Access Protocol Research Articles

Systematic Review of Nevus Counting and Reporting Methodologies in Contemporary Studies of the General Population

Introduction: Having many melanocytic nevi on the skin is a risk factor for melanoma. However, the reproducibility of nevus counts in previous studies is limited due to high inter- and intraobserver variation. Despite the introduction of a protocol for counting and reporting of nevi in 1990 by the International Agency for Research on Cancer (IARC), significant variations in nevus counting methods persist across studies. Objectives: We sought to review the variations in nevus counting and reporting methods, adherence and deviations from the IARC protocol, and the reproducibility of nevus counting studies. Methods: A systematic search of Embase, PubMed and Web of Science was conducted. The review was limited to nevus (>2 mm) counting studies of general population adults conducted between 2000 and 2022, and studies using skilled examiners. Results: Out of the 8 studies which were eligible for inclusion, none followed the IARC protocol. Three studies used a predefined criterion to count nevi. Five studies provided training for their observers. Three studies assessed the inter- or intraobserver variation using the correlation coefficient (>0.75), and 3 studies attempted to verify the validity and the reproducibility of the counts. There was little to no agreement in nevus counting and reporting procedures in the reviewed studies, and most studies did not report their procedures adequately. Conclusion: This review highlights the need for an easily accessible and feasible protocol for identification, counting and reporting of nevi, which also considers nevus counting from total-body imaging and automated nevus counts since these technologies are expected to become widely available for future studies.

Perirhinal cortex to the nucleus accumbens circuit in novelty salience following methamphetamine self-administration

Methamphetamine (meth) use disorder is part of an overarching use disorder that encompasses continued drug seeking and an increased risk of returning to drug use following periods of abstaining. Chronic meth use results in drug-induced cortical plasticity in the perirhinal cortex (PRC) that mediates responses to novelty. PRH projection targets are numerous and include the nucleus accumbens core (NAc). Whereas the PRH-prefrontal cortex is involved in object recognition; we propose that the PRHNAc is involved in novelty salience. Rats underwent short-access (ShA, 1 hr) or long-access (LgA, 6 hr) meth self-administration (SA). We then used a dual viral strategy to inhibit or activate PRHNAc during a novel cue test in which rats were presented with meth‑associated and novel levers. Response patterns on these levers differ depending on the meth access protocol: ShA meth SA results in equal responding on both novel- and meth‑associated levers, whereas LgA meth results in perseverative responding on the meth‑associated lever. Inactivation of the PRHNAc increased responding on the meth lever relative to the novel lever, resulting in a LgA behavioral phenotype. In contrast, activation in LgA rats was without a behavioral effect. We also report that male LgA sucrose SA animals perseverated on the novel lever rather than the meth‑associated lever, which contrast their meth SA counter parts and female specific patterns of behavior. These data open a new line of interest in the role of the PRHNAc circuit in novelty salience through identification of the behavioral relevance of this circuit.

A new methodology for evaluating the neighbor discovery time in schedule-based asynchronous duty-cycling wireless sensor networks

Duty cycling is a fundamental mechanism for battery-operated wireless networks, such as wireless sensor networks. Due to its importance, it is an integral part of several Medium Access Protocols and related wireless technologies. In Schedule-based Asynchronous Duty Cycle, nodes activate and deactivate their radio interfaces according to a pre-designed schedule of slots, which guarantees overlapping uptime between two neighbors, independent of the offset between their internal clocks, making communication between them possible. This paper presents a new methodology for evaluating the Neighbor Discovery Time (NDT) of Schedule-based Asynchronous Duty Cycle. Differently from previous methodologies, it accounts for the possibility of the slots in the schedules of the two neighbors not being perfectly border-aligned — an unrealistic assumption in practice. By means of simulation, we show that not taking this under consideration can lead to an overestimate of the NDT by a factor of 2 depending on the particular scenario, thus justifying the importance of our work.•We propose a new subslot-based methodology for computing the NDT of a wakeup schedule used for asynchronous duty cycling.•It replaces the traditional slot-based methodology, by dividing slots into subslots, allowing for the analysis of non-integer clock offsets between nodes, and further allowing mathematical models to consider the more realistic continuous-time case.•Our validation data shows that the slot-based methodology may overestimate NDT by a factor of up to 2, making the proposed subslot-based methodology much more precise.

