Successful Data Transmission Research Articles

Secure and efficient trust enabled routing in mobile ad hoc network using game theory and grey wolf optimisation techniques

AbstractMobile Ad hoc Networks (MANETs) are crucial wireless networks for military, corporate, and emergency use, yet they are vulnerable to disruptions from malicious nodes. The presence of malicious nodes can lead to message transmission and routing disorganisation, and network performance is effectively compromised. Game theory‐based fuzzy secure clustering (GTFSC) improves performance metrics in low‐scale and high‐scale networks. This protocol's novel ability to dynamically scale performance measures as nodes expand improves efficiency and adaptability. While improving performance metrics, the proposed algorithm also efficiently identifies malicious nodes and re‐routes the transmission, excluding the found malicious nodes. For any MANET system, secure and successful data transmission is paramount. The proposed protocol integrates various algorithms to fulfil its aim of customised EGT, GWO, and fuzzy clustering. Black hole attacks, grey hole attacks, Sybil attacks, and data tampering attacks are all considered to provide comprehensive attacks on MANET. Every node is assigned trust values, which get updated on data transmission. Fuzzy Clustering is employed to identify malicious nodes. Evolutionary Game Theory (EGT) optimises network organisation by designating cluster heads and clusters as nodes. Additionally, the proposed protocol leverages the Grey Wolf Optimisation Routing Algorithm (GWO), which establishes efficient routes from the source to the sink node. The analysis result shows maximum performance with a packet delivery ratio of around 98%, throughput of 90% end‐to‐end delay reduced by 15%, and energy consumption reduced by 18%, respectively, compared to an existing protocol.

Safety and Feasibility of an Implanted Inferior Vena Cava Sensor for Accurate Volume Assessment: FUTURE-HF2 Trial.

A novel implantable sensor has been designed to accurately measure inferior vena cava (IVC) area to allow daily monitoring of IVC area and collapse to predict congestion in heart failure (HF). A prospective, multicenter, single arm, Early Feasibility Study enrolled 15 HF patients (irrespective of ejection fraction) with a HF event in the previous 12 months, an elevated NT-proBNP, and receiving ≥40 mg of furosemide equivalent. Primary endpoints included successful deployment without procedure-related (30 days) or sensor-related complications (three months) and successful data transmission to a secure database (3 months). Accuracy of sensor-derived IVC area, patient adherence, NYHA classification, and KCCQ were assessed from baseline to three months. Patient-specific signal alterations were correlated with clinical presentation to guide interventions. Fifteen patients underwent implantation (66±12 years; 47% female; 27% HFpEF, NT-ProBNP 2569 (median, IQR: (1674-5187)) ng/L; 87% NYHA Class III). All patients met the primary safety and effectiveness endpoints. Sensor-derived IVC area showed excellent agreement with concurrent CT (R2=0.99, mean absolute error=11.15 mm2). Median adherence to daily readings was 98% (IQR: 86-100%) per patient-month. A significant improvement was seen in NYHA class and a non-significant improvement was observed for KCCQ. Implantation of a novel IVC sensor (FIRE1) was feasible, uncomplicated, and safe. Sensor outputs aligned with clinical presentation and improvements in clinical outcomes. Future investigation to establish the IVC sensor remote management of HF is strongly warranted.

Thermoelectric energy harvesting associated with heat pipes for monitoring highways weather conditions

This work aims to develop a prototype for autonomously monitoring highway weather conditions using thermoelectric energy. The prototype utilizes solar thermal energy, heat absorbed by the asphalt and soil heat to generate, convert, manage, and store energy. The study investigates the optimal functioning of the thermoelectric generator, including utilizing the soil as a heat sink and incorporating passive thermal control devices like heat pipes. A commercial ultra-low power converter model LTC3108 was experimentally tested for efficient energy conversion. The monitoring system is designed to acquire readings from sensors measuring relevant climate parameters such as temperature, atmospheric pressure, and humidity, focusing on ultra-low power characteristics. The acquired data is transmitted via LoRa technology to a server for processing and analysis. The prototype generated 286.24 J of energy with a maximum temperature gradient of 4.25 ºC in the thermoelectric generator. The energy cost of transmitting a 40-byte message through the LoRaWAN module was 0.625 J. The proposed climate data acquisition circuit had a theoretical consumption of 17.69 J. Experimental tests with the LTC3108 converter, and a 0.22 F supercapacitor demonstrated successful data transmission. This work provides a solid foundation for future studies utilizing thermoelectric energy in highway applications, resulting in a prototype suitable for real-world road scenarios.

