Priority Messages Research Articles

Abstract B040: Building a lung cancer awareness event

Abstract Introduction: Lung cancer is the top cancer killer in the United States. Lung cancer screening (LCS) can decrease mortality of lung cancer, but current uptake is low. Concentrated effort during lung cancer awareness month has potential to positively impact uptake. Patient engagement and education are meaningful ways for medical students to make an impact. Methodology: We created a lung cancer awareness event during November (Lung Cancer Awareness Month) that aims to educate and engage regarding lung cancer and LCS. Prior to event day: 1. We secured buy-in from LCS leadership at the hospital, nurse navigators of the LCS program, leaders of nonprofit organizations and lung cancer support group leadership. 2. We recruited medical students to assist with creating informational materials, promoting the event and staffing day-of. All students attended a 1-hour training session on priority messages regarding lung cancer and LCS, engaging people in surveys and connecting eligible patients with LCS. 3. Informational materials and promotional flyers were sent to the lung cancer screening leadership to ensure messaging was in-line with messaging by the hospital and nonprofit organizations. Day-of event prep: 4. Tables with lung cancer educational materials were placed at the hospital entrances where foot traffic was greatest and staffed by medical students, nurse navigators and representatives from the nonprofits and lung cancer support groups. Educational and engagement materials at the table included lung cancer informational pamphlets, smoking cessation pamphlets and surveys to determine LCS eligibility. 5. Each table had a lung cancer and LCS trivia wheel with small give away items to attract and engage people at the tables. Event: 6. Medical students greeted people who approached the table and explained the purpose of the event (e.g. increasing lung cancer and LCS awareness and education). High priority messages regarding lung cancer and LCS (e.g. lung cancer is the top cancer killer, LCS can lower risk of dying from lung cancer, many eligible patients may not be getting screened) was conveyed by the student to the participant. 7. Participants were invited to complete the survey to determine LCS eligibility. 8. Participants were invited to answer a trivia question to win a lung cancer awareness t-shirt prize. After event: 9. Eligible patients identified by event surveys were followed-up by the nurse navigators to connect to LCS. Results: This lung cancer awareness event was successful in engaging people with lung cancer and lung cancer screening education. 73 people were recorded to have stopped by the table; 58 completed the survey in full. This event is within the power of medical students to do and can be set up easily with buy-in from faculty, hospital staff and local nonprofits. Conclusion: A student-run lung cancer awareness event is a feasible and impactful method to quickly engage patients in lung cancer screening. This event model can be translatable to future years and potentially expanded to other institutions and centers. Citation Format: Michelle Gomez-Guevara, Kristine Chin, Anthony Smith Jr., Masashi Azuma, Grace X. Ma, Cherie P Erkmen. Building a lung cancer awareness event [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr B040.

PrioriNet

During disaster scenarios, effective communication systems are essential for coordinating emergency response efforts and ensuring the safety of affected individuals. However, existing communication protocols often face challenges in providing reliable and efficient communication in these highly dynamic and resource-constrained environments. To overcome these challenges a novel energy-efficient emergency priority protocol namely PrioriNet technique which specifically tailored for urban earthquake scenarios. The protocol focuses on prioritizing the transmission of emergency data packets to ensure their prompt and reliable delivery, while appropriately managing normal data packets. The PrioriNet prioritizes the emergency messages as high and low priority messages and allocate them to energy efficient nodes efficiently. The experimental results indicates that the suggested protocol performs better than the existing LEACH technique in terms of energy consumption, network coverage, packet delivery ratio, and throughput. In emergency data scenarios, the LEACH protocol demonstrates throughputs between 0.3 Mbps and 1.2 Mbps, whereas the proposed method consistently outperforms the LEACH protocol with throughputs ranging from 0.7 Mbps to 1.8 Mbps respectively.

DPB-MA: Low-Latency Message Authentication Scheme Based on Distributed Verification and Priority in Vehicular Ad Hoc Network

Vehicular ad hoc networks (VANETs) serve as crucial means to ensure safe transportation systems and enhance driving convenience. Ensuring authentication between vehicles and units is the most essential line of defense for VANETs systems. Various schemes of message authentication are put forward to realize safe communication in VANETs. However, these schemes mainly pay attention to privacy and security issues, and are not fit for high-density traffic environments where many messages should be verified by a roadside unit (RSU). At present, achieving the low-latency authentication under the security and privacy of messages remains a critical requirement and challenge. For addressing this problem, this study puts forward a novel low-latency message authentication scheme based on the distributed authentication and message priority (DPB-MA), which can minimize message verification latency through cooperation between the RSU and cooperative vehicles (CVs). In addition, a message priority strategy has been designed to ensure that urgent messages are preferentially verified. According to the security proof with tight reduction, the DPB-MA is existentially unforgeable against adaptive chosen message attack (EU-CMA) in the random oracle model (ROM). Furthermore, our DPB-MA achieves full message aggregation, which also greatly optimizes the communication overhead and authentication efficiency. Performance analysis indicates that our scheme works well in high-density traffic scenarios and is more suitable for securing emergency messages with ultra-low latency requirements.

