Synchronous Message Research Articles

Intelligent Edge-Enabled Efficient Multi-Source Data Fusion for Autonomous Surface Vehicles in Maritime Internet of Things

With the rapid development of low-end Internet of Things (IoT) devices and shipborne sensors, efficient multi-source data fusion methods for autonomous surface vehicles (ASVs) have recently attracted significant research interest in intelligent edge-enabled maritime applications. The data fusion capacity can enhance the situation awareness of ASVs, leading to improved efficacy and safety in ASV-empowered maritime IoT (MIoT). Both cameras and automatic identification system (AIS) equipment, which provide visual and positioning information, respectively, have become the commonly adopted cost-effective sensors. In this work, we first introduce a lightweight YOLOX-s network with transfer learning to accurately and robustly detect the moving vessels at different scales in real time. A data augmentation method is then proposed to promote its generalization ability. The detected vessels and synchronous AIS messages are finally fused to make full use of the multi-source sensing data, contributing to an augmented reality (AR)-based maritime navigation system at the shipborne intelligent edges. The AR system is able to superimpose both static and dynamic information from the collected AIS messages onto the video-captured images. It has the capacity of providing auxiliary information for early warning of navigation risks for ASVs in MIoT networks. Compared with traditional single-sensor-based navigation methods, our data fusion framework exhibits more reliable and robust results, and appears to have substantial practical potential applications. Extensive experiments have been conducted to demonstrate the superior performance of our framework under different navigational conditions.

Energy-Efficient Message Bundling with Delay and Synchronization Constraints in Wireless Sensor Networks.

In a wireless sensor network (WSN), reducing the energy consumption of battery-powered sensor nodes is key to extending their operating duration before battery replacement is required. Message bundling can save on the energy consumption of sensor nodes by reducing the number of message transmissions. However, bundling a large number of messages could increase not only the end-to-end delays and message transmission intervals, but also the packet error rate (PER). End-to-end delays are critical in delay-sensitive applications, such as factory monitoring and disaster prevention. Message transmission intervals affect time synchronization accuracy when bundling includes synchronization messages, while an increased PER results in more message retransmissions and, thereby, consumes more energy. To address these issues, this paper proposes an optimal message bundling scheme based on an objective function for the total energy consumption of a WSN, which also takes into account the effects of packet retransmissions and, thereby, strikes the optimal balance between the number of bundled messages and the number of retransmissions given a link quality. The proposed optimal bundling is formulated as an integer nonlinear programming problem and solved using a self-adaptive global-best harmony search (SGHS) algorithm. The experimental results, based on the Cooja emulator of Contiki-NG, demonstrate that the proposed optimal bundling scheme saves up to 51.8% and 8.8% of the total energy consumption with respect to the baseline of no bundling and the state-of-the-art integer linear programming model, respectively.

Vulnerability Analysis of LTE-R Train-to-Ground Communication Time Synchronization

The time synchronization of LTE-R train-to-ground communication systems plays an important role in ensuring the safety of high-speed railways. In the LTE-R time synchronization process, existing problems, such as the time synchronization message broadcast address and LTE-R all-IP architecture, are vulnerable to attack. In order to analyze the impact of these problems, we propose a new vulnerability analysis method of LTE-R time synchronization based on stochastic Petri nets. Firstly, we construct a stochastic Petri net model of an LTE-R time synchronization process under attack. Secondly, steady-state probability expressions are obtained using the model isomorphism Markov chain. Finally, bychanging the firing rate of several key vulnerable nodes, the relationship curve between the firing rate and the steady-state probability of the clock node is obtained. Simulations show that the vulnerability of LTE-R time synchronization is most affected by the attack on eNodeB of the LTE-R base station. The results can provide a certain theoretical basis for the evolution of high-speed railway GSM-R communication systems to LTE-R.

