Search Results (1,627)

Information diffusion models developed for Twitter, Reddit, and Facebook assume network contagion and competition for shared attention. Telegram operates differently. It is built around channels rather than social graphs, and users receive posts directly from subscribed channels without algorithmic mediation. We analyze over 5000 forwarding cascades from the Pushshift Telegram dataset to examine whether existing diffusion models generalize to this broadcast environment. Our findings reveal fundamental structural differences. Telegram forwarding produces perfect star topologies with zero multi-hop propagation. Every forward connects directly to the original message, creating trees with maximum depth of exactly 1. This contrasts sharply with Twitter retweet chains that routinely reach depths of 5 or more hops. Forwarding delays follow heavy-tailed Weibull or lognormal distributions with median delays measured in days rather than hours. Approximately 15 to 20 percent of cascades exhibit administrative bulk reposting rather than organic user-driven growth. Most strikingly, early-stage competitive overtaking is absent. Six of 30 pairs exhibit crossings, but these occur late (median 79 days) via administrative bursts rather than organic competitive acceleration during peak growth. We develop a delay-driven star diffusion model that treats forwarding as independent draws from a delay distribution. The model achieves median prediction errors below 10 percent for organic cascades. These findings demonstrate that platform architecture fundamentally shapes diffusion dynamics. Comparison with prior studies on Twitter, Weibo, and Reddit reveals that Telegram’s broadcast structure produces categorically different patterns—including perfect star topology and asynchronous delays—requiring platform-specific modeling approaches rather than network-based frameworks developed for other platforms. Full article

Research on Cooperative Driving Automation (CDA) has advanced to overcome the limited perception range of onboard sensors and the difficulty of inferring surrounding vehicles’ intentions by leveraging vehicle-to-everything (V2X) communications. This paper models how an autonomous vehicle receives cooperative sensing and cooperative maneuvering information generated at an edge roadside unit (edge RSU) that integrates roadside units (RSUs) with multi-access edge computing (MEC), and how the vehicle fuses this information with its onboard situational awareness and path-planning modules. We then analyze the performance gains of edge RSU-enabled services across diverse traffic environments. In a highway-merging scenario, simulations show that employing the edge RSU’s sensor sharing service (SSS) reduces collision risk relative to onboard-only baselines. For unsignalized intersections and roundabouts, we further propose a guidance-driven Hybrid Pairing Optimization (HPO) scheme in which the edge RSU aggregates CAV intents/trajectories, resolves spatiotemporal conflicts via lightweight pairing and time window allocation, and broadcasts maneuver guidance through MSCM. Unlike a first-come, first-served (FCFS) policy that serializes passage, HPO injects edge guidance as soft constraints while preserving arrival order fairness, enabling safe concurrent passage opportunities when feasible. Across intersections and roundabouts, HPO improves average speed by up to 192% and traffic throughput by up to 209% compared with FCFS under identical demand in our simulations. Full article

Connecting distributed applications across multiple cloud-native domains is growing in complexity. Applications have become containerized and fragmented across heterogeneous infrastructures, such as public clouds, edge nodes, and private data centers, including emerging IoT-driven environments. Existing networking solutions like CNI plugins and service meshes have proven insufficient for providing isolated, low-latency and secure multi-cluster communication. By combining SDN control with Kubernetes abstractions, we present L2S-CES, a Kubernetes-native solution for multi-cluster layer-2 network slicing that offers flexible isolated connectivity for microservices while maintaining performance and automation. In this work, we detail the design and implementation of L2S-CES, outlining its architecture and operational workflow. We experimentally validate against state-of-the-art alternatives and show superior isolation, reduced setup time, native support for broadcast and multicast, and minimal performance overhead. By addressing the current lack of native link-layer networking capabilities across multiple Kubernetes domains, L2S-CES provides a unified and practical foundation for deploying scalable, multi-tenant, and latency-sensitive cloud-native applications. Full article

The rapid growth in demand for diverse network application services has driven the continuous development and expansion of data centers. BCubes was proposed by Microsoft Research Asia for designing modular data centers, and it is a multi-layer recursively constructed network with many advantages. This article shows that BCube is the existence of two edge-disjoint Hamiltonian cycles, abbreviated as two EDHCs, which provide two significant benefits in data center operations: (1) parallel data broadcast and (2) edge fault-tolerance in network communications. We present the following results in this paper: (1) By utilizing the network topology characteristics, we first provide construction algorithms for two EDHCs on low-dimensional BCubes. (2) Based on the algorithm and the recursive structure of BCubes, we prove that two EDHCs exist for all BCubes. (3) Considering all-to-all broadcasting using two EDHCs as transmission channels, we evaluate the performance of all-to-all broadcasting through simulations on low-dimensional BCubes. Full article