Robust Deep Reinforcement Learning Scheduling via Weight Anchoring

Questions remain on the robustness of data-driven learning methods when crossing the gap from simulation to reality. We utilize weight anchoring, a method known from continual learning, to cultivate and fixate desired behavior in Neural Networks. Weight anchoring may be used to find a solution to a learning problem that is nearby the solution of another learning problem. Thereby, learning can be carried out in optimal environments without neglecting or unlearning desired behavior. We demonstrate this approach on the example of learning mixed QoS-efficient discrete resource scheduling with infrequent priority messages. Results show that this method provides performance comparable to the state of the art of augmenting a simulation environment, alongside significantly increased robustness and steerability.

Message priority MaxDelivery algorithm applied in earthquake communication situation

The study of Delay Tolerant Networks (DTNs) has considerably grown in recent years as communication contexts have emerged with needs that go beyond what the Internet could offer. For example, in case of a natural disaster that damages the classic communication network, a delay tolerant network can be implemented ad hoc, to face the challenges imposed by this context. The delay tolerant network is special because there are no permanent end-to-end path between nodes and links characteristics are time-varying. This paper aims to test the performance of the DTN MaxDelivery algorithm in establishing an efficient communication in the context of a post-earthquake situation, that affected the classical communication network. The goal of the algorithm is to maximize the number of high priority messages that manage to reach their destination. A series of simulations are presented to verify the optimal parameters that the network must comply with in order to maximize the message transfer rate.

Effective communication for message prioritization in DTN for disaster scenarios

When disaster strikes, effective communication is crucial for emergency responses and accessing a victim’s location. Using smartphone-based Delay Tolerant Networks (DTNs) is the prevalent proposed approach to work around network disruptions. One of the challenges in these networks is high-traffic congestion since buffer limitation produces messages that get dropped before they are delivered. This article presents a congestion control strategy using message prioritization for DTNs to increase network resilience facing high message congestion. We measure congestion by considering the free space in the buffer of the nodes involved in the routing or by counting the messages deleted from the buffer in a fixed period to improve the availability and immediacy of information for disaster scenarios. We evaluated the proposed strategies using The ONE simulator to test different mobility models and communication protocols. Results show that the strategy improved delivery rate, buffer usage, eliminated messages, overhead, and latency for the highest priority messages. The best results were obtained in terms of latency, which fits our disaster scenario since timely information is vital. The trade-offs are a slightly lower average delivery rate and a decrease in the lowest priority message delivery rate.

A probabilistic routing algorithm based on node communication capability and message strength

SummaryIn delay‐tolerant networks (DTN), node connection time and message transmission time are two important influencing factors that can improve the delivery rate. In this paper, we first define a new concept called communication capability (CC) and then apply this concept to the delivery predictability formulation in Prophet and improve it. Then, in Prophet, the selection of relay nodes relies only on the delivery predictability and ignores the caching and forwarding capability of the node. Therefore, we combine delivery predictability, buffering, and forwarding capability to develop a new adaptive relay node selection strategy. Subsequently, we define two metrics called message priority (MP) and message strength (MS). The node forwards messages sequentially based on message priority and discards messages based on message strength. Finally, we present a probabilistic routing algorithm based on node communication capability and message strength (CAMS). The simulation results show that compared with traditional routing algorithms, the CAMS can effectively improve the message delivery rate, reduce the overhead ratio, and keep average hop counts low.

