Search Results (775)

This paper addresses the problem of achieving consensus control for homogeneous multi-agent systems (MASs) under aperiodic sampled data and communication delays. By incorporating additional delay information, this paper introduces two novel delay-incorporating integral terms, an enhanced two-sided looped functional, and a novel discontinuous function to further exploit system state responses observed during sampling and data transmission. In addition, this paper introduces two additional zero equalities to derive less conservative stability and stabilization conditions. Based on these, sufficient conditions for guaranteeing consensus in MASs under this context are derived as linear matrix inequalities (LMIs). Finally, the effectiveness and superiority of the proposed method are validated through a numerical example. Full article

The currently observed development of time-sensitive applications also affects wireless communication with the IoT carried by UAVs. Although research on wireless low-latency networks has matured, there are still issues to solve at the transport layer. Since there is a general agreement that classical transport solutions are not able to achieve end-to-end delays in the single-digit millisecond range, in this paper, the use of WebRTC is proposed as a potential solution to this problem. This article examines UAV-borne WebRTC-based IoT in an outdoor environment. The results of field experiments conducted under various network conditions show that, in highly reliable networks, UAV and WebRTC-based IoT achieved stable end-to-end delays well below 10 ms during error-free air-to-ground transmissions, and below 10 ms in the immediate vicinity of the retransmitted packet. The significant advantage of the WebRTC data channel over the classic WebSocket is also demonstrated. Full article

Internet congestion control focuses on balancing effective network utilization with the avoidance of congestion. When bottleneck bandwidth and network buffer capacities are exceeded, congestion typically manifests as packet loss. Additionally, when packets remain in buffers for too long, a queueing delay occurs. Most existing congestion control algorithms aim to solve this as a constraint satisfaction problem, where constraints are defined by bandwidth or queueing delay limits. However, these approaches often emphasize finding feasible solutions over optimal ones, which often lead to under-utilization of available bandwidth. To address this limitation, this article leverages Little’s Law to derive a closed-form optimality equation for congestion control. This optimality equation serves as the foundation for developing a new algorithm, TCP QtColFair, designed to optimize the sending rate. TCP QtColFair is evaluated against two widely deployed congestion control algorithms: TCP CUBIC, which utilizes a cubic window growth function to enhance performance in high-bandwidth, long-distance networks and TCP BBR (Bottleneck Bandwidth and Round-trip propagation time), developed by Google to optimize data transmission by estimating the network’s bottleneck bandwidth and round-trip time. In terms of avoiding queueing delays and minimizing packet loss, TCP QtColFair outperforms TCP CUBIC and matches TCP BBR’s performance when network buffers are large. For effective network utilization, TCP QtColFair outperforms both TCP BBR and TCP CUBIC. TCP QtColFair achieves an effective utilization of approximately 96%, compared to just above 94% for TCP BBR and around 93% for TCP CUBIC. Full article

Underwater acoustic (UWA) communication encounters significant challenges, including impulsive noise from breaking waves and marine organisms, as well as long-delay taps caused by ocean properties and high transmission rates. To address these issues, we enhance the channel estimation process by introducing iteratively reweighted least squares (IRLS) methods and propose an impulsive noise suppression algorithm. Furthermore, we analyze the inter-frequency interference (IFI) resulting from channel variability and implement IFI cancellation (IFIC) during iterative processing. Furthermore, an IFIC-based dual decision–feedback equalization (DDFE) algorithm is proposed for fast time-varying channels, enabling a considerable reduction in channel length and subsequent equalizer complexity. The proposed IFIC-based DDFE algorithm with impulsive noise suppression has been validated through sea trial data, demonstrating robustness against impulsive noise. Experimental results indicate that the proposed algorithm reduces click signal energy and significantly improves receiver performance compared to traditional DDFE algorithms. This research highlights the effectiveness of adapted UWA communication strategies in environments characterized by impulsive noise and long delay taps, facilitating more reliable UWA communication. Full article

