHz, and 5.2 GHz are achieved. The operational bands covered by the antenna are Bluetooth 2.5 GHz, WiMAX 3.6 GHz, and WLAN 5.2 GHz. The insertion of CRSR to patch antenna has made it possible to compact and simple design, and miniaturized antenna for cognitive radio. Moreover, the directivity of the proposed antenna is adequate with acceptable radiation properties and perfectly matches with the simulated and measured results.

Cognitive Heterogeneous Wireless Network and Artificial Intelligence-Based Supply Chain Efficiency Optimization Application.

Cognitive radio can specifically perceive the surrounding environment, can understand and learn the changes in the surrounding environment, and can adjust its own adaptation method, channel calculation, and other transmission parameters at any time. This cognitive radio method is more flexible and is an intelligent wireless communication system, a relatively advanced system. Cognitive communication devices can detect changes in the surrounding wireless environment and relatively change their own parameters to cope with the changes in the environment and ensure the stability of communication quality. As a different part of the supply chain, enterprises use the sharing economy and cooperation to improve the overall competitiveness of the enterprises in the supply chain, ultimately achieve a win-win effect for all enterprises in the supply chain, and complete the improvement of the company's competitiveness. The supply chain model can help companies to be familiar with the structure, operation process, and orientation of the supply chain in which they are located, so that they can clearly understand the work process through simulation scenarios and better understand the problems of the supply chain work process. Supply chain supply with cognitive heterogeneous wireless networks and artificial intelligence is a necessary way to deeply improve the operation and working process of supply chain control. In short, the cognitive radio system proposed in this study can receive network-related messages by observing the surrounding wireless network environment, and can receive internal communication tasks and emergency communication tasks based on historical data and prediction of future relationships. Through the access control process, we make an appropriate strategy and finally complete the communication function of the system.

Retraction Note to: Trust and privacy based vertical handoff decision algorithm for telecardiology application in heterogeneous wireless networks

Retraction Note to: Trust and privacy based vertical handoff decision algorithm for telecardiology application in heterogeneous wireless networks

Knowledge-defined networking: Applications, challenges and future work

Future 6G wireless communication systems are expected to feature intelligence and automation. Knowledge-defined networking (KDN) is an evolutionary step toward autonomous and self-driving networks. The building blocks of the KDN paradigm in achieving self-driving networks are software-defined networking (SDN), packet-level network telemetry, and machine learning (ML). The KDN paradigm intends to integrate intelligence to manage and control networks automatically. In this study, we first introduce the disadvantages of current network technologies. Then, the KDN and associated technologies are explored with three possible KDN architectures for heterogeneous wireless networks. Furthermore, a thorough investigation of recent survey studies on different wireless network applications was conducted. The aim is to identify and review suitable ML-based studies for KDN-based wireless cellular networks. These applications are categorized as resource management, network management, mobility management, and localization. Resource management applications can be further classified as spectrum allocation, power management, quality-of-service (QoS), base station (BS) switching, cache, and backhaul management. Within network management configurations, routing strategies, clustering, user/BS association, traffic classification, and data aggregation were investigated. Applications in mobility management include user mobility prediction and handover management. To improve the accuracy of positioning in indoor environments, localization techniques were discussed. We classify existing research into the respective KDN architecture and identify how the knowledge obtained will enhance future networks; as a result, researchers can extend their work to empower intelligence and self-organization in the network using the KDN paradigm. Finally, the requirements, motivations, applications, challenges, and open issues are presented.

Future outlook on 6G technology for renewable energy sources (RES)

As the renewable energy sources (RES) continues to grow in power system due to emissions decarbonisation and sustainability policies, a fast and reliable connection between RES components and equipment is crucial to ensure quality power delivery. This review provides a detailed insight into the full potential in 6G for the acceleration of RES with the faster and stable data bandwidth. The potential applications of 6G wireless networks for faster data processing in RES include P2P energy trade market, vehicular network, wireless energy transfer, energy management system, smart grid, self-healing, smart batteries and AI-based weather forecasting. This paper also lists the advantages and challenges of 6G in RES sectors, the practical implementations and the potential applications. It was found out that although the 6G is a visionary application in the RES sector to improve the security, connectivity, integration and sensory data processing of RES, 6G still possesses various technical limitations, including incompatibility issues of older devices, higher power consumption and higher operating cost. Future research should focus on the improvements of 6G in RES in terms of cost-effectiveness, compatibility issues and power consumption to balance between the advancement and limitations. This review serves as a visionary for 6G wireless communication to be applied in the RES sector in the near future. 6G in the RES sector encountered several critical limitations needing an intensive development, including still the issues of security and privacy, prone to hacking or data bleaching, required advanced hardware support and requirements for ultra-fast communications with low latency.

