Transmission Scheduling Research Articles

Dynamic multimedia transmission scheduling by unmanned aerial vehicle–mounted base stations for a vehicular ad hoc network

On highways, vehicle speed and topology changes are likely to cause transmission delays. In this study, a multimedia transmission system for highways is proposed; this system combines a next-generation cloud radio access network, which has a centralised architecture, with unmanned aerial vehicle (UAV)-mounted base stations (UAV-BSs), cellular network base stations, and roadside units. The deployment characteristics of the UAV-BSs are examined to improve the service of vehicular ad hoc networks and the quality of experience of users. A UAV location assignment algorithm and a transmission resource allocation algorithm for multiple bit rates, communication channels, and relay stations are proposed to reduce multimedia playback lag. We implemented a simulation programme to evaluate how the proposed algorithms outperformed other relevant methods. The simulation results indicate that the proposed algorithms achieve lower lag time than do existing demand- and transmission-based methods. The findings of this study have implications for the practical application of multimedia transmission decision support on highways.

A sane approach to the high volume of alert transmissions in remote monitoring- turning of clinically non-relevant alerts decreases substantially workload

Abstract Background Remote monitoring (RM) offers a safe and effective method of monitoring patients with cardiac implantable electronic devices (CIEDs). The downside of RM is the data deluge of various transmissions, the majority of which are non-actionable. It has been suggested that optimizing alert transmissions could partly overcome this problem. Purpose The purpose of this study is to evaluate how the workload in RM can be safely decreased by thoroughly assessing the clinical relevance of each alert and deactivating non-relevant alerts. Methods Data on the number of alerts, scheduled and patient-initiated transmissions, as well as the causes and actions initiated by the transmissions, were systematically collected from the year 2023, during which the approach of actively deactivating clinically non-relevant alerts was conducted (A sane approach, Figure 1). The trend of alert transmissions and the proportion of actionable scheduled transmissions are presented. Results Overall, during the study period, 8182 transmissions were generated from 3732 followed CIEDs. Of these, 2306 were alert transmissions, and the rate of alerts decreased by 56% during the follow-up, from 0.07 to 0.04 per device per month. Additionally, our data shows that new alerts that have not occurred in the previous six months occurred on average at a rate of 0.03 per CIED per month, and this trend remained unchanged during the follow-up. Of the 3335 scheduled transmissions, 11% (364) were actionable, and both the number and proportion of actionable scheduled transmissions remained unchanged during the follow-up period. Interestingly, no alerts were triggered from 1124 (70%) of all patients but 88 (2%) of all CIEDs generated 30% of all alerts. Conclusions In this study, we demonstrate that RM workload can be decreased by actively evaluating the clinical relevance of each alert transmission. Our approach, where non-relevant alerts are turned off, likely does not impair patient safety and thus this practise enhance the RM.

Assessing adherence to remote monitoring recommendations for cardiovascular implantable electronic devices: a retrospective analysis

Abstract Background The recently published Expert Consensus Statement on the Practical Management of Remote Device Clinic offers evidence-based recommendations for managing patients with cardiovascular implantable electronic devices (CIEDs). Purpose This study evaluates adherence to remote monitoring (RM) recommendations in current clinical practice using data from a RM database. Methods According to RM guidelines, patient connectivity should be maintained. If continuous connection is ensured, it is reasonable to schedule in-person visits every 24 months, with alert-based RM potentially replacing structured intermittent device follow-up. Data from 6553 CIED patients followed on the LATITUDE (Boston Scientific) remote network at 26 Italian centers between 2010 and 2023 were analyzed. Median RM duration was 40 months (25th-75th percentile: 23-67). Results Enrollment of patients at centers significantly increased over the observation period (Figure). As of the January 2024 data extraction, 4723 patients had transmitted data in the last 12 months. Among these, 639 (14%) were NOT MONITORED (i.e. interrupted connectivity), with no significant differences among CIED types (Pacemaker: 13%; ICD: 12%; CRT-P: 7%; CRT-D: 13%; S-ICD: 18%). Scheduled device transmissions occurred at least once every 3 months in 96% of patients. The volume of in-office device interrogations and remote transmissions is detailed in Figure. In 2023, among the 4084 MONITORED patients, 6600 in-office device interrogations were conducted, and 64296 remote transmissions were reviewed. Of these, 34267 (53%) were scheduled, 15091 (24%) were patient-initiated, and only 14938 (23%) were triggered by alerts. Conclusions In current clinical practice, RM adoption is increasing, alongside the volume of in-office and remote visits. Solutions must be implemented to ensure transmission continuity in a substantial percentage of patients. Additionally, there persists a significant reliance on frequent scheduled transmissions and in-office visits. Centers stand to gain from implementing the guideline-recommended alert-based RM strategy, reducing the considerable burden of nonactionable remote and in-office visits among patients with continuous connectivity.

