Reliable Message Delivery Research Articles

Improved Fast-Response Consensus Algorithm Based on HotStuff.

Recent Byzantine Fault-Tolerant (BFT) State Machine Replication (SMR) protocols increasingly focus on scalability and security to meet the growing demand for Distributed Ledger Technology (DLT) applications across various domains. Current BFT consensus algorithms typically require a single leader node to receive and validate votes from the majority process and broadcast the results, a design challenging to scale in large systems. We propose a fast-response consensus algorithm based on improvements to HotStuff, aimed at enhancing transaction ordering speed and overall performance of distributed systems, even in the presence of faulty copies. The algorithm introduces an optimistic response assumption, employs a message aggregation tree to collect and validate votes, and uses a dynamically adjusted threshold mechanism to reduce communication delay and improve message delivery reliability. Additionally, a dynamic channel mechanism and an asynchronous leader multi-round mechanism are introduced to address multiple points of failure in the message aggregation tree structure, minimizing dependence on a single leader. This adaptation can be flexibly applied to real-world system conditions to improve performance and responsiveness. We conduct experimental evaluations to verify the algorithm's effectiveness and superiority. Compared to the traditional HotStuff algorithm, the improved algorithm demonstrates higher efficiency and faster response times in handling faulty copies and transaction ordering.

Low-Traffic Aware Hybrid MAC (LTH-MAC) Protocol for Wireless Sensor Networks

This paper proposes LTH-MAC (Low-Traffic Aware Hybrid MAC), a novel MAC protocol designed to improve energy efficiency and message delivery reliability in Wireless Sensor Networks (WSNs). LTH-MAC achieves this through innovative techniques like flexible timeslots, channel selection, collision-avoiding, parallel transmissions, and efficient backoff schemes. These optimizations lead to reduced idle listening, minimized collisions, and simplified synchronization. Simulations using OPNET environment demonstrate that LTH-MAC significantly reduces energy consumption, especially under light traffic loads. Additionally, LTH-MAC provides lower end-to-end latency and higher message delivery reliability compared to ECoMAC. These advancements position LTH-MAC as a compelling solution for WSN applications demanding efficient and reliable communication.

Goat Q: A distributed message broker

goat Q, a distributed message broker explores the design and implementation of a robust message broker system. Utilizing advanced distributed concepts of network and synchronization the project aims to enhance efficiency and reliability of message delivery which fits in an event driven system. It also ensures fault tolerance and scalability. It also considers the integration with containerization and on premise and cloud deployment models to use goatQ as a message broker solution in production. The project seeks to unravel the intricate design of message brokers, illuminating the functionality of publishers, subscribers, and message queues. A key focus lies in a rigorous performance analysis, evaluating metrics such as throughput, latency, and resource use across wide variety message broker implementations. Scalability and fault tolerance, critical considerations in the realm of distributed systems, are addressed through an exploration of how message brokers adapt to dynamic scaling requirements and recover from failures. By synthesizing findings from diverse dimensions of message broker technology, this research project aims to equip technology professionals with valuable insights, aiding informed decision-making in the selection, optimization, and integration of message brokers within their ecosystems. Keyword: About four key words or phrases in alphabetical order, separated by commas. Keywords are used to retrieve documents in an information system such as an online journal or a search engine. (Mention 4-5 keywords)

A metaheuristic MAC protocol for safety applications in cognitive vehicular networks

In a dynamic cognitive vehicular network (CVN) environment, ensuring reliable data delivery of safety messages (sm) is crucial. However, fast-moving vehicles and rapidly changing channel accessibility make sm broadcasting challenging. To address this issue, we propose a cooperative make-up technique, which leverages the 2-Hop Harris Hawks Optimization (HHO) algorithm to choose an optimal helper for sm retransmission in case of failed direct transmission. Our simulations using the Network Simulator version 2 with SUMO demonstrate that the proposed approach achieves cooperative communication within the tight 100ms sm broadcast time frame and outperforms contemporary CVN protocols regarding throughput and packet delivery ratio. Our results suggest that our approach holds great promise for reliable and efficient data delivery in CVNs.