A dynamic analysis of UAV -based IoT networks for efficient communication using falcon optimization approach

Unmanned Aerial Vehicles (UAVs) play a pivotal role in Internet of Things (IoT) applications by sensing data, conducting continuous surveillance, and maintaining connectivity among users. However, their high mobility and continuous surveillance for data transmission result in high energy consumption, possibly resulting in lesser network performance, including link failure, node depletion, data loss, and high delays. To address these challenges, a novel scheme termed as 'On-Demand Cross-Layered Falcon Optimization Approach (OCLFO)' has been proposed to enhance connectivity and optimize network performance in UAV-based IoT systems. The on- demand Cross-Layer Optimization (CLO) scheme facilitates data transmission across each layer of the OSI model. CLO is applied to the design of UAVs with the integration of on-demand, based on the queuing size. Falcon Optimization Approach (FOA) has been integrated with the CLO to overcome the energy consumption drawback, and provide successful data transmission between UAV users with the help of fitness value. The fitness value depends maximum on the energy and minimum on the queuing size, and this provides the energy efficient routing path for an efficient data transmission. The proposed OCLFO aims to optimize energy consumption while ensuring successful and expedited data transmission among UAV users. Simulations have been conducted using a network simulator to analyse Quality of Service (QoS) parameters, considering high mobility scenarios by varying energy levels such as 100 J and 200 J. Compared to the existing optimization algorithms, the proposed OCLFO achieves high delivery ratio, high throughput, less delay, lesser energy consumption and enhanced link efficiency.

Directional Adaptive Triboelectric Nanogenerator with Wind-Wave Synergy.

To enhance the adaptability and synergy of the triboelectric nanogenerator (TENG) in a wave environment, this paper introduces a directional adaptive triboelectric nanogenerator (DA-TENG) with wind-water synergistic action for wave energy collection. An innovative design combining a wind vane on the top and fan-shaped blade electrodes internally allows the DA-TENG to adjust its swinging direction adaptively to align with the direction of wave motion. The internal multiple power generation units work in coordination, effectively addressing the issues of low efficiency associated with spherical TENGs in capturing multidirectional wave energy. The DA-TENG demonstrates superior performance under various wind speed conditions, showcasing its practical application potential. Experimental results show that the DA-TENG, equipped with a single tail wind vane and a 700 g mass block, can achieve an output voltage, current, and charge of 374.97 V, 84.77 μA, and 622.69 nC under a mild wind environment. Its peak power density reaches 7.51 W m-3, enabling successful data transmission for a wireless temperature and humidity sensor and powering 248 light-emitting diodes (LEDs). This research expands the possibilities of omnidirectional wave energy collection and the collaborative operation of multiple power generation units, offering an effective method for powering low-power maritime devices.

Design and Evaluation of a Hybrid 2D-SWZCC OCMDA System with Multicarrier MM-Wave

This paper presents a hybrid communication system combining optical code division multiple access (OCDMA) and multicarrier millimeter-wave (MM-Wave) architecture operating at 35, 55, 75, and 95 GHz connected to a home network center (HNC) and the end user (EU). Hybrid Link reduces congestion on complex RF networks by combining optical fiber backhaul with radio links. The OptiSystem simulation demonstrates successful data transmission and transmission capacity at 40Gbps over various distances. Furthermore, this new 40G-MM wave OCDMA system that takes advantage of a two-dimensional single-weighted zero cross-correlation (2D-SWZCC) system with a multiplexing scheme of polarization wavelength multiplies the same N channels to M OCDMA code of the MM-Wave system that dramatically increased scalability. The comparative analysis shows that the proposed 2D-SWZCC hybrid algorithm outperforms 1D-SWZCC regarding scalability. This study contributes to developing communication algorithms with high data rates and provides promising solutions for method limitations and scalability in hybrid-MM-Wave-OCDMA architectures.