New Media Adaptation through Environmentally Friendly Dissemination Messages at a Religious Organization during the COVID-19 Era in Indonesia

This study seeks to explore new media adaptation through environmentally friendly dissemination messages at a religious organization during the Covid 19 era in Indonesia. This study used the phenomenographic method in a constructive/interpretive paradigm to explore the difference in the experience of members of the congregation who participate in online worship versus face-to-face worship to demonstrate environmentally friendly dissemination messages. Data collection was carried out through in-depth interviews with informants who represented three levels of membership of ordinary members, church administrators, and organization administrators. Secondary data was obtained through the documentation of social media of the religious organization (the Christian Church of East Java) in Surabaya, East Java Province, Indonesia. The findings of this study confirm different variations of experience in synchronous and asynchronous worship. The variety of experiences is divided into knowledge, feelings, and mindset of the congregation. Synchronous message dissemination contributes strongly to the knowledge, feelings, and mindset of the congregation in facing changes in worship models. This study contributes by offering an alternative to the phenomenographic method in the study of organizational communication. The limitation of the study lies in the object of the study which is limited to informants from the local church in urban areas. This research has yet to accommodate the online worship experience for congregations in rural areas.

The Influence of Combining Computer-Assisted Language Learning With Instruction on Chinese College Students’ L2 Pragmatic Ability

AbstractIn the area of computer-assisted language learning (CALL), although a number of studies have adopted various CALL-based devices (e. g., blogs, gaming, and synthetic environments) to foster second language (L2) acquisition, the vital component of instruction has received little attention. The present study explored the usefulness of CALL-based communication in conjunction with instruction on EFL learners’ L2 pragmatic development. Sixty-two EFL students from a university in China were recruited for the current research. The experimental group communicated with a native English speaker through synchronous messaging via Skype and had two instructional sessions pertinent to compliment responses, while the control group interacted with a native English speaker via Skype without having the teaching intervention. Findings from an independent samplest-test demonstrated that the experimental group produced significantly more proper compliment responses in the immediate posttest than the control group (p< . 001). Moreover, a significant difference (p< . 001) was found for the experimental group between the pre-intervention and delayed post-intervention mean scores, suggesting that CALL coupled with teaching intervention had a long-term impact on learners’ L2 pragmatic development. These findings enrich our understanding of the beneficial and lasting influence of combining CALL with instruction on EFL students’ pragmatic development. In addition, pedagogical implications for deploying CALL paired with L2 pragmatics instruction are provided.

A Security Enhancement of the Precision Time Protocol Using a Trusted Supervisor Node.

The Precision Time Protocol (PTP) as described in IEEE 1588–2019 provides a sophisticated mechanism to achieve microsecond or even sub-microsecond synchronization of computer clocks in a well-designed and managed network, therefore meeting the needs of even the most time-sensitive industrial and financial applications. However, PTP is prone to many security threats that impact on a correct clock synchronization, leading to potentially devastating consequences. Here, the most vicious attacks are internal attacks, where a threat actor has full access to the infrastructure including any cryptographic keys used. This paper builds on existing research on the impact of internal attack strategies on PTP networks. It shows limitations of existing security approaches to tackle internal attacks and proposes a new security approach using a trusted supervisor node (TSN), in line with prong D as specified in IEEE 1588–2019. A TSN collects and analyzes delay and offset outputs of monitored slaves, as well as timestamps embedded in PTP synchronization messages, allowing it to detect abnormal patterns that point to an attack. The paper distinguishes between two types of TSN with different capabilities and proposes two different detection algorithms. Experiments show the ability of the proposed method to detect all internal PTP attacks, while outlining its limitations.

Formal Verification and Analysis of 5G AKA Protocol Using Mixed Strand Space Model

The 5th generation mobile communication technology (5G) authentication and key management (AKA) protocol specified by the 3rd generation partnership project (3GPP) includes three cases because it introduces synchronization failure and message authentication code (MAC) failure procedures. Thus, there may be interactions between these cases, forming vulnerabilities that do not exist in any single case. However, this is not fully considered in the existing formal analysis and improvement of the 5G AKA protocol. To solve this problem, this paper formally analyzes the security of the latest version of the 5G AKA protocol based on the mixed strand space model for mixed protocols and finds many new attacks, including cross attacks for mixed cases. Then, a secure and efficient primary authentication and key agreement protocol for 5G networks is proposed, which is named the 5G-AKA’. In the 5G-AKA’ protocol, the pre-shared key between the user equipment (UE) and the home network (HN) is replaced with a derivation key of the pre-shared key, the challenge–response mechanism between the serving network (SN) and the HN is added, the subscription permanent identifier (SUPI) of the UE is added to the second message between the SN and the HN, and the MAC failure is replaced with a timeout mechanism on the HN. Finally, the 5G-AKA’ protocol is proved secure in the mixed strand space model and can overcome these attacks of the latest version of the 5G AKA protocol. Additionally, the comparative analysis shows that the 5G-AKA’ protocol is better than the recently improved 5G AKA protocols in security, and the 5G-AKA’ protocol is efficient and is backward compatible with the 5G AKA protocol.