Optimization of message delivery reliability and throughput in a DDS-based system with per-publisher sending rate adjustment

Optimization of message delivery reliability and throughput in a DDS-based system with per-publisher sending rate adjustment

Improving accuracy of medical data handling and processing using DCAF for IoT-based healthcare scenarios

The Internet of Things (IoT), uses communication technologies and intelligent computing to improve data analysis and computation accuracy, which is essential to the healthcare industry. The sensitivity and requirement for precision in managing and processing medical data make it a difficult task for diagnosing patients. To handle medical data in a healthcare scenario based on the IoT, a Data Classification and Analysis Framework (DCAF) is proposed in this research. The proposed framework seeks to improve the precision and dependability of handling and processing medical data, which are essential components of biomedical signal processing. By reducing errors and accelerating the processing of medical data, the framework can help in improving the accuracy of medical diagnosis and therapy, which is a key objective of biomedical signal processing and control. The goal of this framework is to increase the reliability of message delivery by concentrating on data classification and analysis. The earlier procedure is in charge of decreasing the volume of medical data transfers and ensuring the accuracy and delivery of consent data. The framework's latter process is in charge of allotting suitable processing time slots to increase delivery speed and lower data handling faults. A linear decision-making process based on accessibility, sequence order, and accuracy constraints and conditions supports the framework's joint process. Utilizing measures such as an accuracy ratio 0f 93.09 %, message delivery rate of 0.949 %, error with a range of 0.052 %, classification of 73.81 ms, and analysis time over fluctuating flow instances and analysis slots, the suggested framework's performance is validated.

An energy-efficient command broadcast protocol in dynamic WSNs

In wireless sensor networks (WSNs), a sink must broadcast periodically a command message to a group of nodes or all nodes to control the operation of the network. However, the sparse distribution and limited resources of nodes bring difficulties for efficient broadcasting. In this paper, we propose an energy-efficient command broadcast protocol based on the construction of a spanning tree which includes maximizing the number of leaf nodes, and the allocation of one sharable slot to each tree level. The sharable slot that allocates to tree level will be divided into multiple mini slots, and non-leaf nodes at the same level will compete for broadcasting; in this way, collision can be reduced. Moreover, a node that moves to another level can use the sharable slot allocated to the new level without reallocating the slots. Extensive simulations prove that this approach not only achieves high reliability of message delivery but also energy efficiency.

Optimizing Resource Allocation With High-Reliability Constraint for Multicasting Automotive Messages in 5G NR C-V2X Networks

Cellular vehicle-to-everything (C-V2X) has been continuously evolving since Release 14 of the 3 rd Generation Partnership Project (3GPP) for future autonomous vehicles. Apart from automotive safety, 5 G NR further bring new capabilities to C-V2X for autonomous driving, such as real-time local update, and coordinated driving. These capabilities rely on the provision of low latency and high reliability from 5 G NR. Among them, a basic demand is broadcasting or multicasting environment update messages, such as cooperative perception data, with high reliability and low latency from a Road Side Unit (RSU) or a base station (BS). In other words, broadcasting multiple types of automotive messages with high reliability and low latency is one of the key issues in 5 G NR C-V2X. In this work, we consider how to select Modulation and Coding Scheme (MCS), RSU/BS, Forward Error Correction (FEC) code rate, to maximize the system utility, which is a function of message delivery reliability. We formulate the optimization problem as a nonlinear integer programming problem. Since the optimization problem is NP-hard, we propose an approximation algorithm, referred to as the Hyperbolic Successive Convex Approximation (HSCA) algorithm, which uses the successive convex approximation to find the optimal solution. In our simulations, we compare the performance of HSCA with those of three algorithms respectively, including the baseline algorithm, the heuristic algorithm, and the optimal solution. Our simulation results show that HSCA outperforms the baseline and the heuristic algorithms and is very competitive to the optimal solution.