With the increasing demand for high throughput and ultra-dense small cell deployment in the next-generation communication networks, spectrum resources are becoming increasingly strained. At the same time, the security risks posed by eavesdropping remain a significant concern, particularly due to the broadcast-access property of optical fronthaul networks. To address these challenges, we propose a high-security, high-spectrum efficiency radio-over-fiber (RoF) system in this paper, which leverages compressive sensing (CS)-based algorithms and chaotic encryption. An 8 Gbit/s RoF system is experimentally demonstrated, with 10 km optical fiber transmission and 20 GHz radio frequency (RF) transmission. In our experiment, spectrum efficiency is enhanced by compressing transmission data and reducing the quantization bit requirements, while security is maintained with minimal degradation in signal quality. The system could recover the signal correctly after dequantization with 6-bit fronthaul quantization, achieving a structural similarity index (SSIM) of 0.952 for the legitimate receiver (Bob) at a compression ratio of 0.75. In contrast, the SSIM for the unauthorized receiver (Eve) is only 0.073, highlighting the effectiveness of the proposed security approach. Full article

The Internet of Vehicles (IoV) can transmit the status information of vehicles and roads through single-hop or multi-hop broadcast communication, which is a key technology for building intelligent transportation systems and enhancing road safety. However, in dense traffic environments, broadcasting Emergency messages via vehicles can easily trigger massive forwarding redundancy, leading to channel resource selection conflicts between vehicles and affecting the reliability of inter-vehicle communication. This paper analyzes the forwarding near the single-hop transmission radius boundary of the sending node in a probability-based inter-vehicle multi-hop forwarding scheme, pointing out the existence of the boundary forwarding redundancy problem. To address this problem, this paper proposes two probability-based schemes with boundary optimization: (1) By optimizing the forwarding probability distribution outside the transmission radius boundary of the sending node, the forwarding nodes outside the boundary can be effectively utilized while effectively reducing the forwarding redundancy they bring. (2) Additional forwarding backoff timers are allocated to nodes outside the transmission radius boundary of the sending node based on the distance to further reduce the forwarding redundancy outside the boundary. Experimental results show that, compared with the reference schemes without boundary forwarding probability optimization, the proposed schemes significantly reduce forwarding redundancy of Emergency messages while maintaining good single-hop and multi-hop transmission performance. When the reference transmission radius is 300 m and the vehicle density is 0.18 veh/m, compared with the probability-based forwarding scheme without boundary optimization, the proposed schemes (1) and (2) improve the single-hop packet delivery ratio by an average of about 5.41% and 11.83% and reduce the multi-hop forwarding ratio by about 18.07% and 36.07%, respectively. Full article

In this paper, we propose a two-way hybrid satellite–terrestrial relay scheme employing Fountain codes (FCs). In the proposed model, a satellite and a ground user exchange data through a group of terrestrial relay stations, in the presence of an eavesdropper. In the first phase, the satellite and the ground user simultaneously transmit their encoded packets to the relay stations. The relay stations then apply a successive interference cancelation (SIC) technique to decode the received packets. To reduce the quality of the eavesdropping links, a cooperative jammer is employed to transmit jamming signals toward the eavesdropper during the first phase. Next, one of the relay stations which can successfully decode the encoded packets from both the satellite and the ground user is selected for data forwarding, by using a partial relay selection method. Then, this selected relay performs an XOR operation on the two encoded packets, and then broadcasts the XOR-ed packet to both the satellite and the user in the second phase. We derive exact closed-form expressions of outage probability (OP), system outage probability (SOP), intercept probability (IP), and system intercept probability (SIP), and realize simulations to validate these expressions. This paper also studies the trade-off between OP (SOP) and IP (SIP), as well as the impact of various system parameters on the performance of the proposed scheme. Full article