Parameterized verification of systems with component identities, using view abstraction

The parameterized verification problem seeks to verify all members of some collection of systems. We consider the parameterized verification problem applied to systems that are composed of an arbitrary number of component processes, together with some fixed processes. The components are taken from one or more families, each family representing one role in the system; all components within a family are symmetric to one another. Processes communicate via synchronous message passing. In particular, each component process has an identity, which may be included in messages, and passed to third parties. We extend Abdulla et al.’s technique of view abstraction, together with techniques based on symmetry reduction, to this setting. We give an algorithm and implementation that allows such systems to be verified for an arbitrary number of components: we do this for both safety and deadlock-freedom properties. We apply the techniques to a number of examples. We can model both active components, such as threads, and passive components, such as nodes in a linked list: thus our approach allows the verification of unbounded concurrent datatypes operated on by an unbounded number of threads. We show how to combine view abstraction with additional techniques in order to deal with other potentially infinite aspects of the analysis: for example, we deal with potentially infinite specifications, such as a datatype being a queue; and we deal with unbounded types of data stored in a datatype.

SecFHome: Secure remote authentication in fog-enabled smart home environment

Fog computing is the best solution for IoT applications with low latency and real-time interaction. Fog can endow smart home with many smart functions and services. One of the most important services is that users can remotely access and control smart devices. Since remote users and smart homes communicate through insecure channels, it is necessary to design a secure and effective remote authentication scheme to guarantee secure communications. The existing authentication schemes designed for smart homes have some security issues and are not suitable for fog-enabled smart home environments. Therefore, this paper designs a secure remote user authentication scheme, SecFHome. It supports secure communication at the edge of the network and remote authentication in fog-enabled smart home systems. Specifically, We present an efficient authentication mode in the fog-enabled environment, which includes the edge negotiation phase and the authentication phase. SecFHome adds updated information to the authenticator, which can verify the message synchronization simultaneously with the authentication, thus improving the authentication efficiency. In addition, SecFHome does not store sensitive information of users and smart devices in the memory of the smart gateway, which can avoid various attacks caused by the compromised gateway. The formal security proof and informal security analysis show that the SecFHome is secure and can resist known attacks. Compared with the related authentication schemes, SecFHome only needs fewer communication costs and computation costs, and achieves more security features.

The Insertion of Person References Motivated by Pragmatic Differences in Estonian-English-Japanese Facebook Communication

Sociopragmatic differences have been examined between many languages and cultures, including English and Japanese. However, Estonian and Japanese have yet to be compared, and thus this data of EstonianEnglish-Japanese communication on Facebook offers a look at a type of code-switching that is caused by the sociopragmatic differences between Estonian and Japanese – i.e. the insertion of person references from Japanese to Estonian and English utterances by native Estonians. I am using the Estonian-English-Japanese Facebook communication dataset from Kilp (2021) with new added conversations. The data consist of synchronous private Facebook messages between 2015 and 2021: a total of 7 informants, 50 conversations and 14,681 tokens. A usage-based approach and a qualitative analysis are applied to the data from individual informants and particular cases. These data show that a perception of pragmatic differences causes the insertions of the Japanese person references, senpai ‘senior’ and sensei ‘teacher’, in various forms (affixed to the name, replacing the name, elongated, capitalised, in the Latin alphabet, in Japanese script) in Estonian and English utterances, while factors such as vertical hierarchy, horizontal solidarity and (situational) salience play an important role in facilitating insertion. Keywords: deixis, code-switching, vocative, usage-based approach, contact linguistics, computer-mediated communication, salience, Estonian, English, Japanese

A Methodology for Modeling Interoperability of Smart Sensors in Smart Grids.