Optimizing Bulk Transfer Size and Scheduling for Efficient Buffer Management in Mobile Opportunistic Networks

Mobile Opportunistic Networks (MONs) are characterized by intermittent connectivity with long isolation period, and nodes following redundant transmissions for reliable message delivery. This often leads to unnecessary buffer occupancy, preventing new messages from getting replicated due to small contact duration and low bandwidth, or leading to packet drop under constrained buffer. Although attempts have been made to mitigate buffer congestion, the existing schemes are localized, are slow to react, or are specific to a routing scheme. Moreover, they rely on message exchanges to obtain buffer state/occupancy, thereby incurring additional overhead. In this paper, we first develop a generalized probabilistic forwarding model where the forwarding probability denotes the likelihood of a message to get forwarded to the encountered node. Based on the forwarding probability, we develop a congestion indicator and predict the point of congestion using the Kalman filter. Using this, a node can decide the optimal number and the exact set of messages to replicate, which leads to an optimal performance with minimal packet drop and overhead. Simulation results using a synthetic mobility model and a real-life mobility trace show that the proposed scheme outperforms the existing schemes.

ERCP: Energy-Efficient and Reliable-Aware Clustering Protocol for Wireless Sensor Networks.

Wireless Sensor Networks (WSNs) have been around for over a decade and have been used in many important applications. Energy and reliability are two of the major problems with these kinds of applications. Reliable data delivery is an important issue in WSNs because it is a key part of how well data are sent. At the same time, energy consumption in battery-based sensors is another challenge. Therefore, efficient clustering and routing are techniques that can be used to save sensors energy and guarantee reliable message delivery. With this in mind, this paper develops an energy-efficient and reliable clustering protocol (ERCP) for WSNs. First, an efficient clustering technique is proposed for sensor nodes' energy savings considering different clustering parameters, including the link quality metric, the energy, the distance to neighbors, the distance to the sink node, and the cluster load metric. The proposed routing protocol works based on the concept of a reliable inter-cluster routing technique that saves energy. The routing decisions are made based on different parameters, such as the energy balance metric, the distance to the sink node, and the wireless link quality. Many experiments and analyses are examined to determine how well the ERCP performs. The experiment results showed that the ECRP protocol performs much better than some of the recent algorithms in both homogeneous and heterogeneous networks.

Blossom: Cluster-Based Routing for Preserving Privacy in Opportunistic Networks

Opportunistic networks are an enabler technology for typologies without centralized infrastructure. Portable devices, such as wearable and embedded mobile systems, send relay messages to the communication range devices. One of the most critical challenges is to find the optimal route in these networks while at the same time preserving privacy for the participants of the network. Addressing this challenge, we presented a novel routing algorithm based on device clusters, reducing the overall message load and increasing network performance. At the same time, possibly identifying information of network nodes is eliminated by cloaking to meet privacy requirements. We evaluated our routing algorithm in terms of efficiency and privacy in opportunistic networks of traditional and structured cities, i.e., Venice and San Francisco by comparing our approach against the PRoPHET, First Contact, and Epidemic routing algorithms. In the San Francisco and Venice scenarios, Blossom improves messages delivery probability and outperforms PRoPHET, First Contact, and Epidemic by 46%, 100%, and 160% and by 67%, 78%, and 204%, respectively. In addition, the dropped messages probability in Blossom decreased 83% compared to PRoPHET and Epidemic in San Francisco and 91% compared to PRoPHET and Epidemic in Venice. Due to the small number of messages generated, the network overhead in this algorithm is close to zero. The network overhead can be significantly reduced by clustering while maintaining a reliable message delivery.

Protecting endangered megafauna through AI analysis of drone images in a low-connectivity setting: a case study from Namibia.