Empirical Analysis of Widely Used Website Automated Testing Tools

In today's software development, achieving product quality while minimising cost and time is critical. Automated testing is crucial to attaining these goals by lowering inspection efforts and discovering faults more effectively. This paper compares widely used automated testing tools, such as Selenium, Appium, Java Unit (JUnit), Test Next Generation (TestNG), Jenkins, Cucumber, LoadRunner, Katalon Studio, Simple Object Access Protocol User Interface (SoapUI), and TestComplete, based on functionality, ease of use, platform compatibility, and integration capabilities. Our findings show that no single tool is inherently superior, with each excelling in certain areas such as online, mobile, Application Programming Interface (API), or performance testing. While Selenium and Appium are the dominant online and mobile testing frameworks, TestComplete and Katalon Studio offer complete, user-friendly cross-platform testing solutions. Despite the benefits of automation, obstacles such as tool maintenance, scalability, and cost issues remain. The report finishes with advice for picking the best tool for the project and offers potential approaches for enhancing testing frameworks, such as AI-driven optimisation, cloud-based testing, and greater Continuous Integration/ Continuous Deployment (CI/CD) integration. This study offers useful information for developers and testers looking to optimise their testing methods and increase software quality.

Sound and Partially-Complete Static Analysis of Data-Races in GPU Programs

GPUs are progressively being integrated into modern society, playing a pivotal role in Artificial Intelligence and High-Performance Computing. Programmers need a deep understanding of the GPU programming model to avoid subtle data-races in their codes. Static verification that is sound and incomplete can guarantee data-race freedom, but the alarms it raises may be spurious and need to be validated. In this paper, we establish a True Positive Theorem for a static data-race detector for GPU programs, i.e., a result that identifies a class of programs for which our technique only raises true alarms. Our work builds on the formalism of memory access protocols, that models the concurrency operations of CUDA programs. The crux of our approach is an approximation analysis that can correctly identify true alarms, and pinpoint the conditions that make an alarm imprecise. Our approximation analysis detects when the reported locations are reachable (control independence, or CI), and when the reported locations are precise (data independence, or DI), as well identify inexact values in an alarm. In addition to a True Positive result for programs that are CI and DI, we establish the root causes of spurious alarms depending on whether CI or DI are present. We apply our theory to introduce FaialAA, the first sound and partially complete data-race detector. We evaluate FaialAA in three experiments. First, in a comparative study with the state-of-the-art tools, we show that FaialAA confirms more DRF programs than others while emitting 1.9× fewer potential alarms. Importantly, the approximation analysis of FaialAA detects 10 undocumented data-races. Second, in an experiment studying 6 commits of data-race fixes in open source projects OpenMM and Nvidia’s MegaTron, FaialAA confirmed the buggy and fixed versions of 5 commits, while others were only able to confirm 2. Third, we show that 59.5% of 2,770 programs are CI and DI, quantifying when the approximation analysis of FaialAA is complete. This paper is accompanied by the mechanized proofs of the theoretical results presented therein and a tool (FaialAA) implementing of our theory.

