Search Results (708)

Frequency-hopping multiple access is widely adopted to blunt narrow-band jamming and limit spectral disclosure in cyber–physical systems, yet its practical resilience depends on three sequence-level properties. First, balancedness guarantees that every carrier is occupied equally often, removing spectral peaks that a jammer or energy detector could exploit. Second, a wide gap between successive hops forces any interferer to re-tune after corrupting at most one symbol, thereby containing error bursts. Third, a no-hit zone (NHZ) window with a zero pairwise Hamming correlation eliminates user collisions and self-interference when chip-level timing offsets fall inside the window. This work introduces an algebraic construction that meets the full set of requirements in a single framework. By threading a permutation over an integer ring and partitioning the period into congruent sub-blocks tied to the desired NHZ width, we generate balanced wide gap no-hit zone frequency-hopping (WG-NHZ FH) sequence sets. Analytical proofs show that (i) each sequence achieves the Lempel–Greenberger bound for auto-correlation, (ii) the family and zone sizes satisfy the Ye–Fan bound with equality, (iii) the hop-to-hop distance satisfies a provable WG condition, and (iv) balancedness holds exactly for every carrier frequency. Full article

This paper proposes a multi-hop peer-to-peer (P2P) video streaming architecture designed to support dynamic, conversation-aware communication. The primary contribution is a decentralized system built on WebRTC that eliminates reliance on a central media server by employing super node aggregation. In this architecture, video streams from multiple peer nodes are dynamically routed through a group of super nodes, enabling real-time reconfiguration of the network topology in response to conversational changes. To support this dynamic behavior, the system leverages WebRTC data channels for control signaling and overlay restructuring, allowing efficient dissemination of topology updates and coordination messages among peers. A key focus of this study is the rapid and efficient reallocation of network resources immediately following conversational events, ensuring that the streaming overlay remains aligned with ongoing interaction patterns. While the automatic detection of such events is beyond the scope of this work, we assume that external triggers are available to initiate topology updates. To validate the effectiveness of the proposed system, we construct a simulation environment using Docker containers and evaluate its streaming performance under dynamic network conditions. The results demonstrate the system’s applicability to adaptive, naturalistic communication scenarios. Finally, we discuss future directions, including the seamless integration of external trigger sources and enhanced support for flexible, context-sensitive interaction frameworks. Full article

Vanillin photoinduced deprotonation was evaluated and analyzed. Vibronic states and transitions were computationally investigated. Optimizations and vertical electron transitions in the gas phase and with the continuum solvation model were computed using the time-dependent density functional theory. Static absorption and emission (photostatic optical) spectra were statistically averaged over the excited instantaneous molecular conformers fluctuating on quantum–classical molecular dynamic trajectories. Photostatic optical spectra were generated using the hybrid quantum–classical molecular dynamics for explicit solvent models. Conical intersection searching and nonadiabatic molecular dynamics simulations defined potential energy surface propagations, intersections, dissipations, and dissociations. The procedure included mixed-reference spin–flip excitations for both procedures and trajectory surface hopping for photodynamics. Insignificant structural deformations vs. hydroxyl bond cleavage followed by deprotonation were demonstrated starting from different initial structural conditions, which included optimized, transition state, and several other important fluctuating configurations in various environments. Vanillin electronic structure changes were illustrated and analyzed at the key points on conical intersection and nonadiabatic molecular dynamics trajectories by investigating molecular orbital symmetry and electron density difference. The hydroxyl group decomposed on transition to a σ-molecular orbital localized on the elongated O–H bond. Full article

With the rapid development of heterogeneous satellite networks integrating geostationary earth orbit (GEO) and low earth orbit (LEO) satellite systems, along with the significant growth in the number of satellite users, it is essential to consider frequency compatibility and coexistence between GEO and LEO systems, as well as to design effective system resource allocation strategies to achieve efficient utilization of system resources. However, existing beam-hopping (BH) resource allocation algorithms in LEO systems primarily focus on beam scheduling within a single time slot, lacking unified beam management across the entire BH cycle, resulting in low beam-resource utilization. Moreover, existing algorithms often employ iterative optimization across multiple resource dimensions, leading to high computational complexity and imposing stringent requirements on satellite on-board processing capabilities. In this paper, we propose a BH-based beam scheduling and resource allocation framework. The proposed framework first employs geographic isolation to protect the GEO system from the interference of the LEO system and subsequently optimizes beam partitioning over the entire BH cycle, time-slot beam scheduling, and frequency and power resource allocation for users within the LEO system. The proposed scheme achieves frequency coexistence between the GEO and LEO satellite systems and performs joint optimization of system resources across four dimensions—time, space, frequency, and power—with reduced complexity and a progressive optimization framework. Simulation results demonstrate that the proposed framework achieves effective suppression of both intra-system and inter-system interference via geographic isolation, while enabling globally efficient and dynamic beam scheduling across the entire BH cycle. Furthermore, by integrating the user-level frequency and power allocation algorithm, the scheme significantly enhances the total system throughput. The proposed progressive optimization framework offers a promising direction for achieving globally optimal and computationally tractable resource management in future satellite networks. Full article