Information Freshness for Vehicles Communications of Safety-critical Vulnerable Road Users

Information freshness is an indicator of the timing of a status update which is of utmost significance for many real-time applications, such as connected vehicles, autonomous vehicles, and sensor networks. The age of information (AoI) metric is useful for quantifying the information freshness for messages delivered to the entities concerned. In this paper, we averaged the peak AoI (PAoI) over time for each vulnerable road user (VRU) in the network with a proposed algorithm namely, priority-based push-out last-generated first-served (PPLGFS) strategy, for safety-critical usage cases to address the issue of maintaining timely VRU status updates across all nearby connected vehicles. A multi-VRU system that supports the cellular network is assumed in which status updates arrive and should be transmitted over the network to the intended vehicle. We model the worst-case information freshness (i.e., PAoI) for VRU-destination vehicle links, using a queuing model with the proposed algorithm to manage the packets on arrival. It gives priority messages which have arrived recently, and blocks stale packets to avoid wasting network resources for the transmission of old information. Results show that the proposed algorithm used with PAoI gradually achieves a better performance than other queuing models as the packets arrival rate increases. Besides, it also enhances the maintenance of timely VRU status updates in the intended vehicle.

Identifying opportunities for strengthening advice to enhance vegetable liking in the early years of life: qualitative consensus and triangulation methods.

To prioritise and refine a set of evidence-informed statements into advice messages to promote vegetable liking in early childhood, and to determine applicability for dissemination of advice to relevant audiences. A nominal group technique (NGT) workshop and a Delphi survey were conducted to prioritise and achieve consensus (≥70 % agreement) on thirty evidence-informed maternal (perinatal and lactation stage), infant (complementary feeding stage) and early years (family diet stage) vegetable-related advice messages. Messages were validated via triangulation analysis against the strength of evidence from an Umbrella review of strategies to increase children's vegetable liking, and gaps in advice from a Desktop review of vegetable feeding advice. Australia. A purposeful sample of key stakeholders (NGT workshop, n 8 experts; Delphi survey, n 23 end users). Participant consensus identified the most highly ranked priority messages associated with the strategies of: 'in-utero exposure' (perinatal and lactation, n 56 points) and 'vegetable variety' (complementary feeding, n 97 points; family diet, n 139 points). Triangulation revealed two strategies ('repeated exposure' and 'variety') and their associated advice messages suitable for policy and practice, twelve for research and four for food industry. Supported by national and state feeding guideline documents and resources, the advice messages relating to 'repeated exposure' and 'variety' to increase vegetable liking can be communicated to families and caregivers by healthcare practitioners. The food industry provides a vehicle for advice promotion and product development. Further research, where stronger evidence is needed, could further inform strategies for policy and practice, and food industry application.

A Distributed Congestion Control Strategy Using Harmonic Search Algorithm in Internet of Vehicles

Aiming at the diversified requirements of network application QoS (Quality of Service) in the terminal equipment of Internet of Vehicles, this paper proposes a distributed congestion control strategy based on harmony search algorithm and the Throughput Evaluation Priority Adjustment Model (TEPAM) to ensure real-time transmission of high-priority data messages related to security applications. Firstly, the channel usage rate is periodically detected and the congestion is judged; then, in order to minimize delay and delay jitter as the goal, harmony search algorithm is utilized to perform global search to obtain a better solution for the transmission range and transmission rate. Secondly, packet priority and the TEPAM are applied to indicate the sending right of each packet. The data message priority and throughput percentage factor are used to express the transmission weight of each data message. Besides, the real-time evaluation of path state in MPTCP is carried out by the batch estimation theory model, which realizes the on-demand dynamic adjustment of the network congestion time window. Finally, SUMO, MOVE, and NS2 tools are used to create a VANET-like environment to evaluate the performance of the proposed congestion control strategy. Experimental results show that the proposed method is superior to other three methods in the four indicators of average delay time, average transmission rate, number of retransmissions, and packet loss rate compared with other advanced methods.

ASSESSMENT OF THE PERFORMANCE OF A BUFFER MANAGEMENT SYSTEM TO IMPROVE HIGH PRIORITY MESSAGE DELIVERY TIME LIMIT

In vehicular delay-tolerant networks, buffer management systems are developed to improve overall performance. However, these buffer memory management systems cannot simultaneously reduce network overload, reduce high priority message delivery time limit, and improve all priority class message delivery rates. As a result, quality of service is not guaranteed. In this paper, we propose a drop policy based on the constitution of two queues according to message weight, the position of the node in relation to the destination and the comparison of the oldness between the high-priority message and the messages in the low-priority queue. The results of the simulations show that compared to the existing buffer management policy based on time-to-live and priority, our strategy simultaneously reduces network overload, reduces the delivery time limit of high-priority messages and allows for an increase in the delivery rate of messages regardless of their priority.