9179 Type 2 Diabetes Alters Metabolic Fuel Selection During Intermittent Fasting

Abstract Disclosure: M.O. Conn: None. D.M. Marko: None. J.D. Schertzer: None. Type 2 Diabetes Alters Metabolic Fuel Selection During Intermittent Fasting Diabetes is characterized by elevated blood glucose resulting from defective insulin secretion and/or insulin resistance. Intermittent fasting, a popular weight loss strategy involving periodic reduction of caloric intake, can improve glycemia. Fasting shifts metabolism from carbohydrates to free fatty acids and ketones. However, high blood insulin can inhibit lipolysis and alter metabolic substrate selection in prediabetes, resulting in muscle catabolism to maintain energy homeostasis. Clinical studies have observed a significant decrease in muscle mass in subjects with obesity and diabetes. Our research aims to characterize lean mass versus fat loss after intermittent fasting in a mouse model of obesity and type 2 diabetes (T2D) and investigate the role of muscle alanine catabolism. We hypothesized that intermittent fasting would promote less lipolysis and more muscle alanine catabolism, causing more muscle loss in diabetic mice than controls. We compared male db/db mice manifesting obesity, hyperglycemia, and hyperinsulinemia to age-matched db/+ (control) mice. Our lab established a 5:2 repeated fasting protocol of ad-libitum access to food for 5 days a week and 2 days of fasting on non-consecutive days. Blood glucose was monitored weekly in fed and fasted states to assess glycemic control. While intermittent fasting lowered fasted blood glucose in both groups, no significant body weight or metabolic tissue mass changes were observed. Metabolic cage data demonstrated increased reliance on fat-based substrates for energy in control mice that underwent intermittent fasting during feeding and fasting periods. Diabetic mice did not show significant changes in the fasted state, but intermittent fasting led to increased reliance on carbohydrate oxidation during re-feeding periods, indicating impaired metabolic flexibility. After 10 weeks, the mice were sacrificed, and metabolic tissue histology (adipose, liver, skeletal muscle) will be performed. We will also analyze serum markers (alanine, fatty acids, glycerol, glucose, insulin) and the activity of the metabolic enzyme alanine transaminase (ALT) in the muscle and liver. This experiment will improve our understanding of how lipolysis and protein breakdown in muscle regulate lean mass versus fat mass loss in obesity and T2D, leading to more effective tailoring of fasting to specific populations. Presentation: 6/3/2024

Impact of China’s Accession Protocol on its Participation in the Dispute Settlement Mechanism (DSM): An Analysis of Eleven Protocol-related Cases

Impact of China’s Accession Protocol on its Participation in the Dispute Settlement Mechanism (DSM): An Analysis of Eleven Protocol-related Cases

Hybrid vehicular access protocol and message prioritization for real-time safety messaging

Real-time safety services rely on the exchange of messages to enhance the operations of connected and automated vehicles (CAVs). These safety messages convey vital information about traffic conditions, enabling drivers to take necessary measures to prevent accidents. The timely and reliable delivery of these messages is essential, necessitating efficient channel access. Vehicular Deterministic Access (VDA) is employed as a channel access scheme with distinct priorities and stringent timing guidelines, particularly for urgent safety warnings. In this paper, we propose a hybrid approach that combines VDA and Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) protocols, along with a message prioritization algorithm, to ensure efficient and reliable communication of safety messages in vehicular networks. Our approach leverages the strengths of both VDA and CSMA/CA to avoid message collisions; VDA is more efficient under high traffic loads, while CSMA/CA is better suited for low traffic loads. Additionally, the incorporation of the message prioritization algorithm ensures strict deadline guarantees for high-priority messages, such as Decentralized Environmental Notification Messages (DENMs). We evaluate our proposed solution using the Artery simulation framework. Our results show over a 93% delivery rate for DENM exchanges while maintaining low collision probability across various traffic loads. This research provides practical guidance for the development of efficient and reliable communication systems for CAVs. It also offers a detailed analysis of the trade-offs among different access protocols and message prioritization strategies in vehicular networks.