Methodology for the design of a nanosatellite telecommunication system in S-Band based on Software for Digital Mission Engineering

Abstract A trend in the development of nanosatellite platforms for technology demonstration has increased in both private industry and academic projects. Communication link design plays a crucial role in the success of space missions, enabling efficient and reliable data transmission between satellites and ground stations. In this context, the use of advanced tools such as System Tool Kit (STK) has gained significant importance by enabling a comprehensive analysis of the technical and operational aspects of the communication link. In an effort to make the future design of the communications subsystem payload on a nanosatellite more efficient and accessible, this paper shows a methodology for the efficient use of STK to perform link analysis.

RON‐based cross‐chain routing optimization strategy in metaverse

AbstractMetaverse is a new ecology that integrates the digital world with the physical world, generates a mirror image of the real world based on digital twin technology, and guarantees the fairness of the virtual world through the trusted mechanism of blockchain. Cross‐chain communication technology is the key to realizing data circulation and collaborative processing between blockchains, which provides the communication foundation for the massive connection of blockchains in the metaverse. The current cross‐chain communication mode is dominated by direct‐connect routing, leading to network congestion and high propagation delay once the direct‐connect link fails and cannot be recovered quickly. To optimize direct‐connect routing, this paper proposed a cross‐chain routing optimization strategy based on RON (Resilient Overlay Network), that is, Cross‐Chain_RON, which firstly applies RON to reconstruct the direct‐connect routing model, and then selects the optimal link through the shortest‐path algorithm and policy routing, and combines with the RON performance database to improve the data transmission efficiency. Finally, the two communication modes were simulated by simulation tools. The experiments show that Cross‐Chain_RON outperforms the direct‐connect routing in terms of latency, rate of successful data transmission, and throughput in poor network environments, but at the expense of a certain amount of system overhead.

NEW HOME BLOOD PRESSURE TELEMONITORING SYSTEM IN AN AGED COMMUNITY: PROTOCOL OF THE DIGITAL CARDIOVASCULAR PREVENTION FEASIBILITY STUDY

Objective: We sought to (i) determine the precise feasibility of a new telemonitoring-based healthcare system in a community of aged individuals and (ii) clarify the clinical implications of blood pressure variabilities in a time series until the end of life for the management of hypertension in elderly patients. Design and method: We have devised a simple, easy-to-use blood-pressure monitoring system and automated telemonitoring system, i.e., the DICAP (DIgital Cardiovascular Prevention) system, that obtains all of the different blood pressure values measured in a time series in different settings in community-dwelling elderly individuals in their homes and other facilities. Results: The feasibility of the DICAP system was confirmed by the successful serial transmission of the home blood pressure data of the community-dwelling hypertensive patients including those who were not familiar with digital technology and those who resided at different community locations. Among the first-recruited 221 subjects, 92.3% have been monitoring their blood pressure with the DICAP >12 times/week. Conclusions: The newly developed DICAP system using a cellular blood-pressure monitoring device suggests the possibility of being feasible and acceptable for the management of hypertension among elderly community-living individuals.