This paper introduces a novel energy-efficient lightweight, void hole avoidance, localization, and trust-based scheme, termed as Energy-Efficient and Trust-based Autonomous Underwater Vehicle (EETAUV) protocol designed for 6G-enabled underwater acoustic sensor networks (UASNs). The proposed scheme addresses key challenges in UASNs, such as energy consumption, network stability, and data security. It integrates a trust management framework that enhances communication security through node identification and verification mechanisms utilizing normal and phantom nodes. Furthermore, a 6G communication module is deployed to reduce network delay and enhance packet delivery, contributing to more efficient data transmission. Leveraging Autonomous Underwater Vehicles (AUVs), the EETAUV protocol offers a lightweight approach for node discovery, identification, and verification while ensuring a high data transmission rate through a risk-aware strategy including at low computational cost. The protocol’s performance is evaluated through extensive simulations and compared against state-of-the-art methods across various metrics, including network lifetime, throughput, residual energy, packet delivery ratio, mean square error, routing overhead, path loss, network delay, trust, distance, velocity, Computational Cost of Routing, and data security. The results demonstrate the superior cumulative performance of the proposed EETAUV scheme, making it a robust solution for secure, efficient, and reliable communication in UASNs. Full article

We introduce a novel wired communication approach for interactive wearable systems, employing a single signal wire and innovative group addressing protocol to reduce overhead. While wireless solutions dominate body sensor networks, wired approaches offer advantages for interactive applications that require low latency, high reliability, and communication with high-density nodes; yet they have been less explored in the context of wearable systems. Many commercial products use wired connections without disclosing technical details, limiting broader adoption. To address this gap, we present and test a new group addressing protocol implemented using Universal Asynchronous Receiver–Transmitter (UART) hardware, disclosing frame diagrams and node architectures. We developed a prototype interactive jacket with nine sensor/actuator nodes connected via three wires for power supply and data transmission to a wireless gateway. Mathematical analysis showed an overhead reduction of approximately 50% compared to traditional individual addressing. Our solution is the most wire-efficient among wired interactive wearable systems reviewed in the literature, using only one signal wire; other methods require at least two wires and often have overlapping topologies. Performance experimental evaluation revealed a total feedback delay of 2.27 ms and a maximum data frame rate of 435.4 Hz, comparable to the best-performing products and leaving room for twice the performance calculated theoretically. These results indicate that the proposed approach is suitable for interactive wearable systems, both for real-time applications and high-resolution data acquisition. Full article

The integration of unmanned aerial vehicles (UAVs) into vehicular networks offers numerous advantages in enhancing communication and coverage performance. With the ability to move flexibly in three-dimensional space, UAVs can effectively bridge the communication gap between intelligent connected vehicles (ICVs) and infrastructure. However, the rapid movement of UAVs and ICVs poses significant challenges to the stability and reliability of communication links. Motivated by these challenges, integrated UAV–ICV networks can be viewed as vehicular delay-tolerant networks (VDTNs), where data delivery is accomplished through the “store-carry-forward” transmission mechanism. Since VDTNs exhibit social attributes, this paper first investigates the opportunistic transmission problem in the presence of selfish nodes. Then, by enabling node cooperation, this paper proposes an opportunistic transmission scheme for integrated UAV–ICV networks. To address the issue of node selfishness in practical scenarios, the proposed scheme classifies the degree of cooperation and analyzes the encounter probability between nodes. Based on this, information is initially flooded, and the UAV is selected for data distribution by jointly considering the node centrality, energy consumption, and cache size. Finally, simulation results demonstrate that the proposed scheme can effectively improve the delivery ratio and reduce the average delivery delay compared to state-of-the-art schemes. Full article

The high mobility and dynamic nature of unmanned aerial vehicles (UAVs) pose significant challenges to clustering and routing in flying ad hoc networks (FANETs). Traditional methods often fail to achieve stable networks with efficient resource utilization and low latency. To address these issues, we propose a hybrid bio-inspired algorithm, HMAO, combining the mountain gazelle optimizer (MGO) and the aquila optimizer (AO). HMAO improves cluster stability and enhances data delivery reliability in FANETs. The algorithm uses MGO for efficient cluster head (CH) selection, considering UAV energy levels, mobility patterns, intra-cluster distance, and one-hop neighbor density, thereby reducing re-clustering frequency and ensuring coordinated operations. For cluster maintenance, a congestion-based approach redistributes UAVs in overloaded or imbalanced clusters. The AO-based routing algorithm ensures reliable data transmission from CHs to the base station by leveraging predictive mobility data, load balancing, fault tolerance, and global insights from ferry nodes. According to the simulations conducted on the network simulator (NS-3.35), the HMAO technique exhibits improved cluster stability, packet delivery ratio, low delay, overhead, and reduced energy consumption compared to the existing methods. Full article