Remote monitoring of cardiac implantable electronic devices using smart device interface versus radiofrequency-based interface: a systematic review

Abstract Background Guidelines recommended remote monitoring (RM) in managing patients with Cardiac Implantable Electronic Devices (CIED). In recent years, smart device (phone or tablet) monitoring-based RM (SM-RM) was introduced. SM-RM is a specifically developed application (app) which can be downloaded from app stores using smart devices. The app uses Bluetooth low-energy to communicate automatically and securely with the patient’s CIED. The app then uses a cellular or Wi-Fi internet connection to transfer the data securely to the manufacturer’s repository. Purpose This study aims to systematically review SM-RM versus bedside monitor RM (BM-RM) using radiofrequency in terms of compliance, connectivity, and episode transmission time. Methods We conducted a systematic review, searching three international databases from inception until July 2023 for studies comparing SM-RM (intervention group) versus BM-RM (control group). Results Two propensity score-matched studies with a total of 21978 patients were retrieved (9642 patients in the SM-RM arm and 12336 patients in the BM-RM arm) (1, 2). There is significantly higher compliance among patients using SM-RM compared with patients using BM-RM in both pacemaker and defibrillator patients. There were higher enrolment rates and completed scheduled transmissions among SM-RM compared to BM-RM. Higher connectivity was also seen in patients with SM-RM, and more SM-RM patients transmitted at least once compared to BM-RM patients. Additionally, SM-RM patients had more patient-initiated transmissions compared to BM-RM patients. Younger patients (aged <75) had more patient-initiated transmissions, and a higher proportion had ≥10 such transmissions compared with older patients (aged ≥75) in both SM-RM and BM-RM groups. The episode transmission time of SM-RM patients was also shorter than that of BM-RM patients. Conclusion SM-RM is a step in the right direction, with good compliance, connectivity, and shorter episode transmission time. It allows patients to feel empowered and in control of their health. Further research on cost-effectiveness and long-term clinical outcomes can be carried out in the future.

Insights from an international clinic survey on CIED patient management practices and perceptions

Abstract Background Remote monitoring (RM) is recommended as standard of care to manage patients with cardiac implantable electronic devices (CIEDs). However, implementation within overall follow-up (FU) practice is challenging with many organizational aspects to consider. While the 2023 HRS/EHRA/APHRS/LAHRS consensus on management of remote device clinics provided guidance, data on current patient management practice is lacking to understand existing gaps. Purpose This survey of device clinic staff characterized the state and perceptions of CIED patient management. Methods A Delphi panel of US and EU clinical experts guided the research objectives, structure, and content of the survey. Once consensus was reached, the online survey (Qualtrics) was deployed in partnership with HRS. An available case analysis was performed to handle missing data. Results A total of 471 responses were received between September 2023-January 2024 (66% US, 19% Europe, 15% other). Overall, performing a combination of in-office visits and RM was the most frequent FU practice for all devices. Remote-only management was only commonly reported for insertable cardiac monitors (ICM). Adoption of RM was lower in EU compared to US for therapeutic devices, especially pacemakers for which in-person only FU remained high (Figure 1). Frequency of routine visits and transmissions is reported in Figure 2. While the majority of respondents (48-67%, depending on device type) expressed that less than 20% routine visits are actionable, adopting a practice of FU visits scheduled every 2 years as suggested in the 2023 consensus was rarely reported for therapeutic devices. However, alert-based RM seems to emerge for ICM without routine FU. In the US, frequency of scheduled transmissions appeared aligned with reimbursement rules (monthly for ICMs; quarterly for therapeutic devices), whereas there was more variability in EU where RM often lacks clear funding. Divided opinion was observed regarding staff sufficiency as 43% found staffing levels somewhat/very sufficient, while 42% rated it as somewhat/very insufficient. Managing disconnected patients, initial transmission review, and patient phone calls were identified as most burdensome tasks and were the ones for which there was most willingness to outsource. Although 60% respondents rated their practice as somewhat/very efficient, the majority (45%) did not report monitoring performance. The minority (29%) assessing patient management performance primarily tracked workload volume rather than quality-related metrics. Conclusion This large international survey characterized contemporary CIED patient management practices. While the 2023 HRS/EHRA/APHRS/LAHRS consensus highlighted the potential for alert-based RM, reducing in-person visits, and third-party resources to streamline patient FU, these practices have yet to be fully implemented. As such, there is opportunity to standardize and optimize workflows to drive efficiency and quality of care.Follow-up paradigm by regionFrequency of routine follow-up