Tradeoff Between Age of Information and Operation Time for UAV Sensing Over Multi-Cell Cellular Networks

Unmanned aerial vehicles (UAVs) have a significant potential for sensing applications in further cellular networks due to their extensive coverage and flexible deployment. In this paper, we consider a multi-cell cellular network with a cellular-connected UAV, which senses data with onboard sensors and uploads sensory data to the ground base stations (BSs). To evaluate the freshness of sensory data, we employ the concept of age of information (AoI), which is defined as the time elapsed since the latest successful transmission of sensory data. A lower AoI implies fresher sensory data, which may lead to the increase of UAV operation time. To balance such tradeoff, we aim to minimize the weighted sum of operation time and total AoI for the UAV by jointly optimizing transmission scheduling, BS association, as well as UAV trajectory. The problem is formulated as a mixed-integer nonlinear programming (MINLP) problem, which is difficult to solve due to the time-varying propagation channels. To this end, we first characterize the average communication performance with statistic channel information, and then develop a search algorithm to obtain the optimal solution via employing the optimal structure as well as convex optimization techniques, while a low-complexity Double Graph based Algorithm (DGA) is developed to obtain a suboptimal solution. Then, by taking into account the site-specific performance and making fast decisions online, we propose a Deep reinforcement Learning Algorithm (DLA). Compared to DGA, DLA can adapt to the specific local environment and obtain a solution more rapidly once the training process is completed. Simulation results show that the proposed algorithms outperform the benchmarks about 30%, and achieve flexible tradeoff between operation time and AoI of UAV sensing, which is not available by considering just one objective.

Against Jamming Attack in Wireless Communication Networks: A Reinforcement Learning Approach

When wireless communication networks encounter jamming attacks, they experience spectrum resource occupation and data communication failures. In order to address this issue, an anti-jamming algorithm based on distributed multi-agent reinforcement learning is proposed. Each terminal observes the spectrum state of the environment and takes it as an input. The algorithm then employs Q-learning, along with the primary and backup channel allocation rules, to finalize the selection of the communication channel. The proposed algorithm designs primary and backup channel allocation rules for sweep jamming and smart jamming strategies. It can predict the behavior of jammers while reducing decision conflicts among terminals. The simulation results demonstrate that, in comparison to existing methods, the proposed algorithm not only enhances data transmission success rates across multiple scenarios but also exhibits superior operational efficiency when confronted with jamming attacks. Overall, the anti-jamming performance of the proposed algorithm outperforms the comparison methods.

Distributed optimization game algorithm to improve energy efficiency for multi-radio multi-channel wireless sensor network

To send and receive data simultaneously, reduce network interference, and effectively improve energy efficiency, this paper analyzes the network characteristics of Multi-Radio Multi-Channel Wireless Sensor Network and optimizes the power and channel of each radio frequency interface. Based on the novel energy efficiency model and energy consumption efficiency model, this paper establishes a distributed optimization game model using Game Theory to maximize network energy efficiency, minimize energy consumption, and ensure network connectivity. Based on the game model, an efficient distributed resource allocation game algorithm is designed, in which a joint power control and channel allocation can quickly converge to Nash Equilibrium with low complexity. At the same time, the simulation results show that the distributed resource allocation game algorithm can effectively improve the energy efficiency, reduce network interference and bit error rate to ensure the successful data transmission.

Underwater Audio and Data Transmission System using Li-Fi Technology

Underwater communication system utilizing Li-Fi (Light Fidelity) technology for transmitting audio and data. The system addresses limitations of traditional methods by leveraging an Arduino Uno microcontroller for control, lasers for data transmission, and solar panels for reception. To enhance received audio signals, an amplifier circuit is employed before feeding them into a speaker for playback. Data is recovered and processed on the receiving end using the Arduino Uno. This research explores the feasibility of Li-Fi for underwater applications. The paper details the design and development of the communication system, including hardware components like lasers, solar panels, amplifier circuits, and speakers, along with the software implemented on the Arduino Uno. The results focus on the successful transmission and reception of both audio (heard through the speaker) and text data processed by the Arduino Uno. This work paves the way for further development of Li-Fi based underwater communication solutions for various applications. Keywords- Underwater Communication, Li-Fi (Light Fidelity), Arduino Uno, Laser Diode, Solar Panel, Audio Transmission, Data Transmission, Amplifier Circuit, Speaker

Laser communications system with drones as relay medium for healthcare applications.