Background: Ischemic preconditioning (IPC) is a non-invasive, time-efficient strategy that has been shown to acutely enhance athletic performance. The present study examined the effects of 5 min of IPC on vertical and horizontal jump performance. A secondary aim was to explore the associations between outcomes of the 5-Hop (5-H) test and drop jump performance, in order to provide further evidence supporting the validity of the 5-H test for assessing reactive strength characteristics in trained jumpers. Methods: Twelve trained track and field jumpers (nine males, three females, age: 23.2 ± 2.9 years; height: 1.76 ± 0.07 m; body mass: 71.5 ± 8.0 kg) completed two conditions: an IPC condition applied to one leg and a control condition applied to the contralateral leg. In the first week, one leg was assigned to IPC and the other to the control condition, while in the second week, the conditions for each leg were reversed. Vertical single-leg performance was evaluated by drop jump (DJ) height, ground contact time, and reactive strength index (RSI). Horizontal jump performance was assessed by a five-hop (5-H) test during which total distance (TD), total time (TT), and reactive hopping index (RHI) were obtained. Results: Compared to the control condition, IPC enhanced DJ height (+ 3.6%) and RSI (+ 7.8%) (p < 0.05, g = 0.16 and 0.32, respectively) and reduced contact time (−4.4% p < 0.05, g = 0.41). Also, IPC resulted in significant improvements in TD (+ 4.1%) and RHI (+ 3.9%) during the 5-H test (p < 0.05, g = 0.32 and 0.42, respectively), while TT remained unchanged. Conclusions: A single cycle of IPC acutely improved vertical and horizontal jump performance and reactive strength indices in trained jumpers. These findings support the use of IPC as a practical, time-efficient method to enhance neuromuscular performance in explosive tasks. Full article

In contrast to terrestrial networks, the rapid movement of low-earth-orbit (LEO) satellites causes frequent changes in the topology of intersatellite links (ISLs), resulting in dynamic shifts in transmission paths and fluctuations in multi-hop latency. Moreover, limited onboard resources such as buffer capacity and bandwidth competition contribute to the instability of these links. As a result, providing reliable quality of service (QoS) for time-sensitive flows (TSFs) in LEO satellite networks becomes a challenging task. Traditional terrestrial time-sensitive networking methods, which depend on fixed paths and static priority scheduling, are ill-equipped to handle the dynamic nature and resource constraints typical of satellite environments. This often leads to congestion, packet loss, and excessive latency, especially for high-priority TSFs. This study addresses the primary challenges faced by time-sensitive satellite networks and introduces a management framework based on software-defined networking (SDN) tailored for LEO satellites. An advanced queue management and scheduling system, influenced by terrestrial time-sensitive networking approaches, is developed. By incorporating differentiated forwarding strategies and priority-based classification, the proposed method improves the efficiency of transmitting time-sensitive traffic at multiple levels. To assess the scheme’s performance, simulations under various workloads are conducted, and the results reveal that it significantly boosts network throughput, reduces packet loss, and maintains low latency, thus optimizing the performance of time-sensitive traffic in LEO satellite networks. Full article

Routing in flying ad hoc networks (FANETs) is hindered by high mobility, trajectory-induced topology dynamics, and energy constraints. Conventional topology-based or position-based protocols often fail due to stale link information and limited neighbor awareness. This paper proposes a trajectory-informed routing protocol enhanced by Q-learning: Traj-Q-GPSR, tailored for mission-oriented UAV swarm networks. By leveraging mission-planned flight trajectories, the protocol builds time-aware two-hop neighbor tables, enabling routing decisions based on both current connectivity and predicted link availability. This spatiotemporal information is integrated into a reinforcement learning framework that dynamically optimizes next-hop selection based on link stability, queue length, and node mobility patterns. To further enhance adaptability, the learning parameters are adjusted in real time according to network dynamics. Additionally, a delay-aware queuing model is introduced to forecast optimal transmission timing, thereby reducing buffering overhead and mitigating redundant retransmissions. Extensive ns-3 simulations across diverse mobility, density, and CBR connections demonstrate that the proposed protocol consistently outperforms GPSR, achieving up to 23% lower packet loss, over 80% reduction in average end-to-end delay, and improvements of up to 37% and 52% in throughput and routing efficiency, respectively. Full article