A Fair MAC Protocol Based on Dual Bandwidth Allocation Iterations in Underwater Acoustic Sensor Networks

ABSTRACTMost existing passive allocation‐based media access control (MAC) protocols for underwater acoustic sensor networks (UASNs) overlook the fairness issue in channel bandwidth allocation, resulting in certain nodes occupying channel resources for extended periods, thereby leading to low channel utilization. To address this issue, this paper proposes a fair MAC protocol based on dual bandwidth allocation iterations (FBA‐MAC). Firstly, by limiting the maximum number of packets and the maximum number of available time slots that the host node can receive in each communication cycle, the protocol reduces collisions and collisions more effectively, thus controlling the communication delay. Secondly, in the process of channel bandwidth allocation, a dual bandwidth allocation iterative method was used to allocate appropriate channel bandwidth for each member node according to its communication requirements and the generation time of its generated data packets. Finally, in order to minimize the time interval of each packet arriving at the host node to reduce the communication delay, the transmission scheduling scheme was adaptively adjusted by combining the results of channel bandwidth allocation to maximize the channel utilization. Simulation results indicate that compared to the other four MAC protocols, FBA‐MAC demonstrates significant advantages in terms of fairness (10% higher), achieving higher network throughput (10% higher) and shorter end‐to‐end delay. Therefore, FBA‐MAC exhibits superior adaptability and efficiency in dynamic network environments.

RIS-Assisted Transmission Scheduling for Train-to-Train Communication System

RIS-Assisted Transmission Scheduling for Train-to-Train Communication System

Multi-Objective Optimization of Orchestra Scheduler for Traffic-Aware Networks

The Internet of Things (IoT) presents immense opportunities for driving Industry 4.0 forward. However, in scenarios involving networked control automation, ensuring high reliability and predictable latency is vital for timely responses. To meet these demands, the contemporary wireless protocol time-slotted channel hopping (TSCH), also referred to as IEEE 802.15.4-2015, relies on precise transmission schedules to prevent collisions and achieve consistent end-to-end traffic flow. In the realm of diverse IoT applications, this study introduces a new traffic-aware autonomous multi-objective scheduling function called OPTIMAOrchestra. This function integrates slotframe and channel management, adapts to varying network sizes, supports mobility, and reduces collision risks. The effectiveness of two versions of OPTIMAOrchestra is extensively evaluated through multi-run experiments, each spanning up to 3600 s. It involves networks ranging from small-scale setups to large-scale deployments with 111 nodes. Homogeneous and heterogeneous network topologies are considered in static and mobile environments, where the nodes within a network send packets to the server with the same and different application packet intervals. The results demonstrate that OPTIMAOrchestra_ch4 achieves a current consumption of 0.72 mA while maintaining 100% reliability and 0.86 mA with a 100% packet delivery ratio in static networks. Both proposed Orchestra variants in mobile networks achieve 100% reliability, with current consumption recorded at 6.36 mA. Minimum latencies of 0.073 and 0.02 s are observed in static and mobile environments, respectively. On average, a collision rate of 5% is recorded for TSCH and RPL communication, with a minimum of 0% collision rate observed in the TSCH broadcast in mobile networks. Overall, the proposed OPTIMAOrchestra scheduler outperforms existing schedulers regarding network efficiency, time, and usability, significantly improving reliability while maintaining a balanced latency–energy trade-off.

Adaptive Clustering and Scheduling for UAV-Enabled Data Aggregation

Using unmanned aerial vehicles (UAVs) is an effective way to gather data from Internet of Things (IoT) devices. To reduce data gathering time and redundancy, thereby enabling the timely response of state-of-the-art systems, one can partition a network into clusters and perform aggregation within each cluster. Existing works solved the UAV trajectory planning problem, in which the energy consumption and/or flight time of the UAV is the minimization objective. The aggregation scheduling within each cluster was neglected, and they assumed that data must be ready when the UAV arrives at the cluster heads (CHs). This paper addresses the minimum time aggregation scheduling problem in duty-cycled networks with a single UAV. We propose an adaptive clustering method that takes into account the trajectory and speed of the UAV. The transmission schedule of IoT devices and the UAV departure times are jointly computed so that (1) the UAV flies continuously throughout the shortest path among the CHs to minimize the hovering time and energy consumption, and (2) data are aggregated at each CH right before the UAV arrival, to maximize the data freshness. Intensive simulation shows that the proposed scheme reduces up to 35% of the aggregation delay compared to other benchmarking methods.