A compact four-band high-isolation quad-port MIMO antenna for 5G and WLAN applications

A miniaturized quad-port multiple-input-multiple-output (MIMO) antenna, generating four-band and high port isolation properties, is developed for 5G and wireless local area network (WLAN) applications. The realized MIMO antenna consists of four elements. Each element combines multiple L-shaped and rectangular branches with concave grounds, so that good impedance matching in four frequency bands is reached. The four elements are orthogonally placed to reduce current coupling. Moreover, four pairs of rotationally symmetrical strip lines are added to further improve the isolation between the units at low frequency. The antenna has been optimized to achieve a compact size of 39 mm × 39 mm × 1.6 mm, covering three 5G bands (2.6/3.5/4.8 GHz) and the 5.8 GHz WLAN band. In addition, inter-port isolation is better than 21.5 dB. Furthermore, the measured envelop correlation coefficient is smaller than 0.012 in the desired bands. Measurements also show that the radiation patterns and gains of the fabricated antenna agree well with the simulated ones. The diversity gain is as good as 9.94 dB. Moreover, the channel capacity loss is satisfactory, being below 0.4 bits/s/Hz. Satisfactory efficiency and diversity performance are realized. These facts indicate that the antenna system is a promising candidate for MIMO usage on 5G and WLAN devices.

Research on Internal Parameter Filtering of Natural Gas Pipeline under Duty Cycle Transmission Mechanism

In recent years, with the continuous growth of China's long-distance oil and gas pipeline network, wireless communication network applications have become more and more extensive with the continuous promotion of intelligent oilfield construction, while the energy-saving problem in the process of information transmission has become increasingly prominent. In order to ensure the sustainable development of China's oil and gas industry, low-power wireless transmission has become a basic requirement for the current intelligent oil and gas pipeline communication construction. For the monitoring of pipeline operating conditions, pressure and flow rate values are important parameters. If the accuracy and comprehensiveness of pipeline operation data can be ensured simultaneously under an energy-efficient transmission mechanism, it will provide strong support for the green and safe operation of pipelines. Therefore, in this paper, a recursive filtering study is conducted for natural gas gathering pipeline flow system under duty cycle transmission mechanism to complete the reliable monitoring of pipeline fluid transportation status.

Affirmative data analytics based data processing method for 6G wireless network applications

AbstractSixth generation (6G) wireless network infrastructure makes use of terahertz communication interfaces and latency service. The growth of real‐time applications and service support increases the data handling capacity and processing requirements. The data processing rate must be comparatively high with the available resources to meet the users' quality of service (QoS) requirements. This article proposes an affirmative data analytics (ADA) method to improve data processing consistency in 6G wireless networks. The consistency of the ADA method relies on the 6G service features in the service‐rendering environment. The affirmation process is provided using support vector machine (SVM) learning to achieve consistency in handling diverse‐attributed data. Then the attribute and association between data and services are achieved with best‐fit processing time and minimum complexity. The performance of the proposed ADA is verified for heterogeneous service applications in a wireless network using the metrics analysis time (723.629 ms), complexity (11.311%), and response time (1.034 s).

A New Compact Dual-Polarized MIMO Antenna Using Slot and Parasitic Element Decoupling for 5G and WLAN Applications

This paper presents a compact dual-polarized multiple-input multiple-output (MIMO) antenna for fifth generation (5G) and wireless local area network (WLAN) applications. At first, a compact two-element dual-polarized MIMO antenna designed to operate at 3.5 GHz was developed. After that, some modifications were performed in the initial configuration, and a compact two-element dual-polarized MIMO was designed to operate at 3.5 and 5.35 GHz. A simple decoupling technique using parasitic element and slot was used to enhance the isolation between the radiating elements and to achieve an isolation above 18 dB over the band ranging from 3.4 to 3.6 GHz for the first antenna, and to achieve isolations above 19.8 dB over the first band ranging from 3.4 to 3.6 GHz and above 16.75 dB over the second band ranging from 5.15 to 5.85 GHz for the second antenna. Simulations were performed in the Ansoft HFSS software for numerical characterization and the prototype was fabricated with FR-4 dielectric and measured, presenting a good agreement between simulated and measured results. Furthermore, the envelope correlation coefficient (ECC) and the diversity gain (DG) were analyzed and present good results.