This article introduces a prototype laser communication system integrated with uncrewed aerial vehicles (UAVs), aimed at enhancing data connectivity in remote healthcare applications. Traditional radio frequency systems are limited by their range and reliability, particularly in challenging environments. By leveraging UAVs as relay points, the proposed system seeks to address these limitations, offering a novel solution for real-time, high-speed data transmission. The system has been empirically tested, showcasing its ability to maintain data transmission integrity under various conditions. Results indicate a substantial improvement in connectivity, with high data transmission success rate (DTSR) scores, even amidst environmental disturbances. This study underscores the system's potential for critical applications such as emergency response, public health monitoring, and extending services to remote or underserved areas.

IoT-Enabled Real-Time Monitoring System for Electricity Consumption in Maritime SMEs: Design and Evaluation

The growing demand for electrical energy in Small and Medium Enterprises (SMEs) within the maritime sector, necessitates efficient and cost-effective monitoring systems. This paper presents the design and implementation of an Internet of Things (IoT)-based real-time monitoring system for electricity consumption, specifically aimed at maritime SMEs. Using SCT-013-000 and ZMPT101B sensors for current and voltage measurements, the system enables remote monitoring through the Cayenne IoT platform. Experimental results demonstrate an average accuracy rate of 93.94% for current measurement and 98.50% for voltage measurement. Data transmission success rates were 74.00% and 99.02% in two consecutive tests. The proposed system provides an affordable and practical solution for maritime SMEs, contributing to improved energy management, reduced operational costs, and the promotion of sustainable practices. Future work includes the integration of predictive analytics and smart grid technology to further enhance energy efficiency and sustainability in maritime operations.

Game-Theoretic Optimization Of Intelligent Iot Networks For Enhanced Resource Management In Precision Agriculture

The burgeoning application of Internet of Things (IoT) technologies in agriculture has revolutionized precision farming practices. Intelligent IoT networks equipped with sensors, actuators, and edge computing capabilities offer real-time monitoring and intelligent control over crucial agricultural parameters. However, optimizing resource allocation and network performance in these dynamic environments remains a complex challenge due to competing interests among network devices and potential interference between neighboring farms. This paper proposes a novel approach for optimizing intelligent IoT networks in precision agriculture using game theory. We first model the network as a non-cooperative game where individual devices act as rational players aiming to maximize their own utilities, represented by factors like data transmission success, energy efficiency, and resource utilization. We then employ Nash equilibrium and its refinements to determine stable and efficient network configurations. To address the potential for strategic manipulation and ensure collective benefit, we further introduce cooperative game mechanisms, such as coalition formation and resource sharing protocols, to incentivize collaborative behavior among devices. The efficacy of the proposed approach is evaluated through extensive simulations with realistic agricultural scenarios. Results demonstrate significant improvements in network performance metrics, including higher data throughput, reduced energy consumption, and improved resource utilization compared to traditional non-game-theoretic approaches. We conclude by discussing the real-world implementation challenges and future research directions in game-theoretic optimization of intelligent IoT networks for sustainable and efficient precision agriculture.

Seamless real-time thermal imaging system with ESP8266: wireless data transfer and display using UDP