Quasi-Synchronous Frequency hopping (FH) Multiple Access (QS-FHMA) systems feature high communication efficiency, strong flexibility, and low operational costs, and they have been widely used in various FH communication scenarios such as satellite communication, military communication, and radio measurement. The low-hit zone (LHZ) FH sequences set (LHZ FHS set) plays a critical role in QS-FHMA systems, enabling user access with permissible time-delay offsets while maintaining superior performance. In this paper, three new methods to construct LHZ FHS sets based on m-sequences are proposed. The newly constructed sequence sets achieve optimality with respect to the Peng–Fan bound. Compared with existing LHZ FHS sets constructed from m-sequences, these new sequence sets offer more flexible parameters. Furthermore, due to the simple structure of m-sequences and their extensive adoption in engineering applications, the proposed new sequence sets possess significant practical value for engineering implementation. Full article

With the rapid evolution of social computing, online sentiments have become valuable information for analyzing the latent structure of social networks. Sentiment leaders in social networks are those who bring in new information, ideas, and innovations, disseminate them to the masses, and thus influence the opinions and sentiment of others. Identifying sentiment leaders can help businesses predict marketing campaigns, adjust marketing strategies, maintain their partnerships, and improve their products’ reputations. However, capturing the complex sentiment dynamics from multi-hop interactions and trust/distrust relationships, as well as identifying leaders within sentiment-aligned communities while maximizing sentiment spread efficiently through both direct and indirect paths, is a significant challenge to be addressed. This paper pioneers a challenging and important problem of sentiment leader identification in social networks. To this end, we propose an original solution framework called “SentiRank” and develop the associated algorithms to identify sentiment leaders. SentiRank contains three key technical steps: (1) constructing a sentiment graph from a social network; (2) detecting sentiment communities; (3) ranking the nodes on the selected sentiment communities to identify sentiment leaders. Extensive experimental results based on the real-world datasets demonstrate that the proposed framework and algorithms outperform the existing algorithms in terms of both one-step sentiment coverage and all-path sentiment coverage. Furthermore, the proposed algorithm performs around 6.5 times better than the random approach in terms of sentiment coverage maximization. Full article

Wildfires are complex natural disasters that significantly impact ecosystems and human communities. The early detection and prediction of forest fire risk are necessary for effective forest management and resource protection. This paper proposes an innovative early detection system based on a wireless sensor network (WSN) composed of interconnected Arduino nodes arranged in a hybrid circular/star topology. This configuration reduces the number of required nodes by 53–55% compared to conventional Mesh 2D topologies while enhancing data collection efficiency. Each node integrates temperature/humidity sensors and uses ZigBee communication for the real-time monitoring of wildfire risk conditions. This optimized topology ensures 41–81% lower latency and 50–60% fewer hops than conventional Mesh 2D topologies. The system also integrates artificial intelligence (AI) algorithms (multiclass logistic regression) to process sensor data and predict fire risk levels with 99.97% accuracy, enabling proactive wildfire mitigation. Simulations for a 300 m radius area show the non-dense hybrid topology is the most energy-efficient, outperforming dense and Mesh 2D topologies. Additionally, the dense topology achieves the lowest packet loss rate (PLR), reducing losses by up to 80.4% compared to Mesh 2D. Adaptive routing, dynamic round-robin arbitration, vertical tier jumps, and GSM connectivity ensure reliable communication in remote areas, providing a cost-effective solution for wildfire mitigation and broader environmental monitoring. Full article

This paper addresses the critical challenge of time management in wireless sensor networks (WSNs) applied to industrial process control. Although wireless technologies have gained ground in industrial monitoring, their adoption in control applications remains limited due to concerns around reliability and timing accuracy. This study proposes a practical, low-cost solution based on commercial off-the-shelf (COTS) components, leveraging the IEEE 802.15.4-2020 standard in Time-Slotted Channel-Hopping (TSCH) mode. A custom time management algorithm is developed and implemented on STM32 microcontrollers paired with AT86RF212B transceivers. The proposed system ensures a sub-millisecond synchronization drift across nodes by dividing communication into a structured slot frame and implementing precise scheduling and enhanced beacon-based synchronization. Validation is performed through experimental setups monitored with logic analyzers, demonstrating a time drift consistently below 600 microseconds. The results confirm the feasibility of using synchronized wireless nodes for real-time industrial control tasks, suggesting that further improvements in hardware precision could enable even tighter synchronization and broader applicability in fast and critical processes. Full article