Application of Wireless Network Based on Artificial Intelligence in Network Teaching of Preschool Education Manual and Aesthetic Education Practical Course

For preschool education majors, art and crafts are required courses. This course is a hands-on exercise that helps students develop their creative awareness, design thinking, and hands-on skills. At the same time, it provides learners with the teaching thinking mode of art and handicraft theme and the form of online teaching helps learners to construct the thinking mode of online learning. As a new teaching form, online teaching is gradually leading the reform in the field of education. However, the majority of present online teaching is simply a continuation of traditional teaching thought, relying on substantial teaching research rather than utilizing its particular advantages to develop and expand. Also, the connotation depth of traditional teaching may not involve the essential problem of teaching application itself—teaching methods and experience of acquiring knowledge. As a result, determining how to characterize an individual’s ability to acquire knowledge and successfully assessing the level of growth of an individual’s cognitive structure is critical to the development of a new generation of online education. In order to prepare for the next generation of network teaching, this article uses artificial intelligence and wireless networks to teach preschool education manual and aesthetic education practical courses through the Internet. From the perspectives of individuals and groups, two teaching case recommendation experiments are given. The experiment’s end result confirms the practicality and logic of the evaluation model described in this research, which is based on individual cognitive structure.

The Application of Artificial Intelligence Wireless Network in Music Contextual Teaching under the New Media Art Perspective

Technological growth has resulted in simplifying various tasks previously considered tedious jobs by humans. Artificial intelligence technology has increased and is being appointed to reduce the burden of handling charges by assisting humans in their tasks. The artificial intelligence technology integrated with the wireless network systems is designed to teach music with the help of new media art. New media art is referred to as artwork that deploys new media technologies for its production. Some of the new media technologies are as follows: animation, computer graphics, digital art, video games, sound art, and interactive art. New media art is different from the traditional visual arts, such as paintings, sculptures, and architecture. The new media art is gaining popularity and has become an unavoidable technology. In this article, people will research the application of artificial intelligence and wireless networks in the music context of teaching under the vision of new media art. The integration of AI and wireless network technology with new media art in the music teaching field is more advantageous than the traditional methods of music teaching. The integration model Convolutional Neural Network Art Algorithm (CNNAA) is a CNN algorithm to train and test the music teaching in the context of new media art such as technological involvement such as 4G and 5G for faster data transfer in the wireless communication. The proposed model is compared with the existing fuzzy logic, neural network (NN), and K-Nearest Neighbour (KNN) for the training and testing of the model for an accurate teaching process. The results show that the CNNAA has obtained a higher accuracy of 98% and 99% for training and testing.

Characteristic mode analysis of two port semi‐circular arc‐shaped multiple‐input‐multiple‐output antenna with high isolation for 5G sub‐6 GHz and wireless local area network applications

SummaryThe work presents the design of a novel semi‐circular arc‐shaped two‐element multiple‐input‐multiple‐output (MIMO) antenna with improved isolation. The antenna is obtained by cutting and subtracting a circular disk from another circular disk, forming the shape of a semi‐circular arc. The antenna is replicated to form a two element MIMO antenna system on a FR4 substrate of size 36 × 26 mm2 with edge‐to‐edge separation of 12.4 mm. The developed MIMO antenna resonates in the frequency range 3.26 to 6.97 GHz giving a maximum element‐to‐element isolation around 26 dB in the operating bandwidth. Also, the antenna gives a maximum radiation efficiency of 98% with a peak gain of 5.3 dBi in the operating band. The proposed compact MMO antenna covers wide variety of wireless applications like 5G sub‐6 GHz and wireless local area network (WLAN) applications, which includes n77/n78/n79, WiFi‐5, V2X/DSRC, WiFi‐6, and INSAT‐C bands. Characteristic mode analysis (CMA) is performed in characterizing the performance of the antenna over the specified operating bands by studying and analyzing the parameters like modal significance (MS), characteristic angle (CA), modal current, and modal patterns. The obtained MIMO parameters like envelope correlation coefficient (ECC), diversity gain (DG), mean effective gain (MEG), and total active reflection coefficient (TARC) reveal that the proposed antenna is a suitable choice in MIMO environment.

A multimode substrate integrated waveguide based s elf‐hexplexing antenna for mobile terminal applications

A low-profile self-hexplexing antenna based on the multimode substrate integrated waveguide (SIW) cavity is presented for mobile terminal applications. It has three feeding ports, each of which can generate two resonant modes. Taking the advantage of the truncated SIW resonant cavity, the footprint of the antenna remains compact in the multiple functional mode scenario. The proposed antenna operates at six different modes, namely TM10 mode at 3.55 GHz, TM01 mode at 4.85 GHz, TE110 mode at 2.45 GHz, TE220 mode at 5.6 GHz, TE110 mode at 3.4 GHz and TE120 mode at 5.35 GHz. Good agreement is achieved between the simulated and measured antenna performance. The excitation and field distribution of each mode is analyzed. Keeping the structure miniaturized, the proposed antenna realizes hex-band characteristics without excessive feeding ports. It can be used for Microwave Access (WIMAX), the 5th Generation Mobile Communication Technology (5G) and Wireless Local Area Network (WLAN) applications, which is suitable for mobile handheld multiband terminals.

Knowledge Diffusion of the Internet of Things (IoT): A Main Path Analysis.