Based on the C/S multithreaded control framework, this article used AES encryption technology, and by customizing the S-boxes therein and differential diffusion of the S-boxes, it improved the randomness of the ciphertexts and the resistance to differential attacks, and reduced the likelihood of leakage in the process of data computation. On this basis, in order to reduce the cost overhead generated by AES encryption, this paper used the pre-computed method of optimizing S-boxes and Mixcolumn matrices to be applied to the multithreaded control framework, which improved the computation rate of AES, and then it improved the efficiency of the information transmission in the multithreaded control process. In addition, by using the TLS protocol, the authentication module was set up on the client and server side, which effectively defended against various attacks on data transmission by external users. The experimental results indicate that after the optimization of the multithreaded C/S architecture, the corresponding time of the average transmission delay was reduced by 49.1%, the throughput rose by 96.4%, and the acceleration ratio reached 1.96. Full article

The limited coverage of terrestrial base stations and the limited transmission distance and onboard resources of satellite communications make it difficult to ensure the quality of communication services for marine users by relying only on satellites and terrestrial base stations. In contrast, UAVs, as flexible mobile communication nodes, have the capacity for dynamic deployment and real-time adjustment. They can effectively make up for the communication blind spots of traditional satellites and ground base stations in the marine environment, especially in the vast and unpredictable marine environment. Considering the mobility of maritime users, one can effectively reduce the communication delay and optimize the deployment scheme of UAVs by predicting their sailing trajectories in advance, thus enhancing the communication service quality. Therefore, this paper proposes a communication coverage model based on mobile user route prediction and a UAV dynamic deployment algorithm (RUDD). It aims to optimize the coverage efficiency of the maritime communication network, minimize the communication delay, and effectively reduce the energy consumption of UAVs. In this algorithm, the RUDD algorithm employs a modified Long Short-Term Memory (LSTM) network to predict the maritime user’s trajectory, utilizing its strengths in processing time-series data to provide accurate predictions. The prediction results are then used to guide the Proximal Policy Optimization (PPO) algorithm for the dynamic deployment of UAVs. The PPO algorithm can optimize the deployment strategy in dynamic environments, improve communication coverage, and reduce energy consumption. Simulation results show that the proposed algorithm can complement the existing satellite and terrestrial networks well in terms of coverage, with a communication coverage rate of more than 95%, which significantly improves the communication quality of marine users in areas far from land and beyond the reach of traditional networks, and enhances network reliability and user experience. Full article

With the development of Internet of Vehicles (IoV) technology, the need for real-time data processing and communication in vehicles is increasing. Traditional request-based methods face challenges in terms of latency and bandwidth limitations. Mode 4 in cellular vehicle-to-everything (C-V2X), also known as autonomous resource selection, aims to address latency and overhead issues by dynamically selecting communication resources based on real-time conditions. However, semi-persistent scheduling (SPS), which relies on distributed sensing, may lead to a high number of collisions due to the lack of centralized coordination in resource allocation. On the other hand, non-orthogonal multiple access (NOMA) can alleviate the problem of reduced packet reception probability due to collisions. Age of Information (AoI) includes the time a message spends in both local waiting and transmission processes and thus is a comprehensive metric for reliability and latency performance. To address these issues, in C-V2X, the waiting process can be extended to the queuing process, influenced by packet generation rate and resource reservation interval (RRI), while the transmission process is mainly affected by transmission delay and success rate. In fact, a smaller selection window (SW) limits the number of available resources for vehicles, resulting in higher collisions when the number of vehicles is increasing rapidly. SW is generally equal to RRI, which not only affects the AoI part in the queuing process but also the AoI part in the transmission process. Therefore, this paper proposes an AoI estimation method based on multi-priority data type queues and considers the influence of NOMA on the AoI generated in both processes in C-V2X system under different RRI conditions. Our experiments show that using multiple priority queues can reduce the AoI of urgent messages in the queue, thereby providing better service about the urgent message in the whole vehicular network. Additionally, applying NOMA can further reduce the AoI of the messages received by the vehicle. Full article