IEC104 protocol-based substation data upload IoT cloud platform implementation

Abstract The Industrial Internet of Things (IoT) has been developing rapidly under the background of Internet technology, and the most crucial part of its realization is the unified collection and access of heterogeneous data from multiple sources across networks and regions. For the access of substation system data, this paper designs a scheme to read data from IEC 60870-5-104 protocol and upload the data to IOT cloud platform by converting the data to data format supported by Kafka protocol, solving the problem of incompatibility between communication protocols, obtaining data from 104 secondary stations by connecting to them, parsing and processing the data in different formats, and converting the data to JSON format by processing and sending it to the IOT cloud platform. The data is converted into JSON format through processing and sent to the Kafka server, and the cloud platform obtains its data by subscribing to the corresponding topics. This approach makes substation data access more convenient, and efficiently and effectively saves the cost of hardware gateway, solves the incompatibility and interoperability between the underlying equipment access protocol and the cloud platform communication protocol, and builds a bridge for the remote transmission of the underlying equipment data of the Industrial Internet of Things.

Performance Analysis of Antenna-relay Selection in CNOMA Systems under Practical Impairments

Selection strategies prove to be a valuable approach in mitigating complexity associated with antenna selection (AS) and relay selection (RS), optimizing signal transmission through a streamlined number of antennas/relays, and enhancing overall system performance. This paper offers a comprehensive analysis, deriving closed-form expressions for the outage probability (OP) and throughput in proposed scenarios that leverage the best relay selection (BRS) and transmit antenna selection (TAS) protocol for cooperative non-orthogonal multiple access (CNOMA), along with partial relay selection (PRS) and TAS protocol for CNOMA. The study extends to Rayleigh fading channels, considering practical impairments such as successful interference cancellation (SIC) error, channel estimation error (CEE), and feedback delay error. In comparing the proposed system to conventional CNOMA, our findings highlight the substantial impact of SIC, CEE, and feedback delay imperfections on the performance of both proposed scenarios. Notably, the application of BRS-based TAS protocol outperforms PRS-based TAS in terms of OP and throughput. The close alignment between analytical, asymptotic, and simulation results attests to the credibility of conducted analysis.

Making the case for local strategic coordination? An investigation of fair access protocols and their role in the reintegration of pupils from alternative provision to mainstream school

ABSTRACT Fair access protocols (FAPs) are intended to ensure all schools in a local authority (LA) area take collective responsibility for ensuring pupils struggling to access an in-year school place are quickly admitted to a school. Every LA must have a FAP which, once agreed, can be used to direct schools to admit pupils. This is somewhat against the fragmentation of local education systems seen in the academies agenda. This paper considers the role of FAPs in facilitating inclusive local education systems by exploring the reintegration of students from alternative provision (AP) to mainstream school. The data on which this paper draws were collected as part of an England-wide research project which drew on nationally published datasets, administrative data from freedom of information (FOI) requests, and survey data from 64 professionals working in AP. The extent of FAP use varies widely as do rates of reintegration. Likewise, there is both evidence suggesting that FAPs can play a significant role in facilitating strategic coordination, and that they have limited power/influence to ensure reintegration. These findings suggest that achieving inclusive local practice requires a shift towards an underlying logic of cooperation in the education system.

Advancements in Pan-Canadian Data Access and Analysis Facilitation: Insights from Collaborative Health Research supported in Alberta, British Columbia, and Ontario

ObjectiveTo highlight progress in facilitating and supporting pan-Canadian data analysis research that is supported by a central coordinating center. This process will be illustrated with the use of a recently completed project that has been supported using data from Alberta, British Columbia, and Ontario. ApproachThe project represents a significant endeavor within the central coordinating center, as it necessitates coordination for data access, data importation and analytical support across three provinces. The focus will be on the administrative processes refined to support collaborative research endeavors. While specific project details will remain undisclosed, procedural enhancements within the central coordinating center framework will be highlighted. Key discussion points include standardized protocols for data access, collaborative efforts to streamline data importation, and facilitation of analytical support across jurisdictions. The type of cross-jurisdictional analytic support will as well be highlighted; data variables harmonization and sharing of data algorithms cohorts across the participating provincial data centers in support of the meta-analysis. ResultsThe successful completion of the final data analysis underscores the effectiveness of a unified data access coordination center for researchers seeking multi-regional health data in Canada. By highlighting advancements enabled by the central coordinating center and provincial data centers, this submission aims to inform researchers about the current landscape of pan-Canadian research and foster opportunities for future collaboration. ImplicationsSharing insights and lessons from this project emphasizes the advancements facilitated by the central coordinating center and provincial data centers, informing researchers about the potential of pan-Canadian research, and encouraging future collaborative endeavors.