The Internet of Things (IoT) is a concept that has attracted significant attention since the emergence of wireless technology. The knowledge diffusion of IoT takes place when an individual disseminates his knowledge of IoT to the persons to whom he is directly connected, and knowledge creation arises when the persons receive new knowledge of IoT, which is combined with their existing knowledge. In the current literature, several efforts have been devoted to summarising previous studies on IoT. However, the rapid development of IoT research necessitates examining the knowledge diffusion routes in the IoT domain by applying the main path analysis (MPA). It is crucial to update prior IoT studies and revisit the knowledge evolution and future research directions in this domain. Therefore, this paper adopts the keyword co-occurrence network and MPA to identify the research hotspots and study the historical development of the IoT domain based on 27,425 papers collected from the Web of Science from 1970 to 2020. The results show that IoT research is focused on IoT applications for smart cities, wireless networks, blockchain technology, computing technologies, and AI technologies. The findings from the MPA address the need to explore the knowledge evolution in the IoT domain. They also provide a valuable guide to disseminate the knowledge of IoT among researchers and practitioners, assisting them to understand the history, present and future trends of IoT development and implementation.

A Design for the Bandwidth Improvement for the Microstrip Patch Antenna for Wireless Network Sensor

The microstrip patch antenna is extensively used in the wireless network because the Microstrip patch Antenna can be easily manufactured. Bandwidth Improvement of the Microstrip patch antenna is shown in this paper. The Antenna is made at the 8.5GHz frequency. The material used for the substrate is FR4-epoxy. For this material, the dielectric loss tangent is 0.0018. This antenna observes the Bandwidth to 660MHz, gain 5.4028, Directivity 5.5068, return loss -37.0048, and VSWR 1.0629. In this design there is an Improvement of bandwidth to 660 MHz which is suitable for wireless network applications and the software which is being used for the simulation is the High-Frequency Structure Simulator which is also known as HFSS.

The Application of Wireless Network-Based Artificial Intelligence Robots in Badminton Teaching and Training.

Artificial intelligence technology has already set its foot in various industries, including sports, to train athletes. In this research article, people will study the application of wireless networks based on artificial intelligence robots in badminton teaching and training. People propose a system that deploys intelligent robots to teach badminton to athletes. The robots will train the players with various moves and techniques required for the game. The wireless networking system allows the robot to connect to the network. Various sets of plays and players' movements were preprogrammed for the robot. The trainer has to select essential factors such as training mode and set height required for a particular player in the robot—these are the complexities in badminton training. Moreover, in the case of effective and efficient training, people need a robot that will aid in different training modes. The changing variables, such as speed, frequency, angle, height, and change in coordinates, are utilised in the training and teaching of robots, which are more efficient than the traditional training methods given by people. The decision tree algorithm (DTA) is used in this research and is compared with the existing sports motion segmentation method (SMSM). From the results, it is observed that the proposed DTA has given improved accuracy of 93% compared with the SMSM.

Adaptive Routing Design for Flying Ad Hoc Networks

Adaptive routing and efficient packet delivery in Flying Ad Hoc Networks (FANETs) are significant challenges due to underlying environment constraints, such as dynamic nature, mobility, and limited connectivity. With the increasing number of machine learning (ML) applications in wireless networks, FANETs can benefit from these data-driven predictions. This letter proposes a Packet Arrival Prediction (PAP) routing protocol to improve transmission link reliability. Primarily, we apply a Long Short-Term Memory (LSTM) model to predict the packet arrival of each UAV, seeking to avoid the high-traffic UAVs, which cause packet loss significantly. Then, we formulate the routing decision issue as an optimization problem, which attempts to find an appropriate path by a proposed constrained sorting approach, in order to make joint yet fast routing decisions. The simulation results demonstrate that the PAP routing protocol outperforms the existing manifold protocols in the aspects of Packet Delivery Ratio (PDR) and delay.

Application of Wireless Mesh Network in Interface Tracking Between Two Immiscible Fluids

The characteristics of the interaction between immiscible fluids are prominent because of their intriguing conduct in many situations in the environment and industry, such as lubrication process, oil extraction, physicochemical process, and polymers co-extrusion. We examine the time-dependent flow of two immiscible liquids via a horizontal channel in this paper. Due to external pressure, time, and other physical circumstances, the fluidfluid interface alters its location. It may collapse, even though it is non-slip and hyper-stick at the channel’s wall. Hence the single momentum equation by the volume of fluid (VOF) method is combined with Wireless Mesh Network’s to track the interface. The modeled coupled partial differential equation is analytically solved for fluid interface evolution, and using the proposed Algorithm, the coverage and uniformity between the node are calculated. Based on the calculations, the optimal node is selected to track the interface, resulting in discovering the lost information with the least distance. The advection and tracking of the interface with time through graphs. It is observed that the undulating sequence occurs faster for a considerable high time, and the proposed algorithms track the interface with optimal node selection.