Assessing the numbers and distribution of at-risk megafauna such as the black rhino (Diceros bicornis) is key to effective conservation, yet such data are difficult to obtain. Many current monitoring technologies are invasive to the target animals and expensive. Satellite monitoring is emerging as a potential tool for very large animals (e.g., elephant) but detecting smaller species requires higher resolution imaging. Drones can deliver the required resolution and speed of monitoring, but challenges remain in delivering automated monitoring systems where internet connectivity is unreliable or absent. This study describes a model built to run on a drone to identify in situ images of megafauna. Compared with previously reported studies, this automated detection framework has a lower hardware cost and can function with a reduced internet bandwidth requirement for local network communication. It proposes the use of a Jetson Xavier NX, onboard a Parrot Anafi drone, connected to the internet throughout the flight to deliver a lightweight web-based notification system upon detection of the target species. The GPS location with the detected target species images is sent using MQ Telemetry Transport (MQTT), a lightweight messaging protocol using a publisher/subscriber architecture for IoT devices. It provides reliable message delivery when internet connection is sporadic. We used a YOLOv5l6 object detection architecture trained to identify a bounding box for one of five objects of interest in a frame of video. At an intersection over union (IoU) threshold of 0.5, our model achieved an average precision (AP) of 0.81 for black rhino (our primary target) and 0.83 for giraffe (Giraffa giraffa). The model was less successful at identifying the other smaller objects which were not our primary targets: 0.34, 0.25, and 0.42 for ostrich (Struthio camelus australis), springbok (Antidorcas marsupialis) and human respectively. We used several techniques to optimize performance and overcome the inherent challenge of small objects (animals) in the data. Although our primary focus for the development of the model was rhino, we included other species classes to emulate field conditions where many animal species are encountered, and thus reduce the false positive occurrence rate for rhino detections. To constrain model overfitting, we trained the model on a dataset with varied terrain, angle and lighting conditions and used data augmentation techniques (i.e., GANs). We used image tiling and a relatively larger (i.e., higher resolution) image input size to compensate for the difficulty faced in detecting small objects when using YOLO. In this study, we demonstrated the potential of a drone-based AI pipeline model to automate the detection of free-ranging megafauna detection in a remote setting and create alerts to a wildlife manager in a relatively poorly connected field environment.

ТЕХНОЛОГИИ РАЗВИТИЯ МОРСКИХ ИНТЕГРИРОВАННЫХ СИСТЕМ СВЯЗИ

The goal is to improve the quality of information interaction of objects by increasing the reliability of message delivery to recipients and bandwidth through the integration of networks using various signals and physical channels. A search for new technical solutions for the creation of integrated (hybrid) communication technologies aimed at expanding the possibilities for creating adaptive, self organizing, resistant to destabilizing factors communication systems with an increased quality of services provided in vast areas was carried out. The method of solving the tasks is based on the analysis of development trends and forecasting the requirements for integrated mobile communication systems. The novelty lies in the development and evaluation of options for building the structures of integrated communication systems, represented by diverse, complementary subsystems using various methods of channel separation, including in physical environments, as well as algorithms for their operation. Key findings. A set of technologies for the development of coastal integrated communication systems has been developed: the structure of the system based on a hybrid mesh topology; the basic form of the carrier signal with controlled parameters depending on the physical channel; the principle of control of orthogonal signals in adjacent channels of switching and relay nodes, as well as between network nodes; hydroacoustic communication method. Hydroacoustic communication for coastal areas is a potential for increasing the number of simultaneously used information channels per unit of the volume of interaction of vital objects and makes it possible to connect satellite, air, surface, underwater and bottom subsystems of telecommunications. The con ducted studies have shown the stability of the proposed methods in conditions of excess of interference over the signal.

Communication for Real-Time Music Systems: An Overview of O2

Abstract Message passing between processes and across networks offers a powerful method to integrate and coordinate various music programs, facilitating software reuse, modularity, and parallel processing. Networking can integrate components that use different languages and hardware. In this article we describe O2, a flexible protocol for communication ranging from the thread level up to the level of global networks. Messages in O2 are similar to those of Open Sound Control, but O2 offers many additional features, including discovery, clock synchronization, a reliable message delivery option, and routing based on services rather than specific network addresses. A bridge mechanism extends the reach of O2 to web browsers, shared memory threads, and small microcontrollers. The design, implementation, and applications of O2 are described.