The research conducted in this preclinical study assesses QazCovid-live, a live attenuated COVID-19 vaccine created in Kazakhstan, by conducting preclinical evaluations of safety, immunogenicity, and allergenicity in various animal models, including mice, rats, hamsters, and guinea pigs. The vaccine, developed by attenuating SARS-CoV-2 via numerous Vero cell passages, had no significant adverse effects in acute and subacute toxicity assessments, even at elevated dosages. Allergenicity testing indicated the absence of both immediate and delayed hypersensitivity reactions. Immunogenicity evaluations revealed strong virus-neutralizing antibody responses, especially following intranasal and intratracheal delivery. Studies on reversibility and transmission further validated the vaccine’s stability and non-pathogenicity. The data indicate that QazCovid-live is safe, immunogenic, and prepared for clinical trials, presenting a potential strategy for COVID-19 prevention. Full article

In mobile networks, a content server can provide multiple services simultaneously to a mobile device, generating multiple data flows. As the device moves, the transmission path in the wired network may need to be switched to maintain service continuity. However, a single switching path may not be able to accommodate all the flows, potentially leading to congestion and a degraded user experience. To address this challenge, we propose a multi-topology routing-based mobile data scheduling method that dynamically switches flows across multiple paths to enhance flexibility and load balancing. The performance of this method is significantly influenced by the construction of logical topologies. Well-designed topologies provide high-bandwidth, low-latency paths to all possible destination nodes, while poorly designed topologies waste switch capacity and fail to achieve these goals. In this paper, we introduce an efficient multi-topology construction method for scheduling mobile data flows in software-defined networking (SDN). Our approach optimizes and balances transmission capacity for each destination node while adhering to the flow entry constraints of switches. Simulations demonstrate that our method consistently outperforms the single-path switching method and the other two multi-topology construction methods in terms of packet delay, packet loss rate, and network throughput, regardless of the device’s new location. Full article

This paper describes an all-digital clock and data recovery (CDR) circuit for implementing edge processing with a wireless body area network (WBAN). The CDR circuit performs delay-locked loop (DLL)-based and phase-locked loop (PLL)-based operations depending on the use of an external reference clock and is implemented using a digital method that is robust against external noise. The clock generator circuit shared by the two operation methods is described in detail, and the CDR circuit recovers 42 Mb/s input data and a 42 MHz clock, which are the specifications of human body communication (HBC). In DLL-based CDR operation, the clock generator operates as a digitally controlled delay line (DCDL) that delays the reference clock by more than one period. In PLL-based CDR operations, it operates as a digitally controlled oscillator (DCO) that oscillates the 42 MHz clock and adjusts the clock frequency. The proposed all-digital CDR is fabricated in 65 nm CMOS technology with an area of 0.091 mm² and operates with a supply voltage of 1.0 V. Post-layout simulation results show that the lock time for DLL-based CDR operation is 1.6 μs, the clock peak-to-peak jitter is 0.38 ns, and the power consumption is 341.8 μW. For PLL-based CDR operations, the lock time is 6 μs, the clock peak-to-peak jitter is 2.92 ns, and the power consumption is 280.2 μW, respectively. Full article

The satellite Internet can cover up to 70% of the surface of our planet Earth to provide network services for nearly 3 billion people. As such, it is promising to become the building block of future 6G networks. The satellite Internet is capable of providing uniform communication capacity to every part of the Earth’s surface, due to its uniform and symmetrical constellation structure, while the uneven distribution of ground populations leads to globally uneven traffic delivery requests, incurring a mismatch between the capacity and traffic transmission demands. As such, traditional single-criteria (e.g., shortest delay) routing algorithms can lead to severe network congestion and cannot provision delay-deterministic data delivery. To overcome this bottleneck, we propose a multi-criteria routing and scheduling scheme to redirect time-tolerant data, thus preventing congestion for time-sensitive data, based on the spatiotemporal distribution of data traffic. First, we construct a traffic spatiotemporal distribution model, to indicate the network load status. Next, we model the satellite network multi-criteria routing problem as an integer linear programming one, which is NP-hard and challenging to solve within polynomial time. A novel link weight design based on both the link delay and load is introduced, transforming the mathematical programming problem into a routing optimization problem. The proposed correlation scheduling algorithm fully utilizes idle network link resources, significantly improving network resource utilization and eliminating resource competition between non-time-sensitive and time-sensitive services. Simulation results show that compared with traditional algorithms, the proposed method can increase the throughput of time-sensitive data by up to 20.8% and reduce the packet loss rate of time-sensitive services by up to 76.8%. Full article