Dynamic clustering based on Minkowski similarity for web services aggregation

This research, introduces a new dynamic clustering method offering a new approach utilizing Minkowski Distance methods for calculating similarity of xml messages to effectively compress and aggregate them. The increase in Web services utilization has led to bottlenecks and congestion on network links with limited bandwidth. Furthermore, Simple Object Access Protocol (SOAP) is an eXtensible Markup Language (XML) based messaging system often utilized on the internet. It leads to interoperability by facilitating connection both users and their service providers across various platforms. The large amount and huge size of the SOAP messages being exchanged lead to congestion and bottlenecks. Aggregation tools for SOAP messages can effectively decrease the significant amount that traffic generated. This has shown a notable enhancement in performance. Enhancements can be made by using similarity methods. These techniques group together multiple SOAP messages that share a significant level of similarity. Present techniques utilizing grouping for aggregating XML messages have demonstrated efficiency and compression ratio limitations. Practically, the proposed model groups messages into clusters based on minimum distance, supporting Huffman (variable-length) and (fixed-length) encoding compressing for aggregating multiple compressed XML web messages into a single compact message. Generally, the suggested model’s performance has been evaluated through a comparison with K-Means, Principle Component Analysis (PCA) with K-Means, Hilbert, and fractal self-similarity clustering models. Minkowski distance clustering model has shown excellent performance, especially in all message sizes like small, medium, large, V.large. Technically, the model achieved superior average Compression Ratio and it has outperformed all other models.

Load-adaptive MAC protocol for frontier detection in Underwater Mobile Sensor Network

This work proposes a load-adaptive Medium Access Control (MAC) protocol for the frontier/boundary detection application of underwater phenomena using Underwater Mobile Sensor Network (UWMSN). A leader-follower architecture of a swarm of underwater vehicles is proposed here. Autonomous Underwater Vehicles (AUVs) traverse a random mobility pattern beneath one Autonomous Surface Vehicle (ASV) (leader) in the proposed network. ASV has to guide multiple-follower AUVs in the event of interest. The vehicular swarm aims to explore the frontiers in the event to build the map. Load-adaptive MAC protocol is therefore proposed and implemented in this hybrid multi-vehicular network to ensure seamless vehicular communications. The ASV has navigational capabilities to aid the AUVs in navigation and data collection. The proposed MAC protocol can adjust the dynamic mobility and load in the network. The protocol aims to provide dynamic Time Division Multiple Access (TDMA) slots for the AUVs wirelessly linked in the vicinity of the ASV. These slots are used for ranging/navigation and data transmission. Additional urgent data from any AUVs can be transmitted in open Carrier Sense Multiple Access (CSMA) protocol following the TDMA duration. Results have been generated by comparing protocols like CSMA, ALOHA, and TDMA with the proposed Load-Adaptive MAC protocol. The protocols have been compared to the throughput vs number of nodes and throughput vs simulation time. It has been observed that the proposed MAC can perform better than ALOHA and CSMA protocols. Nevertheless, it can produce comparable results for TDMA protocol while supporting the dynamic mobility and load in the network meantime supporting urgent data transmission for nodes in demand.

Disability inclusion in national surveys.