Performance of the Transport Layer Security Handshake Over 6TiSCH

This paper presents a thorough comparison of the Transport Layer Security (TLS) v1.2 and Datagram TLS (DTLS) v1.2 handshake in 6TiSCH networks. TLS and DTLS play a crucial role in protecting daily Internet traffic, while 6TiSCH is a major low-power link layer technology for the IoT. In recent years, DTLS has been the de-facto security protocol to protect IoT application traffic, mainly because it runs over lightweight, unreliable transport protocols, i.e., UDP. However, unlike the DTLS record layer, the handshake requires reliable message delivery. It, therefore, incorporates sequence numbers, a retransmission timer, and a fragmentation algorithm. Our goal is to study how well these mechanisms perform, in the constrained setting of 6TiSCH, compared to TCP’s reliability algorithms, relied upon by TLS. We port the mbedTLS library to OpenWSN, a 6TiSCH reference implementation, and deploy the code on the state-of-the-art OpenMote platform. We show that, when the peers use an ideal channel, the DTLS handshake uses up to 800 less and completes s faster. Nonetheless, using an unreliable communication link, the DTLS handshake duration suffers a performance penalty of roughly , while TLS’ handshake duration degrades by merely . Similarly, the number of exchanged bytes doubles for DTLS while for TLS the increase is limited to . The results indicate that IoT product developers should account for network characteristics when selecting a security protocol. Neglecting to do so can negatively impact the battery lifetime of the entire constrained network.

Bayesian Game Approach to Mitigate DoS Attack in Vehicular Ad-Hoc Networks

Background: Trustful message transmission within the Vehicular ad-hoc Networks is needed as traffic related safety applications needs successful and reliable delivery of messages. The biggest issue is how only the trustworthy parties can be retained and the misbehaved are revoked. From the background analysis, it gives a detailed view of various vulnerabilities in these networks and the techniques used by the researchers to identify and mitigate the attack. Based on the drawbacks observed in the literature the proposed Bayesian Game Mechanism has been designed. Objective: The major objective of this manuscript is to identify the Denial of Service Attack in Vehicular Ad-hoc Networks as it depletes availability of the resources. This attack is identified using Bayesian Game approach. Methods: The Bayesian game approach is used to identify the attack. It analyzes the behavior of vehicles and classifies them into trustworthy or malicious. Results: The simulation is conducted using Network simulator 2.34 and the traffic model is designed using by considering 100 nodes. From the results it is inferred that Packet drop ratio has been improved by 9.82 % and the delay and throughput has been minimized, when the proposed mechanism is used in the presence of attackers. Conclusion: This paper identifies Denial of Service attack as the most vulnerable attack in this network and has designed game theoretic approach namely Bayesian approach for preventing this attack. The proposed method has minimized the delay and packet drop and improved the throughput when compared against the bench mark.

Mitigating message dissemination issues in safety applications for vehicular ad hoc networks

SummaryIn a vehicular ad hoc network (VANET) each node is required to transmit periodic and event‐driven messages. The periodic messages are also known as beacons and consist of the basic vehicle status, such as position, speed, direction, and any additional information required by a safety application. One of the main concerns faced with this technology is channel congestion, which often happens in scenarios with a high vehicular density like traffic jams. When the channel is congested, there are no guarantees for a reliable message delivery. For this purpose, several protocols have been proposed to resolve this issue. In this work we propose neighbor congestion avoidance protocol (NCAP) as a novel solution employing a proactive strategy with vehicle position prediction using Kalman filter and an efficient event‐driven message delivery scheme. When compared with other strategies in congested scenarios, NCAP was able to significantly decrease the number of beacons by 49%, while also reducing the number of event‐driven message retransmissions by approximately 81%. NCAP also presented better performance in regard to the number of collisions between messages and channel busy ratio.