In order to effectively ensure the flight safety of unmanned aerial vehicles (UAVs) and effectively deal with the risk of integrated airspace operation, this study carried out a series of key technology exploration and verification. In terms of data processing, Density-based spatial clustering of applications with noise (DBSCAN) clustering method is used to preprocess the characteristics of UAV automatic dependent surveillance–broadcast (ADS-B) data, effectively purify the data from the source, eliminate the noise and outliers of track data in spatial dimension and spatial-temporal dimension, significantly improve the data quality and standardize the data characteristics, and lay a reliable and high-quality data foundation for subsequent trajectory analysis and prediction. In terms of trajectory prediction, the convolutional neural networks-bidirectional gated recurrent unit (CNN-BiGRU) trajectory prediction model is innovatively constructed, and the integrated intelligent calculation of ‘prediction-judgment’ is successfully realized. The output of the model can accurately and prospectively judge the conflict situation and conflict degree between any two trajectories, and provide core and direct technical support for trajectory conflict warning. In the aspect of conflict detection, the performance of the model and the effect of conflict detection are fully verified by simulation experiments. By comparing the predicted data of the model with the real track data, it is confirmed that the CNN-BiGRU prediction model has high accuracy and reliability in calculating the distance between aircraft. At the same time, the preset conflict detection method is used for further verification. The results show that there is no conflict risk between the UAV and the manned aircraft in integrated airspace during the full 800 s of terminal area flight. In summary, the trajectory prediction model and conflict detection method proposed in this study provide a key technical guarantee for the construction of an active and accurate integrated airspace security management and control system, and have important application value and reference significance for improving airspace management efficiency and preventing flight conflicts. Full article

Phased electromagnetic (EM) surfaces offer a versatile platform for beamforming, yet their application to wide-beam radiation—essential for broadcasting and target tracking—has been hindered by the absence of a foundational analytical model. This article establishes an effective model, quantitatively linking the maximum achievable beamwidth to the surface’s core physical parameters. A direct scaling equation is first derived for an idealized continuous aperture, revealing a proportionality among beamwidth, the quadratic phase coefficient, and aperture size, which demonstrates the potential for quasi-omnidirectional coverage. The model is then extended to practical scenarios, showing that the main-lobe taper is directly controlled by the aperture amplitude taper, establishing a decoupling principle for independent control of beam shape and width. Finally, by modeling the array factor of a discrete aperture, the trade-off between element spacing and maximum beamwidth is quantified, providing clear design rules to prevent grating lobe distortion. This work provides an intuitive, physics-based foundation for the systematic design and performance prediction of wide-beam phased EM surfaces. Full article

This article examines memory and monuments in the science fiction Star Trek franchise as a lens for understanding commemoration technologies and how futuristic visions of memorials anticipated real ones, especially during times of conflict. To understand the cultural reciprocity of sci-fi television and contemporary commemoration of war and trauma, we investigate the interactive website produced by the Israeli Public Broadcasting Corporation, Kan, titled Kan 7.10.360, which commemorates the victims of the 7 October 2023 Hamas massacre of civilians, soldiers, and policemen in Israel’s Gaza Envelope region. The 7.10.360 website employs advanced technologies to create what we identify as a digital “counter-monument.” By applying the concept of metamemorial science fiction relating to the Shoah, investigating its victims’ commemoration and examining the globital turn in memory work, we demonstrate that the Kan project realizes digital mnemonic practices engaged in Star Trek. We argue that the renowned series performs and anticipates three aspects of globital memory work and novel digital commemoration, also prevalent in the Kan 7.10.360 website: the personalization of memory using images; televisual testimony or documentation that mediates personal experience; and the display of objects that symbolize quotidian aspects of the victims’ lives. Full article

The civil Global Navigation Satellite System (GNSS) signal is broadcast with an open structure, making it vulnerable to spoofing attacks. Incorporating authentication data into GNSS signals is a significant measure to enhance system security. Precise Point Positioning (PPP) technology has garnered extensive attention for its ability to provide real-time services with centimeter-level accuracy. The PPP service features a high data update rate, with the validity period of the data being approximately ten to twenty seconds. This imposes more stringent requirements on the authentication data rate and the authentication time. Code Shift Keying (CSK) technology has emerged as a key candidate for satellite-based PPP signal design, as it can increase the data rate without requiring additional spectrum resources. This paper investigates authentication methods for CSK-modulated satellite-based PPP signals. Two approaches are proposed: phase modulation authentication and polarity modulation authentication. Simulation and analysis results indicate that the PPP signal with phase modulation authentication experiences less carrier-to-noise ratio (C/N₀) loss and has a higher detection probability. In contrast, the signal with polarity modulation authentication does not suffer from C/N₀ loss and achieves a higher data rate and a shorter authentication time. These findings can serve as valuable references for future GNSS signal design. Full article