DEFENSE STRATEGY AGAINST SELFISH NODES TAKING INTO ACCOUNT TRAFFIC DIFFERENTIATION IN VEHICULAR DELAY-TOLERANT NETWORKS

Vehicular Delay-Tolerant Networks (VDTNs) are vehicle networks where there is no end-to-end connectivity between source and destination. As a result, VDTNs rely on cooperation between the different nodes to improve its performance. However, the presence of selfish nodes that refuse to participate in the routing protocol causes a deterioration of the overall performance of these networks. In order to reduce the impact of these selfish nodes, proposed strategies, on the one hand, use the nodes transmission rate that does not take into account the message priority class of service, and on the other hand, are based on traditional buffer management systems (FIFO, Random). As a result, quality of service is not guaranteed in this type of network where different applications are derived from messages with different priorities. In this paper, we propose a strategy for detecting selfish nodes and taking action against them in relation to priority classes in order to reduce their impacts. The operation of this strategy is based, on a partitioned memory management system taking into account the priority and the lifetime of messages, on the calculation of the transmission rate of the node with respect to the priority class of the node with the highest delivery predictability, on a mechanism for calculating the nodes degree of selfishness with respect to the priority class, and on the monitoring mechanism. . The simulations carried out show that the proposed model can detect selfish nodes and improve network performance in terms of increasing the delivery rate of high-priority messages, reducing the delivery delay of high-priority messages, and reducing network overload.

AN EFFICIENT METAHEURISTIC FOR DYNAMIC NETWORK DESIGN AND MESSAGE ROUTING

Abstract : The implementation of Net-centric warfare presents major challenges in terms of effectively and efficiently delivering critical information across the Global Information Grid. In many cases, the amount of information requested will exceed the capabilities of the network. One challenge is to dynamically design the network (assign transceivers) to maximize the amount of required information that can be transmitted and the quality of service for those transmissions - to best implement the communications tasking order. The problem is as follows: given a list of required message traffic, to include source, destination, size, and priority, design the network to maximize the delivery of the message traffic based on message priority and quality of service. Once the network is designed, the routing for the messages must be determined. Due to the dynamic nature of the problem and the combinatorial explosion in size as new network nodes are added, a quick-running heuristic approach is needed. In this research, metaheuristic to dynamically design the network based on the projected message traffic requirements and to efficiently route the required messages on the network to maximize priority of messages successfully delivered and the quality of service of the delivery. The meta-heuristic is tested against previous efforts and is shown to generate high quality solutions in a very short amount of time.

Promoting physical activity through text messages: the impact of attitude and goal priority messages

ABSTRACT Introduction Many young adults demonstrate insufficient rates of physical activity (PA) to yield health benefits. The study tested the effectiveness of a text messaging intervention targeting key psychological determinants and PA. Methods Participants received either attitude messages, goal priority messages, a combination of these, or generic PA information (control). After confirming that groups were matched at baseline, a 2 (attitude: yes vs. no) by 2 (goal priority: yes vs. no) by 2 (time: immediately post-intervention, four weeks post-intervention) randomized control trial tested main and interactive effects. Results Results showed participants that received attitude messages had significantly more positive attitudes, intentions and rates of PA. Mediational analyses showed the influence of attitude messages on PA to be fully mediated through the serial path via attitude and intention. There were no other main or interactive effects. Conclusion The study provides support for using attitudinal messages delivered via text messaging to influence key psychological determinants and PA.

Catora: congestion avoidance through transmission ordering and resource awareness in delay tolerant networks

The proliferation of wireless mobile devices encourages research into their employment to form delay tolerant networks (DTN) for such applications as disaster response, military communications, and crowdsourcing. Within a DTN, messages are exchanged between nodes following a store-carry-forward paradigm, which is notably susceptible to congestion and can lead to a crippling in network performance. A DTN’s time-dynamic topology departs from traditional network definitions in its unpredictable and volatile nature, thus prohibiting the effective adoption of traditional network solutions to this problem. In this paper, the Catora system is proposed as a multi-copy message exchange and buffer management system designed to both aid in the delivery of prioritized messages and mitigate congestion and its degradation. Operating around the distinct ordering of messages for transfer, delivery, and deletion, Catora propagates messages so as to balance their dissemination, hasten the delivery of high priority messages, and avoid congestion through strategic buffer management. Simulations using two real-world datasets demonstrate Catora’s capability to quickly deliver more messages at reduced overhead costs when compared to benchmarks and the state-of-the-art, even when the network suffers from congestion.

