Search Results (83)

This study evaluates leadership uniformity—the degree to which the proposer role is evenly distributed among validator nodes over time—in Quorum-based Byzantine Fault Tolerance (QBFT), a Byzantine Fault-Tolerant (BFT) consensus algorithm used in permissioned blockchain networks. By introducing simulated follower timeouts derived from uniform, normal, lognormal, and Weibull distributions, it models a range of network conditions and latency patterns across nodes. This approach integrates Raft-inspired timeout mechanisms into the QBFT framework, enabling a more detailed analysis of leader selection under different network conditions. Three leader selection strategies are tested: Direct selection of the node with the shortest timeout, and two quorum-based approaches selecting from the top 20% and 30% of nodes with the shortest timeouts. Simulations were conducted over 200 rounds in a 10-node network. Results show that leader selection was most equitable under the Weibull distribution with shape $k=0.5$, which captures delay behavior observed in real-world networks. In contrast, the uniform distribution did not consistently yield the most balanced outcomes. The findings also highlight the effectiveness of quorum-based selection: While choosing the node with the lowest timeout ensures responsiveness in each round, it does not guarantee uniform leadership over time. In low-variability distributions, certain nodes may be repeatedly selected by chance, as similar timeout values increase the likelihood of the same nodes appearing among the fastest. Incorporating controlled randomness through quorum-based voting improves rotation consistency and promotes fairer leader distribution, especially under heavy-tailed latency conditions. However, expanding the candidate pool beyond 30% (e.g., to 40% or 50%) introduced vote fragmentation, which complicated quorum formation in small networks and led to consensus failure. Overall, the study demonstrates the potential of timeout-aware, quorum-based leader selection as a more adaptive and equitable alternative to round-robin approaches, and provides a foundation for developing more sophisticated QBFT variants tailored to latency-sensitive networks. Full article

Strawberry harvesting represents a labor-intensive agricultural operation where existing end-effector pose control algorithms frequently exhibit insufficient precision in fruit grasping, often resulting in unintended damage to target fruits. Concurrently, deep learning-based pose control algorithms suffer from inherent training instability, slow convergence rates, and inefficient learning processes in complex environments characterized by high-density fruit clusters and occluded picking scenarios. To address these challenges, this paper proposes an enhanced reinforcement learning framework DRFW-TQC that integrates Dynamic L2 Regularization for adaptive model stabilization and a Group-Wise Feature Weighting Network for discriminative feature representation. The methodology further incorporates a picking posture traction mechanism to optimize end-effector orientation control. The experimental results demonstrate the superior performance of DRFW-TQC compared to the baseline. The proposed approach achieves a 16.0% higher picking success rate and a 20.3% reduction in angular error with four target strawberries. Most notably, the framework’s transfer strategy effectively addresses the efficiency challenge in complex environments, maintaining an 89.1% success rate in eight-strawberry while reducing the timeout count by 60.2% compared to non-adaptive methods. These results confirm that DRFW-TQC successfully resolves the tripartite challenge of operational precision, training stability, and environmental adaptability in robotic fruit harvesting systems. Full article

The ongoing adoption of Robot Operating Systems (ROSs) not only for research-oriented projects but also for industrial applications demands a more thorough assessment of its security than in the past. This paper highlights that a key ROS component—the ROS Master—is indeed vulnerable to a novel kind of Slow Denial of Service (slow DoS) attack, the root reason of this vulnerability being an extremely high idle connection timeout. The effects of vulnerability exploitation have been evaluated in detail by means of a realistic test bed, showing how it leads to a systemwide and potentially dangerous disruption of ROS system operations. Moreover, it has been shown how some basic forms of built-in protection of the Linux kernel can be easily circumvented, and are therefore ineffective against this kind of threat. Full article

Timeouts are a widely supported strategy in the literature, recognized for directly influencing team performance during basketball games. This study aimed to analyze and define the successful patterns of actions after timeouts (ATOs) during critical moments in the 2022/23 EuroLeague season. The sample was drawn from the last two minutes and overtime of 169 games with a final point difference of 10 points or fewer, totaling 365 ATOs. An observational methodology was used, applying the LINCE PLUS software version 2.1.0 and an ad hoc observational instrument. Descriptive analysis and chi-square tests (χ²) were conducted using SPSS 25.0, and T-pattern analysis was performed with Theme 6 software. Statistical significance was set at p < 0.05. Teams in the lead often concluded successful plays through free throws following opponent fouls, while teams trailing behind attempted to close the gap by committing fouls to force free throws in defense and scoring two-point baskets on offense. The findings offer insights into ATOs strategies that can support coaches and technical staff in training and adapting these actions to meet competition demands during critical game moments. These results may assist in enhancing team performance and decision-making under high-stakes conditions. Full article