A window-embedded broadband vehicle-mounted antenna for frequency modulation (FM) broadcast application is proposed. Antenna miniaturization at sub-gigahertz frequencies remains challenging due to the inherently long wavelengths, which impose strict constraints on compactness, bandwidth, and structural weight. A promising strategy to alleviate this problem is to use the vehicle itself as an effective radiator to enhance the bandwidth and maintain good radiation performance. In this work, the potentialities of the radiation patterns offered by the vehicle are analyzed by using the characteristic mode theory (CMT). A compact T-shape coupling element, with dimensions of 0.2λ₀ × 0.08λ₀ × 0.01λ₀, is employed to simultaneously excite multiple significant characteristic modes, thereby broadening the operating band. Both simulated and measured results validate that the proposed antenna can cover the FM broadcast operating band from 87 MHz to 108 MHz, with the 1:10 scaled prototype achieving a maximum measured gain of 7.4 dBi at 950 MHz. The proposed antenna and design strategy have advantages in radio broadcasting, radio navigation, and military and law enforcement communication systems for its low-cost, compact, and easy conformal structure. Full article

Objectives: Traffic accidents cause severe social and economic impacts, demanding fast and reliable detection to minimize secondary collisions and improve emergency response. However, existing cloud-dependent detection systems often suffer from high latency and limited scalability, motivating the need for an edge-centric and consensus-free accident detection framework in IoV environments. Methods: This study presents a real-time accident detection framework tailored for Internet of Vehicles (IoV) environments. The proposed system forms an integrated IoV architecture combining on-vehicle inference, RSU-based validation, and asynchronous cloud reporting. The system integrates a lightweight ensemble of Vision Transformer (ViT) and EfficientNet models deployed on vehicle nodes to classify video frames. Accident alerts are generated only when both models agree (vehicle-level ensemble consensus), ensuring high precision. These alerts are transmitted to nearby Road Side Units (RSUs), which validate the events and broadcast safety messages without requiring inter-vehicle or inter-RSU consensus. Structured reports are also forwarded asynchronously to the cloud for long-term model retraining and risk analysis. Results: Evaluated on the CarCrash and CADP datasets, the framework achieves an F1-score of 0.96 with average decision latency below 60 ms, corresponding to an overall accuracy of 98.65% and demonstrating measurable improvement over single-model baselines. Conclusions: By combining on-vehicle inference, edge-based validation, and optional cloud integration, the proposed architecture offers both immediate responsiveness and adaptability, contrasting with traditional cloud-dependent approaches. Full article

The rapid advancement of low-Earth-orbit (LEO) satellite constellations and unmanned aerial vehicles (UAVs) has positioned space–air–ground integrated networks as a key enabler of large-scale IoT services. However, ensuring reliable end-to-end operation remains challenging due to heterogeneous IoT–UAV link conditions and rapidly varying satellite visibility. This work proposes a two-stage optimization framework that jointly minimizes UAV energy consumption during IoT data acquisition and ensures stable UAV–LEO offloading through a demand-aware satellite association strategy. The first stage combines gradient-based refinement with combinatorial path optimization, while the second stage triggers handover only when the remaining offloading demand cannot be met. Simulation results show that the framework reduces UAV energy consumption by over 20% and shortens flight distance by more than 30% in dense deployments. For satellite offloading, the demand-aware strategy requires only 2–3 handovers—versus 7–9 under greedy selection—and lowers packet loss from 0.47–0.60% to 0.13–0.20%. By improving both stages simultaneously, the framework achieves consistent end-to-end performance gains across varying IoT densities and constellation sizes, demonstrating its practicality for future SAGIN deployments. Full article

This study examined the relationship between trust in COVID-19 information sources and self-rated health (SRH) among Latino Day Laborers (LDLs) and whether mental health mediated this association. Participants (N = 300) recruited at 18 job-seeking locations were interviewed in Spanish during November and December 2021. Validated scales were used to measure trust in formal (e.g., broadcast news, newspapers, and radio) and informal sources (e.g., friends, family, and social media) and mental health (depression, anxiety, and stress), with SRH measured with a single item. Mediation analysis was conducted using Hayes’ SPSS PROCESS macro. Higher trust in formal sources of information was related to lower SRH, but this relationship was not mediated by mental health. However, depression and anxiety were associated with a decrease in SRH. There were no significant direct or indirect effects between trust in informal sources and SRH. Depression and anxiety remained significant predictors of lower SRH. Further research is warranted on the mechanisms underlying these associations and the differential impact of information sources on vulnerable populations, such as LDLs, during health crises. Full article