Smart sensors in smart grids provide real-time data and status of bidirectional flows of energy for monitoring, protection, and control of grid operations to improve reliability and resilience. Smart sensor data interoperability is a major challenge for smart grids. This paper proposes a methodology for modeling interoperability of smart sensors in terms of interactions using labeled transition systems and finite state processes in order to quantitatively and automatically measure and assess the interoperability, identify and resolve interoperability issues, and improve interoperability. A generic interoperability model of synchronous message passing from a sender to a receiver is built based on the proposed methodology. A case study is provided to apply this methodology for modeling interoperability between the Institute of Electrical and Electronics Engineers C37.118 phasor measurement unit-based smart sensors and phasor data concentrators. The interoperability model can be used for the quantitative and automated measurement and assessment of the interoperability of phasor measurement unit-based smart sensors and phasor data concentrators to address interoperability issues. This methodology can also be applied to modeling interoperability of smart sensors based on other standard communication protocols in order to achieve and assure sensor data interoperability in smart grids.

Implementation of a Circuit for Precise Time Stamping of Synchronous Message

Highly required by distributed network operation, the clock synchronization technology is very important. The transmit time of synchronization packets should be stamped precisely in a clock synchronization system. Time stamping in the physical layer is necessary to obtain the time precisely. This paper introduces a general precision time stamping circuit based on 10Mb/s and 100Mb/s transmission. The circuit is designed and manufactured in 0.18μm CMOS technology supporting Precise Timing Protocol based on IEEE 1588. The circuit is verified by an experimental system. The test results show that the general precision time stamping circuit can mark the stamps for UDP/IPv4 Ethernet format in the physical layer. The circuit has an ability to mark a time stamp in less than 60μs.

Lessons Learned: Providing Supportive Accountability in an Online Anxiety Intervention

Technology-delivered interventions have the potential to help address the treatment gap in mental health care but are plagued by high attrition. Adding coaching, or minimal contact with a nonspecialist provider, may encourage engagement and decrease dropout, while remaining scalable. Coaching has been studied in interventions for various mental health conditions but has not yet been tested with anxious samples. This study describes the development of and reactions to a low-intensity coaching protocol administered to N = 282 anxious adults identified as high risk to drop out of a web-based cognitive bias modification for interpretation intervention. Undergraduate research assistants were trained as coaches and communicated with participants via phone calls and synchronous text messaging. About half of the sample never responded to coaches’ attempts to schedule an initial phone call or did not answer the call, though about 30% completed the full intervention with their coach. Some anxious adults may choose technology-delivered interventions specifically for their lack of human contact and may fear talking to strangers on the phone; future recommendations include taking a more intensive user-centered design approach to creating and implementing a coaching protocol, allowing coaching support to be optional, and providing users with more information about how and why the intervention works.

Bump2Baby and Me: protocol for a randomised trial of mHealth coaching for healthy gestational weight gain and improved postnatal outcomes in high-risk women and their children

BackgroundGestational diabetes (GDM) impacts 8–18% of pregnancies and greatly increases both maternal and child risk of developing non-communicable diseases such as type 2 diabetes and obesity. Whilst lifestyle interventions in pregnancy and postpartum reduce this risk, a research translation gap remains around delivering implementable interventions with adequate population penetration and participation. Impact Diabetes Bump2Baby is an implementation project of an evidence-based system of care for the prevention of overweight and obesity. Bump2Baby and Me is the multicentre randomised controlled trial investigating the effectiveness of a mHealth coaching programme in pregnancy and postpartum for women at high risk of developing GDM.MethodsEight hundred women will be recruited in early pregnancy from 4 clinical sites within Ireland, the UK, Spain, and Australia. Women will be screened for eligibility using the validated Monash GDM screening tool. Participants will be enrolled from 12 to 24 weeks’ gestation and randomised on a 1:1 basis into the intervention or control arm. Alongside usual care, the intervention involves mHealth coaching via a smartphone application, which uses a combination of synchronous and asynchronous video and text messaging, and allows for personalised support and goal setting with a trained health coach. The control arm receives usual care. All women and their children will be followed from early pregnancy until 12 months postpartum. The primary outcome will be a difference in maternal body mass index (BMI) of 0.8 kg/m2 at 12 months postpartum. Secondary maternal and infant outcomes include the development of GDM, gestational weight gain, pregnancy outcomes, improvements in diet, physical activity, sleep, and neonatal weight and infant growth patterns. The 5-year project is funded by the EU Commission Horizon 2020 and the Australian National Health and Medical Research Council. Ethical approval has been received.DiscussionPrevious interventions have not moved beyond tightly controlled efficacy trials into routine service delivery. This project aims to provide evidence-based, sustainable support that could be incorporated into usual care for women during pregnancy and postpartum. This study will contribute evidence to inform the early prevention of non-communicable diseases like obesity and diabetes in mothers and the next generation.Trial registrationAustralian New Zealand Clinical Trials Registry ACTRN12620001240932. Registered on 19 November 2020