Proximity-based content sharing between nearby devices in cellular networks using device-to-device (D2D) communications—without routing through the base station—has emerged as a promising solution for offloading traffic from the core cellular network and reducing network congestion, especially when the users requesting content can tolerate some delay before receiving it. Although several analytical models have been developed to derive theoretical performance bounds of D2D-based offloading schemes under different user mobility patterns and routing algorithms used for content dissemination, how to jointly analyse time-limited caching and forwarding policies with both constant and asynchronous timeouts remains still an unsolved problem. To address this issue, we propose a novel fluid model based on ordinary differential equations (ODEs) for the performance analysis of a general D2D-based mobile data offloading scheme, called OORS, which considers both content delivery guarantees and time limitations for storing content copies in local device caches, making it more practical for real-world applications. We also formulate an optimisation problem to maximise the utility of the content dissemination process through a simplified analysis of the stationary regime of the ODE model. Simulation results validate the accuracy of our model predictions, in terms of both aggregate statistics and the temporal evolution of the system state, using both synthetic and real-world mobility datasets. Finally, we compare OORS—optimally tuned with respect to protocol parameters—to two state-of-the-art content offloading schemes, Push-and-track (PAT) and SNSNI, a seed node selection algorithm based on node influence. Our results show that OORS achieves similar offloading efficiency to the benchmarks while reducing the number of content copies by at least 50%. Full article

The rapid growth of the Internet of Things (IoT) has contributed to significant challenges in dealing with congestion within IoT communications due to high packet error rates, latency, and interference in networks. With an emphasis on the Constrained Application Protocol (CoAP), the present study aims to propose the design and development of a novel congestion control mechanism, namely, Fast Response Congestion Control—Random Early Detection, abbreviated as FaCoCo-RED, along with performance analysis and comparison of congestion management efficacy between FaCoCo-RED and Default CoAP Congestion Control (Default CoAP CC) under a Cooja simulator on the Contiki OS platform. The findings from both experiment and performance analysis, which were based on statistical testing, showed that, under medium-scale to large-scale node networks across all traffic scenarios in this study, FaCoCo-RED significantly outperformed Default CoAP CC. The improvement can be seen in such metrics as average throughput, packet loss, response time, settling time, and retransmission timeout values (RTOs). The experimental findings also showed that FaCoCo-RED can perform effectively within the IoT networks, thus potentially enhancing the reliability and scalability of CoAP for large-scale and more complex IoT applications in the future. Full article

Named data networking (NDN) is a novel networking paradigm characterized by in-network caching, receiver-driven communication, and multi-source, multi-path data retrieval, which poses new challenges for congestion control. Existing work has largely focused on receiver-driven mechanisms. Due to delays in obtaining network control information (timeouts, NACKs) within NDN, consumers are unable to access the network congestion status from this information in a timely manner. To address the issues above, this paper combines the Q-learning algorithm with the NDN architecture, proposing Q-NDN. In Q-NDN, consumers can dynamically adjust the congestion window (cwnd) through the real-time monitoring of network status, leveraging the Q-learning algorithm, achieving automatic congestion control for the NDN architecture. Additionally, this paper introduces content popularity-based traffic scheduling for multi-user scenarioswhich adjusts the transmission rates of content with different popularity levels to maintain a dynamic balance in the network. The experimental results show that Q-NDN can converge quickly, make full use of bandwidth resources, and keep the packet loss rate to 0 in the basic network topology. In competing network topologies, Q-NDN can rapidly address conflict issues, efficiently utilize bandwidth resources, and maintain a relatively low packet loss rate. Full article