Highly Efficient Authentication for CAN by Identifier Reallocation With Ordered CMACs

Most of the existing works on securing the CAN bus are using the limited data-field of CAN frames to embed a cryptographic payload. Only very few works have suggested the use of the identifier field since identifiers are critical for the arbitration procedure and changing them at random would interfere with message priorities. To preserve priority on the bus, in this work we use an ordered CMAC buffer. In this way, we can authenticate the identifiers of CAN frames and check that the sender is a legitimate node while arbitration on the bus remains unaltered. Moreover, we determine that for real-world scenarios the achieved security level is very close to the length of the ID field despite the constraints from ordering. This procedure easily circumvents replay attacks and fuzz testing on the bus, which were exploited by many recent works. We prove the feasibility of our approach by testing practical implementations on automotive-grade microcontrollers and CAN-bus traffic allocations from a high-end vehicle. The computational requirements are some of the lowest achievable for securing CAN, with a dozen CMAC-AES computations being sufficient for extracting a table of one hundred identifiers.

Context‐aware pub/sub control method using reinforcement learning

SummaryReinforcement learning (RL) is utilized in a wide range of real‐world applications. Typical applications include single agent‐based RL. However, most practical tasks require multiple agents for cooperative control processes. Multiple‐agent RL demands complicated design, and numerous design possibilities should be considered for its practical usefulness. We propose two RL implementations for a message‐queuing telemetry transport (MQTT) protocol system. Two types of implementations improve the communication efficiency of MQTT: (i) single‐broker‐agent implementation and (ii) multiple‐publisher‐agents implementation. We focused on different message priorities in a dynamic environment for each implementation. The proposed implementations improve communication efficiency by adjusting the loop cycle time of the broker or by learning the message importance. The proposed MQTT control scheme improves the battery efficiency of Internet‐of‐Things (IoT)‐based devices with relatively insufficient battery power.

An Efficient location‐aware routing approach in opportunistic networks

AbstractAn opportunistic network is a kind of self‐organizing network that makes use of the encountering opportunities to realize short‐distance wireless communication. Because of the intermittent connectivity between nodes and dynamic network topology, how to devise a reliable and efficient routing approach has become a challenging issue. However, the periodic update mechanism of the node's location information in the existing works costs too much. To address this issue, we propose a location‐aware opportunistic routing (LAOR) approach. In the the proposed LAOR, we first establish a location‐aware prediction model based on the Markov process to predict the node's next location. Then we devise a decision‐making scheme of message forwarding to select the desired relay nodes based on the node's delivery probability. In addition, we introduce a dynamic buffer management strategy to determine the message priority. Finally, we validate the effectiveness of our proposed model and the high efficiency of the LAOR approach. Simulation results demonstrate that the proposed LAOR outperforms the existing Epidemic, Prophet, history‐based prediction routing, and location prediction‐based forwarding for routing using Markov chain algorithms in terms of delivery ratio, overhead ratio, and the number of messages dropped. © 2020 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

Emergency Message Dissemination in Vehicular Networks: A Review

The number of vehicles on the roads has increased proportionally over the last couple of years and this number is likely to rise due to the increase in population growth and the number of vehicles that are manufacturing every day. This high traffic density leads to several problems, from which effectively disseminating the emergency messages is a major concern. Keeping in view the dynamic characteristics of VANETs, significant challenges are faced in disseminating the message across the network. The major challenges are the broadcast storm problem, hidden node problem and the packet collision. Many studies have been performed to devise an effective and reliable mechanism for disseminating emergency messages in a Vehicular ad-Hoc Network (VANET). Researchers have proposed different models to tackle various types of scenarios for emergency message dissemination. This paper not only reviews some recent contributions to emergency message dissemination in vehicular networks but also discusses various proposed methods based on Intelligent Transportation System (ITS), Internet of Things (IoT), Priority messaging, Clustering approach, Software Defined Network (SDN) and Fog Computing. We have also tried to explore the latest developments in emergency message dissemination using 5G networks.

Intelligent Authentication and Message Forwarding in VANET

Vehicle ad hoc networks face the challenging issue of vehicle communication and its security. So, these issues become key research topics for global VANET researchers. Researcher's current solutions mostly focus on either of the problems but currently they are now heading towards finding satisfactory solutions for both of the above-mentioned problems. VANET networks should be robust and strongly dependent on their communication rapidness, message authentication, priority messaging, and security. Here, the authors discuss four VANET issues: authentication delays, fake messages, priority-based messaging, and VANET security, with respective solutions. This article presents an enhanced ECC-based algorithm to minimize authentication delays and provide secure VANET. Result analysis shows that the algorithm is effective in reducing the authentication delays and improves communication rapidness, improves the security model operation to detect Sybil and reply attack, and promotes intelligent message forwarding to block fake messages and increases message delivery performance.