Single LED positioning scheme based on angle sensors in robotics.

Indoor robotic localization is one of the most active areas in robotics research nowadays. Visible light positioning (VLP) is a promising indoor localization method, as it provides high positioning accuracy and allows for leveraging the existing lighting infrastructure. Apparently, accurate positioning performance is mostly shown by the VLP system with multiple LEDs, while such strict requirement of LED numbers is more likely to lead to VLP system failure in actual environments. In this paper, we propose a single-LED VLP system based on image sensor with the help of angle sensor estimation, which efficiently relaxes the assumption on the minimum number of simultaneously captured LEDs from several to one. Aiming at improving the robustness and accuracy of positioning in the process of continuous change of robot pose, two methods of visual-inertial message synchronization are proposed and used to obtain the well-matched positioning data packets. Various schemes of single-LED VLP system based on different sensor selections and message synchronization methods have been listed and compared in an actual environment. The effectiveness of the proposed single-LED VLP system based on odometer and image sensor as well as the robustness under LED shortage, handover situation and background non-signal light interference, are verified by real-world experiments. The experimental results show that our proposed system can provide an average accuracy of 2.47 cm and the average computational time in low-cost embedded platforms is around 0.184 s.

Wireless strain synchronization acquisition method based on Kalman Filter

For distributed wireless sensor networks, the time synchronization mechanism is the core part and the key to realize the coordination and processing of tasks between nodes. In this paper, an algorithm based on kalman filter is developed the wireless strain of synchronous acquisition system, through the coordinator fixed time interval by a synchronous message, when each node receives the synchronous message to mark its timer timestamp clock information of nodes, then the node according to the records of the clock information periodically call kalman filtering algorithm is used to estimate the next cycle of its own real clock and standard clock deviation coordinator, in the next cycle, real-time compensation is made by adjusting the overflow count value of node timer to achieve high synchronization accuracy. The sensor nodes in the system have high strain sampling accuracy and meet the requirements of general engineering applications.

Advanced Join Patterns for the Actor Model based on CEP Techniques

Context: Actor-based programming languages offer many essential features for developing modern distributed reactive systems. These systems exploit the actor model's isolation property to fulfill their performance and scalability demands. Unfortunately, the reliance of the model on isolation as its most fundamental property requires programmers to express complex interaction patterns between their actors to be expressed manually in terms of complex combinations of messages sent between the isolated actors. Inquiry: In the last three decades, several language design proposals have been introduced to reduce the complexity that emerges from describing said interaction and coordination of actors. We argue that none of these proposals is satisfactory in order to express the many complex interaction patterns between actors found in modern reactive distributed systems. Approach: We describe seven smart home automation scenarios (in which an actor represents every smart home appliance) to motivate the support by actor languages for five radically different types of message synchronization patterns, which are lacking in modern distributed actor-based languages. Fortunately, these five types of synchronisation patterns have been studied extensively by the Complex Event Processing (CEP) community. Our paper describes how such CEP patterns are elegantly added to an actor-based programming language. Knowledge: Based on our findings, we propose an extension of the single-message matching paradigm of contemporary actor-based languages in order to support a multiple-message matching way of thinking in the same way as proposed by CEP languages. Our proposal thus enriches the actor-model by ways of declaratively describing complex message combinations to which an actor can respond. Grounding: We base the problem-statement of the paper on an online poll in the home automation community that has motivated the real need for the CEP-based synchronisation operators between actors proposed in the paper. Furthermore, we implemented a DSL -- called Sparrow -- that supports said operators and we argue quantitatively (in terms of LOC and in terms of a reduction of the concerns that have to be handled by programmers) that the DSL outperforms existing approaches. Importance: This work aims to provide a set of synchronization operators that help actor-based languages to handle the complex interaction required by modern reactive distributed systems. To the best of our knowledge, our proposal is the first one to add advanced CEP synchronization operators to the -- relatively simplistic single-message based matching -- mechanisms of most actor-based languages.