Sporadic Ultra-Time-Critical Crowd Messaging in V2X

Life-critical warning message, abbreviated as warning message, is a special event-driven message that carries emergency information in Vehicle-to-Everything (V2X). Three important characteristics that distinguish warning messages from ordinary vehicular messages are sporadicity, crowding, and ultra-time-criticality. Specifically, warning messages come only once in a while in a sporadic manner; however, when they come, they tend to come as a crowd and they need to be delivered in short order. This paper puts forth a medium-access control (MAC) protocol for warning messages. The overall MAC protocol operates by means of interrupt-and-access. To circumvent potential inefficiency arising from message sporadicity, we adopt an override network architecture whereby warning messages are delivered on the spectrum of the ordinary vehicular messages. A vehicle with a warning message first sends an interrupt signal to pre-empt the transmission of ordinary messages, so that the warning message can use the wireless spectrum originally allocated to ordinary messages. In this way, no exclusive spectrum resources need to be pre-allocated to the sporadic warning messages. Following the interrupt, for transmissions of ultra-time-critical crowd messages, we employ advanced channel access techniques to ensure reliable message delivery within an ultra-short time in the order of 10 ms.

Avoiding Spurious Retransmission over Flooding-Based Routing Protocol for Underwater Sensor Networks

In underwater wireless sensor networks (UWSN), acoustic communication naturally introduces challenges such as long propagation delay and high packet loss. The flooding-based routing protocol can address these challenges with its multipath characteristics. As in flooding-based routing, due to multipath propagation mechanism, not only DATA but also ACK messages are transmitted through multiple routes however still some packet loss will degrade the performance. So, to provide high reliability of message delivery, an efficient retransmission mechanism is inevitable. Though, if the network uses conventional transport layer protocol such as TCP, it will suffer a spurious retransmission problem as TCP was originally not designed for the multipath environment. In this paper, we propose route discrimination for flooding-based routing to reduce spurious retransmission in UWSN to solve the limitation. The notion of ACK copies waiting time (ACWT) is utilized which is selectively updated based on the similarity of paths of transmission of ACK message copies. We also improved our previous solution that lacks flexibility to cope with dynamic link error characteristics. Through evaluation, we verified that our new scheme achieves the performance improvements of 14%~84% in terms of retransmission ratio compared to the previous research.

Development of algorithms of self-organizing network for reliable data exchange between autonomous robots

Factors affecting the reliability of data transmission in networks with nodes with periodic availability were considered. The principles of data transfer between robots are described; the need for global connectivity of communications within an autonomous system is shown, since the non-availability of information on the intentions of other robots reduces the effectiveness of the robotics system as a whole and affects the fault tolerance of a team of independent actors performing distributed activities. It is shown that the existing solutions to the problem of data exchange based on general-purpose IP networks have drawbacks; therefore, as the basis for organizing autonomous robot networks, we used developments in the domain of topological models of communication systems allowing us to build self-organizing computer networks. The requirements for the designed network for reliable message transfer between autonomous robots are listed, the option of organizing reliable message delivery using overlay networks, which expand the functionality of underlying networks, is selected. An overview of existing popular controlled and non-controlled overlay networks is given; their applicability for communication within a team of autonomous robots is evaluated. The features and specifics of data transfer in a team of autonomous robots are listed. The algorithms and architecture of the overlay self-organizing network were described by means of generally accepted methods of constructing decentralized networks with zero configurations. As a result of the work, general principles of operation of the designed network were proposed, the message structure for the delivery algorithm was described; two independent data streams were created, i.e. service and payload; an algorithm for sending messages between network nodes and an algorithm for collecting and synchronizing the global network status were developed. In order to increase the dependability and fault tolerance of the network, it is proposed to store the global network status at each node. The principles of operation of a distributed storage are described. For the purpose of notification on changes in the global status of the network, it is proposed to use an additional data stream for intra-network service messages. A flood routing algorithm was developed to reduce delays and speed up the synchronization of the global status of a network and consistency maintenance. It is proposed to provide network connectivity using the HELLO protocol to establish and maintain adjacency relations between network nodes. The paper provides examples of adding and removing network nodes, examines possible scalability problems of the developed overlay network and methods for solving them. It confirms the criteria and indicators for achieving the effect of self-organization of nodes in the network. The designed network is compared with existing alternatives. For the developed algorithms, examples of latency estimates in message delivery are given. The theoretical limitations of the overlay network in the presence of intentional and unintentional defects are indicated; an example of restoring the network after a failure is set forth.