National surveys are important for understanding the disparities that disabled people experience across social determinants of health; however, limited research has examined the methods used to include disabled people in these surveys. This study reviewed nationally representative surveys administered by the Centers for Disease Control and Prevention (CDC) and the US Census Bureau that collected data in the past 5 years and sampled adults ≥18 years. Data from both publicly available online survey documents and a questionnaire emailed to survey administrators were used to determine whether surveys (1) oversampled disabled people, (2) had a data-accessibility protocol to support data collection, and (3) provided multiple data-collection modalities (eg, phone, paper). Of the 201 surveys identified, 30 met the inclusion criteria for the study. Of these 30 surveys, 1 oversampled disabled people, none had a data-collection accessibility protocol, and 21 provided multiple data-collection modalities. This study highlights barriers and opportunities to including disabled people in national surveys, which is essential for ensuring survey data are generalizable to the US population.

Utilising Health Technology Assessment to Develop Managed Access Protocols to Facilitate Drug Reimbursement in Ireland.

The Health Service Executive, responsible for operating the Irish health service, has introduced health technology management (HTM) initiatives to manage expenditure on medicines. One such approach is managed access protocols (MAPs) to support access to high-cost medicines, while providing oversight, governance and budgetary certainty to the payer. Herein we describe the development and operation of MAPs, using case studies of liraglutide (Saxenda®), dupilumab (Dupixent®) and calcitonin gene-related peptide monoclonal antibodies. A MAP imposes the eligibility criteria attached to reimbursement support of a medicine. Criteria applied include controls on prescribing authority, clinical diagnostic and severity criteria, previous lines of treatment, concomitant treatments, outcome data collection, and validations within the reimbursement claims system. The choice of criteria are specific to each medicine, dictated by the areas of uncertainty highlighted in the health technology assessment report, such as the place in treatment, population, duration of treatment, etc., the commercial arrangements reached with the marketing authorisation holder, and specific recommendations made by the decision maker. By December 2023, there were28 medicines reimbursed subject to a MAP in Ireland. Across the three case studies outlined, over 3000 patients were accessing novel treatments for chronic illnesses in September 2023. Managed access protocols can provide some cost certainty for the payer by aligning utilisation and expenditure with committed funds, while enabling access where unmet need is highest. Managed access protocols are now established in the drug reimbursement process in Ireland, meeting the needs of both payers, patients and industry, and are likely to remain a feature of the reimbursement landscape.

A privacy-aware authentication and usage-controlled access protocol for IIoT decentralized data marketplace

Data is ubiquitous, powerful and valuable today. With vast instalments of Industrial Internet-of-Things (IIoT) infrastructure, data is in abundance albeit sitting in organizational silos. Data Marketplaces have emerged to allow monetization of data by trading it with interested buyers. While centralized marketplaces are common, they are controlled by few and are non-transparent. Decentralized data marketplaces allow the democratization of rates, trading terms and fine control to participants. However, in such a marketplace, ensuring privacy and security is crucial. Existing data exchange schemes depend on a trusted third party for key management during authentication and rely on a ‘one-time-off’ approach to authorization. This paper proposes a user-empowered, privacy-aware, authentication and usage-controlled access protocol for IIoT data marketplace. The proposed protocol leverages the concept of Self-Sovereign Identity (SSI) and is based on the standards of Decentralized Identifier (DID) and Verifiable Credential (VC). DIDs empower buyers and give them complete control over their identities. The buyers authenticate and prove claims to access data securely using VC. The proposed protocol also implements a dynamic user-revocation policy. Usage-controlled based access provides secure ongoing authorization during data exchange. A detailed performance and security analysis is provided to show its feasibility.

Catching some air: a method to spatially quantify aerial triazole resistance in Aspergillus fumigatus.