Timely status updates are essential for Internet of Things (IoT) services. The freshness of these updates can be quantified using Age of Information (AoI). The worst-case behavior of AoI is evaluated by peak AoI (PAoI), denoting the maximum AoI just before each successful update. To characterize the time-averaged evolution of the PAoI over a long time horizon, we adopt the average PAoI as a performance metric. In this paper, we consider a two-hop status update system in IoT monitoring networks, where sensors periodically transmit short status packets to a remote edge server via a sink node. The sink node encodes status packets received from multiple sensors into a single longer packet to enhance the transmission reliability of short-packet communications. Here, we analyze the average PAoI in this setup as a function of system parameters and minimize this function by jointly optimizing three key parameters: (i) the number of status packets for joint coding at the sink node, (ii) the blocklength of a status packet in the first hop, and (iii) the blocklength of a coded packet in the second hop. Through numerical studies, we demonstrate the effectiveness of the proposed optimization in reducing the average PAoI. Full article

We investigate the entanglement dynamics of two giant atoms coupled to a one-dimensional photonic lattice with synthetic chirality. The atoms are connected to multiple lattice sites in a braided configuration and interact with a structured photonic reservoir featuring direction-dependent hopping phases. By tuning the atomic detuning and the synthetic gauge phase, we identify distinct dynamical regimes characterized by decoherence-free population exchange, damped oscillations, long-lived revivals, and excitation trapping. Using a combination of time-domain simulations and resolvent-based analysis, we show how interference and band structure effects lead to the emergence of bound states, quasi-bound states, and phase-dependent entanglement dynamics. We compare the initial states with localized and delocalized atomic excitations, demonstrating that pre-existing entanglement can enhance the robustness against decoherence or accelerate its loss, depending on the system parameters. These results highlight the utility of synthetic photonic lattices and nonlocal emitter configurations in tailoring quantum coherence, entanglement, and information flows in structured environments. Full article

Industry 4.0 has transformed manufacturing and automation by integrating cyber–physical systems with the Industrial Internet of Things (IIoT) for real-time monitoring, intelligent control, and data-driven decision making. The IIoT increasingly relies on IEEE 802.15.4e Time-Slotted Channel Hopping (TSCH) to achieve reliable, low-latency, and energy-efficient industrial communications. The 6TiSCH protocol stack integrates scheduling and routing to optimize transmissions for resource-constrained devices, enhancing Quality of Service (QoS) in IIoT deployments. This paper proposes an innovative adaptive and cross-layer slotframe allocation technique for 6TiSCH networks, dynamically scheduling cells based on node hop distance, queue backlog, predicted traffic load, and link quality metrics. By dynamically adapting to these parameters, the proposed method significantly improves key QoS metrics, including end-to-end latency, packet delivery ratio, and network lifetime. The mechanism integrates real-time queue backlog monitoring, link performance analysis, and energy harvesting awareness to optimize cell scheduling decisions proactively. The results demonstrate that the proposed strategy reduces end-to-end latency by up to 32%, enhances PDR by up to 27%, and extends network lifetime by up to 10% compared to state-of-the-art adaptive scheduling solutions. Full article

Given the problems of uneven distribution, strong time variability of ground service demands, and low utilization rate of on-board resources in Low-Earth-Orbit (LEO) satellite communication systems, how to efficiently utilize limited beam resources to flexibly and dynamically serve ground users has become a research hotspot. This paper studies the dynamic resource allocation and interference suppression strategies for beam hopping satellite communication systems. Specifically, in the full-frequency-reuse scenario, we adopt spatial isolation techniques to avoid co-channel interference between beams and construct a multi-objective optimization problem by introducing weight coefficients, aiming to maximize user satisfaction and minimize transmission delay simultaneously. We model this optimization problem as a Markov decision process and apply a value decomposition network (VDN) algorithm based on cooperative multi-agent reinforcement learning (MARL-VDN) to reduce computational complexity. In this algorithm framework, each beam acts as an agent, making independent decisions on hopping patterns and power allocation strategies, while achieving multi-agent cooperative optimization through sharing global states and joint reward mechanisms. Simulation results show that the applied algorithm can effectively enhance user satisfaction, reduce delay, and maintain high resource utilization in dynamic service demand scenarios. Additionally, the offline-trained MARL-VDN model can be deployed on LEO satellites in a distributed mode to achieve real-time on-board resource allocation on demand. Full article