Optimal Transmission Scheduling for Two-Hop Networks

Optimal Transmission Scheduling for Two-Hop Networks

Sensor Transmission Scheduling Over a Time-Varying Channel

Sensor Transmission Scheduling Over a Time-Varying Channel

A mission planning method for deep space detectors using deep reinforcement learning

Mission planning for deep space detectors is a pivotal step in the successful execution of detection missions. Traditional planning approaches, which typically compartmentalize mission planning and data transmission scheduling, exhibit limitations in adapting to uncertainties and are often inadequate in responding to unforeseen opportunity targets. This paper introduces a mission planning method for deep space detectors designed to address these challenges. Firstly, a Markov Decision Process (MDP) model is formulated, integrating mission planning and data transmission scheduling, with a consideration for planning balance between detection missions and opportunity targets. Subsequently, a Planning Balance with Proximal Policy Optimization (PB-PPO) algorithm is proposed. The proposed algorithm, based in the Proximal Policy Optimization (PPO) algorithm, integrates an orthogonal initialization algorithm to afford improved control over parameter updates. Furthermore, a dynamic learning rate strategy is implemented to accelerate convergence speed. Experimental results show that, the PB-PPO achieves rewards that are 4.42%, 6.78%, 18.32%, and 26.81% higher than those obtained by compared algorithms. Additionally, the PB-PPO demonstrates the capability to address the planning balance between detection missions and opportunity targets, ensuring stable reward growth even when planning a significant number of opportunity targets. In summary, the PB-PPO integrates of MDP, deep reinforcement learning, and innovative strategies to make it a robust solution for detector mission planning in the complex and dynamic environment of deep space.

Online Multi-User Scheduling for XR Transmissions With Hard-Latency Constraint: Performance Analysis and Practical Design

Online Multi-User Scheduling for XR Transmissions With Hard-Latency Constraint: Performance Analysis and Practical Design

Optimal Energy Transmission Scheduling in Event-Triggered Redundant Channel of Cyber-Physical Systems Against DoS Attacks

Optimal Energy Transmission Scheduling in Event-Triggered Redundant Channel of Cyber-Physical Systems Against DoS Attacks

Research on AFDX network configuration testing technology

The terminal system, as a key part of AFDX network data transmission, determines the communication performance of the entire AFDX network. In order to test the functionality of the verification end system and evaluate the transmission performance of the AFDX network, this article proposes an AFDX network configuration testing method. Firstly, the configuration testing specifications for the end system is designed, an overall framework for end system testing is established; the testing response mechanism of the end system is studied; the testing process is standardized; and generated configuration files are as input information for algorithm design in the following stage. Secondly, incentive data generation algorithms is designed, incentive data generation frameworks is established, the constraints for data transmission are formalized, and incentive data transmission schedules are generated using SMT solvers. Next, an AFDX network configuration testing tool is designed and implemented; the performance from the perspectives of operational stability and response time is evaluated to prove the effectiveness of the tool. Finally, the types and performance of the seven clock function modules in the overlay network configuration are tested, and the experimental results prove the effectiveness of the network configuration testing method.

Hybrid Transmission Scheduling Protocol for State Estimation Over a Constrained Channel

Hybrid Transmission Scheduling Protocol for State Estimation Over a Constrained Channel

Adherence to remote monitoring recommendations in current clinical practice: data from a remote monitoring database