Adaptive Fractional-Order Operator Clock Synchronization Algorithm Based on Grey Prediction

As a result of the influence of clock drift and uncertainty delay in synchronous message transmission, the clock synchronization model based on statistical distribution cannot accurately describe clock deviation. This model also requires a large number of timestamp samples that cause a storage occupation issue for wireless sensor nodes with limited resources. The modeling method based on grey prediction has advantages of low sample demand and simple modeling process. However, the accuracy of the existing clock synchronization models needs to be improved. Based on the grey prediction theory, this paper proposes an adaptive fractional-order operator clock synchronization algorithm considering uncertainty delay. First, based on the clock model and clock offset model, the frequency offset between nodes is optimized by taking the mean on the clock frequencies. Second, a grey prediction algorithm based on a fractional-order operator is proposed by estimating the uncertainty delay in message transmission to obtain the clock offset. Finally, the order of the fractional-order accumulation is adjusted adaptively in the grey prediction model according to the collected timestamp sample values so that the estimation of the uncertainty delay is more accurate, thereby improving the accuracy of the clock offset. Compared with the first-order accumulative grey prediction clock synchronization algorithms and timing-sync protocol for sensor networks, the proposed scheme improved the synchronization accuracy by 29.18% and 44.01%, respectively, and reduced the variance of the clock offset by 48.66% and 64.89%. Thus, the proposed algorithm is characterized by improved stability.

Clock-Centric Serial Links for the Synchronization of Distributed Readout Systems

Detector readout systems for medium to large scale physics experiments, and instruments in some other fields as well, are generally composed of multiple front-end digitizer boards distributed over a certain area. Often, this hardware has to be synchronized to a common reference clock with minimal skew and low jitter. Today's mainstream solutions to precise clock distribution and deterministic latency messaging rely on the capabilities of high speed serial transceivers (a.k.a. SerDes) embedded in modern Field Programmable Gate Arrays (FPGAs). An alternative option uses distinct clock and data links. This can potentially reach higher synchronization accuracy, at significant hardware expenses. This work reports some first steps to explore a third scheme for clock and synchronous message distribution. Like the standard approach, the same media is used to convey clock and data, but instead of using today's "data-centric" links where the recovered clock is only a by-product of a SerDes, this paper defines and investigates "clock-centric" links where, at the opposite, a clock is carried by the link, and synchronous data are embedded into it by a modulation technique. After defining the concepts and principles of data-centric links, experimental studies are presented. Finally, the merits and limitations of the proposed approach are discussed.

Performance Optimization for Blockchain-Enabled Distributed Network Function Virtualization Management and Orchestration

Distributed network function virtualization management and orchestration (NFV-MANO) offers a flexible way to manage and orchestrate diversified network services in large-scale Internet of vehicles (IoV). However, it is challenging to manage different services and resources in distributed NFV due to the difficulties of reliable message synchronization among multiple MANO systems. Recently, blockchain technology has emerged to solve the trust and security problems for the interconnections of multiple MANO systems. Moreover, multi-access edge computing (MEC) has become a prospective paradigm shift from the centralized cloud due to its advantages of completing tasks near users. In this work, we propose a blockchain-enabled distributed NFV framework to reach consensus among multiple MANO systems where the computation tasks of the blockchain are processed with MEC. The consensus procedures of MANO systems and blockchain nodes are explained in detail and the representation of the blockchain throughput is given. The blockchain throughput is the number of transactions a blockchain system can handle per second, which is an important evaluation indicator for the performance of a blockchain system. We make decisions for the primary node selection, the MANO system selection and the edge server selection for reaching consensus. Moreover, the blockchain throughput, the processing delay of computation tasks of blockchain and operational costs are jointly considered in the problem formulation. A dueling deep reinforcement learning approach is applied to solve this problem. Simulation results show the effectiveness of the proposed scheme.