Thermal imaging technology has become increasingly popular for various applications, including industrial monitoring, building automation, and medical diagnostics. However, existing thermal imaging systems often come with high costs and limited connectivity options. In this paper, we propose a method to address these challenges by utilizing the ESP8266 microcontroller to create a thermal imaging system that can measure thermal pixel values, transfer the data wirelessly using the ESP8266’s networking capabilities and display the pixel data in real-time on a Thin-film-transistor liquid-crystal (TFT) display. The objective is to establish a seamless and real-time transfer of thermal images within a local network environment. User datagram protocol (UDP) supports transmission via broadcast and multicast, making it highly efficient for delivering data to multiple clients or devices on a network. It allows a single UDP packet to be simultaneously sent to multiple destinations, enhancing its effectiveness. This feature simplifies the implementation of network protocols and applications, reducing their overall complexity. UDP is particularly well-suited for devices with limited resources, such as microcontrollers or embedded systems, where memory and computing power are constrained. Experimental results demonstrate the successful transmission and display of thermal pixel data between the ESP8266 microcontrollers using the UDP protocol. The project utilizes the Arduino framework along with ESP8266WiFi and UDP libraries to enable network connectivity and UDP communication. The sender and receiver devices are connected to the same local network, guaranteeing efficient and low-latency transmission of thermal pixel data. The system achieves real-time communication within a radius of approximately 15–18 m, ensuring immediate visualization of thermal images on connected displays. By minimizing latency, the system enables a seamless and instantaneous viewing experience offering seamless and instantaneous image visualization for the users.

A Salinity-Impact Analysis of Polarization Division Multiplexing-Based Underwater Optical Wireless Communication System with High-Speed Data Transmission

The majority of the Earth’s surface is covered by water, with oceans holding approximately 97% of this water and serving as the lifeblood of our planet. These oceans are essential for various purposes, including transportation, sustenance, and communication. However, establishing effective communication networks between the numerous sub-islands present in many parts of the world poses significant challenges. Underwater optical wireless communication, or UWOC, can indeed be an excellent solution to provide seamless connectivity underwater. UWOC holds immense significance due to its ability to transmit data at high rates, low latency, and enhanced security. In this work, we propose polarization division multiplexing-based UWOC system under the impact of salinity with an on–off keying (OOK) modulation format. The proposed system aims to establish high-speed network connectivity between underwater divers/submarines in oceans at different salinity levels. The numerical simulation results demonstrate the effectiveness of our proposed system with a 2 Gbps data rate up to 10.5 m range in freshwater and up to 1.8 m in oceanic waters with salinity up to 35 ppt. Successful transmission of high-speed data is reported in underwater optical wireless communication, especially where salinity impact is higher.

An incentive-based dynamic energy efficient spectrum allocation for cognitive radio networks

Cognitive radio is a successful technique for utilizing the unused and under-used spectrum, and dynamic spectrum access is one of the major facilitators in making this happen. When a secondary user (an unlicensed user) interferes with the licensed user, the idea of using unused or under-utilized spectrum offers a challenge. Therefore, effective spectrum sensing is necessary to ensure the primary user’s protection and the successful transmission of data by the secondary user. An Optimal Incentive algorithm is suggested to meet this need. It effectively uses the available idle channel based on the joint optimization of sensing time and transmission time without interfering with the primary user. The proposed work also contributes to a significant increase in energy efficiency with minimal interference. Simulation results show an increase in efficiency when compared with the algorithms, namely, exhaustive search and sub-optimal algorithms.

Investigation of Different Mechanisms to Detect Misbehaving Nodes in Vehicle Ad-Hoc Networks (VANETs)

The vehicle ad-hoc network (VANET) is a crucial technology that will play a significant role in shaping the future of transition systems, which is widely used as a subset of ad-hoc networks. VANET aims to ensure driver safety by establishing independent communication with nearby vehicles. A key requirement for successful data transmission is cooperation among nodes, as factors such as high mobility, limited radio range, signal fading, and noise lead to packet loss. Security issues in vehicle ad-hoc networks have recently become a major concern. One factor that affects security is the presence of abusive nodes in the network. Like selfish nodes, they are reluctant to share their sources with their neighbors and try to keep their property. The misbehavior of malicious nodes includes dissemination of false traffic information, false location information, and redirection of packets to a wrong path, retransmission of packets, impersonation, so these nodes should be tracked down to ensure the operation of the network. This article provides a complete summary of various research works proposed to detect selfish and malicious nodes and isolate them from honest vehicles. This review article first describes the types of attacks. It then presents the methods proposed by researchers to deal with uncooperative nodes and compares their performance based on parameters such as the number of misbehaving nodes detected, overhead, throughput, layer involved in the attacks.