When developing a distributed application, several issues need to be handled, and software components should include some mechanisms to make their execution resilient when network faults, delays, or tampering occur. For example, synchronous calls represent a too-tight connection between a client requesting a service and the service itself, whereby potential network delays or temporary server overloads would keep the client side hanging, exposing it to a domino effect. The proposed approach assists developers in dealing with such issues by providing an automatic tool that enhances a distributed application using simple blocking calls and makes it robust in the face of adverse events. The proposed devised solution consists in automatically identifying the parts of the application that connect to remote services using simple synchronous calls and substituting them with a generated customized snippet of code that handles potential network delays or faults. To accurately perform the proposed transformation, the devised tool finds application code statements that are data-dependent on the results of the original synchronous calls. Then, for the dependent statements, a solution involving guarding code, proper synchronization, and timeouts is injected. We experimented with the analysis and transformation of several applications and report a meaningful example, together with the analysis of the results achieved. Full article

To increase bandwidth and overcome packet loss in Wide Area Networks (WANs), per-packet multipath transmission and redundant transmission are increasingly being used as Software-Defined Wide Area Network (SD-WAN) solutions. However, this results in out-of-order and duplicate packets in the destination network. To restore sequential and unique data streams for multiple connections, hardware packet buffers with significant depth are required due to the large delay difference between WAN paths. To address this issue, SSPRD, a shared-storage-based packet reordering and deduplication system using a Field-Programmable Gate Array (FPGA), is proposed. The storage space for packets and sub-buffers is shared by all sessions with dynamic allocation. Packets are stored in the DDR and are sorted by their descriptors in the buffers. We also develop a sub-buffer-based timeout event handling algorithm. While supporting four sessions, SSPRD achieves a deep reorder buffer on hardware, with a depth of up to 15,360 packets per session. Compared with other solutions, SSPRD reduces buffer space usage by 62.5%, and reaches a packet reordering and deduplicating performance of 10 Gbps for 1500-byte packets. Full article

As an important part of urban terminal delivery, automated guided vehicles (AGVs) have been widely used in the field of takeout delivery. Due to the real-time generation of takeout orders, the delivery system is required to be extremely dynamic, so the AGV needs to be dynamically scheduled. At the same time, the uncertainty in the delivery process (such as the meal preparation time) further increases the complexity and difficulty of AGV scheduling. Considering the influence of these two factors, the method of embedding a stochastic programming model into a rolling mechanism is adopted to optimize the AGV delivery routing. Specifically, to handle real-time orders under dynamic demand, an optimization mechanism based on a rolling scheduling framework is proposed, which allows the AGV’s route to be continuously updated. Unlike most VRP models, an open chain structure is used to describe the dynamic delivery path of AGVs. In order to deal with the impact of uncertain meal preparation time on route planning, a stochastic programming model is formulated with the purpose of minimizing the expected order timeout rate and the total customer waiting time. In addition, an effective path merging strategy and after-effects strategy are also considered in the model. In order to solve the proposed mathematical programming model, a multi-objective optimization algorithm based on a NSGA-III framework is developed. Finally, a series of experimental results demonstrate the effectiveness and superiority of the proposed model and algorithm. Full article

The reduction in the blood supply following the 2019 coronavirus pandemic has been exacerbated by the increased use of balanced resuscitation with blood components including whole blood in urban trauma centers. This reduction of the blood supply has diminished the ability of blood banks to maintain a constant supply to meet the demands associated with periodic surges of urban trauma resuscitation. This scarcity has highlighted the need for increased vigilance through blood product stewardship, particularly among severely bleeding trauma patients (SBTPs). This stewardship can be enhanced by the identification of reliable clinical and laboratory parameters which accurately indicate when massive transfusion is futile. Consequently, there has been a recent attempt to develop scoring systems in the prehospital and emergency department settings which include clinical, laboratory, and physiologic parameters and blood products per hour transfused as predictors of futile resuscitation. Defining futility in SBTPs, however, remains unclear, and there is only nascent literature which defines those criteria which reliably predict futility in SBTPs. The purpose of this review is to provide a focused examination of the literature in order to define reliable parameters of futility in SBTPs. The knowledge of these reliable parameters of futility may help define a foundation for drawing conclusions which will provide a clear roadmap for traumatologists when confronted with SBTPs who are candidates for the declaration of futility. Therefore, we systematically reviewed the literature regarding the definition of futile resuscitation for patients with trauma-induced hemorrhagic shock, and we propose a concise roadmap for clinicians to help them use well-defined clinical, laboratory, and viscoelastic parameters which can define futility. Full article