Abstract Background The recently published Expert Consensus Statement on the Practical Management of Remote Device Clinic offers evidence-based recommendations for managing patients with cardiovascular implantable electronic devices (CIEDs). Purpose We examined data from a remote monitoring (RM) database to evaluate adherence to RM recommendations in current clinical practice. Methods According to RM guidelines, patients should be enrolled within 2 weeks of implantation for earlier detection of actionable events, and in any case, within 3 months, as it is associated with improved survival. Continuous connectivity should be maintained. In patients with continuous connectivity, alert-based RM may replace structured intermittent device follow-up. We analyzed data from 4427 CIED patients followed on the LATITUDE (Boston Scientific) remote network at 20 Italian centers. Patients were enrolled between 2010 and 2023, with a median RM duration of 37 months (25th-75th percentile: 21-60). Results The number of patients enrolled at the centers significantly increased during the observation period (Figure). In the overall RM population, we identified a group of patients (56%) enrolled after implantation (within 6 months) and a group of patients enrolled late during their follow-up. In the first group, RM receiver activation occurred within 2 weeks in 62% and within 3 months in 90% of patients. The second group consisted mainly of patients not yet in RM at the time of COVID-19 outbreak and included to allow RM of all patients at the centers. Overall, 96% of enrolled patients performed remote data transmissions during the observation period. As of the July 2023 data extraction, 1405 (33%) patients were not monitored, with no significant differences among CIED types (CRT-D: 37%; ICD: 32%; S-ICD: 32; Pacemaker: 30%). Most not-monitored patients (30%) had not transmitted data for over a year, likely due to patient death, CIED extraction, or other irreversible causes. For the remaining 3%, the recent loss of connection (occurring within a timeframe shorter than the scheduled transmission interval) should have prompted interventions to restore connection. Scheduled device transmissions occurred at least once every 3 months in 94% of patients. Considering individual device programming, the 2836 patients with consistent connectivity performed 25,281 scheduled transmissions in one year. Conclusions In current clinical practice, RM adoption is continually increasing, with generally observed adherence to post-implantation patient enrollment recommendations. However, a significant proportion of patients may activate RM earlier. Centers must implement solutions to ensure transmission continuity in a substantial percentage of patients. Nevertheless, the workload generated by this activity could be effectively balanced by adopting an alert-based RM strategy and reducing unnecessary scheduled transmissions.Enrolled patients trend

Enhanced Beacons Dynamic Transmission over TSCH

Time slotted channel hopping (TSCH) has become the standard multichannel MAC protocol for low-power lossy networks. The procedure for associating nodes in a TSCH-based network is not included in the standard and has been defined in the minimal 6TiSCH configuration. Faster network formation ensures that data packet transmission can start sooner. This paper proposes a dynamic beacon transmission schedule over the TSCH mechanism that achieves a shorter network formation time than the default minimum 6TiSCH static schedule. A theoretical model is derived for the proposed mechanism to estimate the expected time for a node to get associated with the network. Simulation results obtained with different network topologies and channel conditions show that the proposed mechanism reduces the average association time and average power consumption during network formation compared to the default minimal 6TiSCH configuration.

Transmission scheduling of P2P real-time communication based on restless multi-armed bandit

Transmission scheduling of P2P real-time communication based on restless multi-armed bandit

MANAGEMENT OF REMOTE MONITORING FOR IMPLANTABLE DEVICES CONTROLS: SINGLE CENTER EXPERIENCE

Abstract Background Nowadays the benefits of remote monitoring (RM)of cardiac implantable electronic devices (CIEDs) are Known: an improved both device surveillance and patient clinical management and a decrease in office follow up. So RM is used as supplement in clinic follow up for patients with CIED.However despite decades to RM utilization there are challenges in managing patients with RM including large number of trasmissions and lack of trained staff. There are many different model of care to RM management. Methods We describe our model of care to management CIED recipients with RM considering data collected from January 2021 to November 2023. Results Our model of care consists of 4 electrophysiologists Physicians and 4 Tecnicians. RM enrollment is performed at scheduled in office visit after ten days from hospital discharge after device implantation. implantable cardiac device(ICD)recipients with RM are annualy followed in office and biennal for pacemaker (PM) recipients and they send every three months transmissions. Trained tecnicians gives home monitor, take care of patients education and collected and screen transmissions. Tecnicians inform immediately physicians in case of urgent alert (shock or antitachicardia pacing therapy (ATP), sustained ventricular tachycardia(TV), ventricular fibrillation (Fv) indicator of elective replacement (ERI), lead releted alert or noise). Physician contact patients the same day (exept Saturday and Sunday). In addiction Physicians twice a week review less urgent and scheduled transmissions and call the patients by phone for visit in office for patients with low rate of biventricular pacing, detection of atrial fibrillation. We have 1000 patients with RM: 746 ICD recipients (103 Biotronik, 150 Abbott, 200 Boston scientific, 293 medtronic), 50 implantable cardiac monitor (ICM) recipients and 204 PM recipients. We analyze 12721 transmissions.Considering ICD recipient we detect 96 episode of ATP and 31 of shock. Shock of ICD was registered in 52 patients (6,9%)We received 1982 atrial fibrillation (AF) detection, with 35 for new detectable AF.The most of transmisisone were for low bIV pacing. We contacted these patients by phone about clinical status and in some case we called them in office. Conclusions Our model of care allows to control a large number of trasmissions with fast management of urgent alert trasmissions.