Airborne triazole-resistant spores of the human fungal pathogen Aspergillus fumigatus are a significant human health problem as the agricultural use of triazoles has been selecting for cross-resistance to life-saving clinical triazoles. However, how to quantify exposure to airborne triazole-resistant spores remains unclear. Here, we describe a method for cost-effective wide-scale outdoor air sampling to measure both spore abundance as well as antifungal resistance fractions. We show that prolonged outdoor exposure of sticky seals placed in delta traps, when combined with a two-layered cultivation approach, can regionally yield sufficient colony-forming units (CFUs) for the quantitative assessment of aerial resistance levels at a spatial scale that was up to now unfeasible. When testing our method in a European pilot sampling 12 regions, we demonstrate that there are significant regional differences in airborne CFU numbers, and the triazole-resistant fraction of airborne spores is widespread and varies between 0 and 0.1 for itraconazole (∼4 mg/L) and voriconazole (∼2 mg/L). Our efficient and accessible air sampling protocol opens up extensive options for fine-scale spatial sampling and surveillance studies of airborne A. fumigatus.IMPORTANCEAspergillus fumigatus is an opportunistic fungal pathogen that humans and other animals are primarily exposed to through inhalation. Due to the limited availability of antifungals, resistance to the first choice class of antifungals, the triazoles, in A. fumigatus can make infections by this fungus untreatable and uncurable. Here, we describe and validate a method that allows for the quantification of airborne resistance fractions and quick genotyping of A. fumigatus TR-types. Our pilot study provides proof of concept of the suitability of the method for use by citizen-scientists for large-scale spatial air sampling. Spatial air sampling can open up extensive options for surveillance, health-risk assessment, and the study of landscape-level ecology of A. fumigatus, as well as investigating the environmental drivers of triazole resistance.

Multi-Disjoint Path opportunistic networks with Hidden Markov Chain modeling

Advancing the efficiency and reliability of wireless sensor networks is a paramount pursuit in modern networking research. In this context, we introduce a groundbreaking approach based on Hidden Markov Chain (HMC) modeling with opportunistic routing, harnessed by the Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) mechanism. Our innovative algorithm addresses key challenges in Wireless Body Area Networks, including delay, throughput, and bandwidth utilization. By strategically integrating the HMC model, which captures intricate state transitions and emission probabilities, our proposed method introduces a robust solution for optimizing node connections and routing decisions. This fusion of HMC and opportunistic routing capitalizes on the strengths of both paradigms, enhancing the network's ability to make intelligent decisions in dynamic scenarios. Through rigorous simulations, we showcase the algorithm's prowess in achieving efficient data transmission. The empirical evidence from these simulations underscores the algorithm's superiority when juxtaposed against state-of-the-art mechanisms such as Simple Multi-Packet Access (SMPA) and Priority-based Congestion-avoidance Routing Protocol (PCRP). Our algorithm not only outperforms existing solutions in terms of delay, throughput, and bandwidth utilization, but it also showcases its ability to adapt to varying network conditions, making it a versatile tool for diverse applications.

Resource Allocation for UAV-RIS-Assisted NOMA-Based URLLC Systems

This work focuses on maximizing the sum rate of ultra-reliable low-latency communication (URLLC) systems by leveraging unmanned aerial vehicle-mounted reconfigurable intelligent surface (UAV-RIS) to provide short packet services for users based on the non-orthogonal multiple access (NOMA) protocol. To optimize the sum rate of system, a joint optimization is performed with respect to the power allocation, UAV position, decoding order, and RIS phase shifts. As the original problem is a non-convex integer optimization problem, it is challenging to obtain the optimal solution. Therefore, approximate solutions are derived using successive convex approximation (SCA), slack variables, and penalty-based methods. The simulation results demonstrate the superiority of the proposed resource allocation algorithm compared with the benchmark algorithm with orthogonal multiple access (OMA) scheme. In addition, this work emphasizes the performance gap between the proposed communication system and the traditional Shannon communication system in terms of throughput and the performance capacity sacrificed to achieve lower latency.