This review explores the concept of futility timeouts and the use of traumatic brain injury (TBI) as an independent predictor of the futility of resuscitation efforts in severely bleeding trauma patients. The national blood supply shortage has been exacerbated by the lingering influence of the COVID-19 pandemic on the number of blood donors available, as well as by the adoption of balanced hemostatic resuscitation protocols (such as the increasing use of 1:1:1 packed red blood cells, plasma, and platelets) with and without early whole blood resuscitation. This has underscored the urgent need for reliable predictors of futile resuscitation (FR). As a result, clinical, radiologic, and laboratory bedside markers have emerged which can accurately predict FR in patients with severe trauma-induced hemorrhage, such as the Suspension of Transfusion and Other Procedures (STOP) criteria. However, the STOP criteria do not include markers for TBI severity or transfusion cut points despite these patients requiring large quantities of blood components in the STOP criteria validation cohort. Yet, guidelines for neuroprognosticating patients with TBI can require up to 72 h, which makes them less useful in the minutes and hours following initial presentation. We examine the impact of TBI on bleeding trauma patients, with a focus on those with coagulopathies associated with TBI. This review categorizes TBI into isolated TBI (iTBI), hemorrhagic isolated TBI (hiTBI), and polytraumatic TBI (ptTBI). Through an analysis of bedside parameters (such as the proposed STOP criteria), coagulation assays, markers for TBI severity, and transfusion cut points as markers of futilty, we suggest amendments to current guidelines and the development of more precise algorithms that incorporate prognostic indicators of severe TBI as an independent parameter for the early prediction of FR so as to optimize blood product allocation. Full article

Current trends in network traffic management rely on the efficient control of individual flows. Software-defined networking popularized this notion. Per-flow management is perfectly viable in standard IP networks, in which packet processing is in the electric domain. However, optical networks provide more restrictions and constraints making per-flow traffic management difficult. One of the most important challenges is to reduce the concurrent number of flows present in the flow tables to make the switching process quicker. In this paper, we propose a mechanism to manage flow timeout values that uses idle timeout and hard timeout parameters. To calculate the appropriate values of the parameters, the mechanism analyzes the packet inter-arrival times. The algorithm also takes into account the current occupancy of the flow table. Full article

Endoscopy-related musculoskeletal injuries (ERIs) are frequent among gastrointestinal, pulmonary, nasal, and urologic endoscopists, impacting the healthcare system. The present review aims to compare the ERI rates, risk factors, and ergonomic recommendations in the different endoscopic fields. A review was conducted using PubMed and Cochrane Library for articles based on surveys and published until 10 January 2024. Demographic, work, and ERI data from 46 publications were included, covering 10,539 responders. The ERI incidence ranged between 14% and 97%, highlighting the need of intervention independent of the specialties. The neck, back, and shoulder were the most frequent ERI locations, while gender, age, years of experience, and procedure volume the most common risk factors. Ergonomic recommendations suggest concentrating on endoscope design changes, especially in gastrointestinal endoscopy, to increase the comfort, adaptability of the equipment in the operating room, and workflow/institutional policy changes. The inclusion of an ergonomic timeout guarantees the correct equipment positioning, the neutralisation of the endoscopist’s posture, and an indirect break between procedures. Ergonomic training to increase awareness and best practice should be promoted, also using new technologies. Future research should concentrate on intervention and comparative studies to evaluate to which extent prevention measures and newly designed equipment could reduce ERI incidence. Full article

Consensus protocols, as crucial components of blockchain technology, play a vital role in ensuring data consistency among distributed nodes. However, the existing voting-based and proof-based consensus protocols encounter scalability issues within the blockchain system. Moreover, most consensus protocols are serialized, which further limits their scalability potential. To address this limitation, parallelization methods have been employed in both types of consensus protocols. Surprisingly, however, novel fusion consensus protocols demonstrate superior scalability compared with these two types but lack the utilization of parallelization techniques. In this paper, we present PnV, an efficient parallel fusion protocol integrating proof-based and voting-based consensus features. It enhances the data structure, consensus process, transaction allocation, and timeout handling mechanisms to enable concurrent block generation by multiple nodes within a consensus round. Experimental results demonstrate that PnV exhibits superior efficiency, excellent scalability, and acceptable delay compared with Proof of Vote (PoV) and BFT-SMART. Moreover, at the system level, the performance of the PnV-based blockchain system optimally surpasses that of the FISCO BCOS platform. Our proposed protocol contributes to advancing blockchain technology by providing a more efficient and practical solution for achieving decentralized consensus in distributed systems. Full article