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In response to the shortage of skilled workers and the increasing diversity of products and variants, integrating adaptive and flexible mobile manipulators into line-less mobile assembly systems (LMAS) stands out as a promising solution. To fully benefit from these robotic systems in LMAS, offloading computationally intensive tasks from mobile manipulators to edge computing systems is essential. This offloading of computational tasks not only lightens the processing load on individual robots but also enhances AI based perception, improving the overall system capabilities in dynamic manufacturing environments. Achieving these goals requires a robotic edge computing framework that serves as the key to flexible and adaptive mobile manipulation in LMAS. To construct such an edge computing framework, a comprehensive set of building blocks is required. These building blocks include a powerful edge system with high processing power, sensor-equipped mobile manipulators with the ability to perceive the environment, and a robust edge-to-robot connectivity. A comprehensive software stack, including software modules for localization and navigation in dynamic assembly environments, AI perception for precise pose estimation of assembly components, and motion planning for interaction between manipulators and assembly components, is crucial. Furthermore, virtualization techniques, a comprehensive deployment strategy, and a detailed description of robot hardware, site, and resources are essential. The proposed edge computing framework presents a solution that addresses mobile manipulators in LMAS and paves the way towards advanced industrial automation. Through implementation in a research assembly environment, the realized proof-of-concept showcased the feasibility of the proposed edge computing framework in a real-world pick-and-place scenario, highlighting its potential to enhance adaptivity and flexibility. There is a potential to refine and expand the framework to accommodate a broader range of industrial applications and streamline diverse manufacturing processes through the integration of mobile manipulators and edge computing within industrial settings. [ABSTRACT FROM AUTHOR]

In spoken communicative contexts, speakers often convey uncertainty via intonation and through paralinguistic behaviours such as speech rate and gesture—and addressees can use these behaviours to generate inferences about the speaker's epistemic state. In text-based contexts, however, cues of this sort are more restricted. In this study, we examine the expression and reception of epistemic information in the context of real-time written message production. We hypothesised that real-time typing dynamics (like those available in text-based collaborative contexts, such as Google Docs) can function as a rich paralinguistic cue about a partner's epistemic state. In Experiment 1, we collected production data showing that manipulations of typist certainty, instantiated through both the ease of message formulation and repeated experience with the task, are reflected in measures of typing fluency and speed. Then, in Experiment 2, we presented select screen recordings of the typing behaviours from Experiment 1 to a group of independent observers who made epistemic judgements about the typist. Our results show that observable differences in typing speed and fluency contribute to perceptions of typist knowledge and confidence, which has implications for interfaces that enable real-time text-based collaboration. [ABSTRACT FROM AUTHOR]

To enhance communication and collaborative work efficiency in cyber–physical systems (CPSs) within the Industry 4.0 environment, this study investigates a graph-based machine learning approach aimed at optimizing information interaction during multi-party conversations. Devices within CPSs must efficiently exchange information in real time to synchronize operations and responses. This research treats these interactions as intricate graph structures and uses graph learning techniques to accurately identify communication links and dependencies among devices. This improvement leads to more accurate decision-making and smoother operations. Our methodology involves a real-time analysis of structural patterns and node attributes within conversations, improving information flow and comprehension. The empirical findings demonstrate that this approach significantly enhances production efficiency, system adaptability, and minimizes delays attributed to communication misunderstandings. Our method can effectively identify the communication relationships between devices, significantly improving the efficiency and accuracy of information transmission. This improved communication capability leads to an enhanced production efficiency of the entire system. [ABSTRACT FROM AUTHOR]

The 5G core network adopts a Control and User Plane Separation (CUPS) architecture to meet the challenges of low-latency business requirements. In this architecture, a balance between management costs and User Experience (UE) is achieved by moving User Plane Function (UPF) to the edge of the network. However, cross-UPF handover during communication between the UE and the remote server will cause TCP/IP session interruption and affect continuity of delay-sensitive real-time communication continuity. Information-Centric Networks (ICNs) separate identity and location, and their ability to route based on identity can effectively handle mobility. Therefore, based on the 5G-ICN architecture, we propose a seamless mobility support method based on router buffered data (BDMM), making full use of the ICN's identity-based routing capabilities to solve the problem of UE cross-UPF handover affecting business continuity. BDMM also uses the ICN router data buffering capabilities to reduce packet loss during handovers. We design a dynamic buffer resource allocation strategy (DBRAS) that can adjust the buffer resource allocation results in time according to network traffic changes and business types to solve the problem of unreasonable buffer resource allocation. Finally, experimental results show that our method outperforms other methods in terms of average packet delay, weighted average packet loss rate, and network overhead. In addition, our method also has good performance in average handover delay. [ABSTRACT FROM AUTHOR]

Intelligent Transportation Systems are rapidly expanding to meet the growing demand for safer, more efficient, and sustainable transportation solutions. These systems encompass various applications, from traffic management and control to autonomous vehicles, aiming to enhance mobility experiences while addressing urbanization challenges. This paper examines key components of Intelligent Transportation Systems, including Vehicular Ad-hoc Networks, Intelligent Traffic Lights, Virtual Traffic Lights, and Mobility Prediction, emphasizing their role in improving transportation efficiency, safety, and sustainability. It explores recent advancements in communication systems that enable real-time Intelligent Transportation Systems operations, contributing to the realization of environmentally friendly smart cities.Moreover, the paper addresses security challenges associated with Intelligent Transportation Systems deployment, particularly concerning public transit privacy, and presents case studies illustrating the benefits of Intelligent Transportation Systems integration in specific urban areas, emphasizing its role in fostering Sustainable Smart Cities. Additionally, it examines proactive initiatives by automotive manufacturers in adhering to Intelligent Transportation Systems standards, ensuring mutual benefits for drivers and urban centers.

Time-Sensitive Networking (TSN) extends Ethernet bridging with features for deterministic transmission. Periodic streams may be scheduled such that their frames hardly interfere in bridges. Additionally, the Time-Aware Shaper (TAS) can keep egress ports free from other traffic when scheduled traffic arrives. TAS scheduling determines transmission starts of scheduled streams at end stations and configures the TAS in bridges. Most TAS scheduling algorithms disregard jitter and synchronization errors at end stations and bridges, race conditions from simultaneously arriving frames with same egress ports, and hardware-based configuration limits of the TAS. We call the resulting schedules tight schedules (TS). However, all these challenges apply to real hardware bridges. Therefore, we present an algorithm using event times with uncertainty to compute efficient robust schedules (ERS) that respect these constraints. We also propose a repair for existing scheduling approaches and call their output naïve robust schedules (NRS). We evaluate and compare their bandwidth usage and stream admission with those of TS. ERS are more efficient than NRS, and the performance gap between ERS and TS quantifies the price for robust schedules. Moreover, the presented algorithm for ERS computes significantly faster than four well-known methods for TS, and it can solve larger problem instances.

Achieving reliable low-latency streaming on real-time immersive services that require seamless interaction has been of increasing importance recently. To cope with such an immersive service requirement, IETF and 3GPP defined Low Latency, Low Loss, and Scalable Throughput (L4S) architecture and terminologies to enable delay-critical applications to achieve low congestion and scalable bitrate control over 5G. With low-latency applications in mind, this paper presents a cloud-based streaming system using WebRTC for real-time communication with an adaptable L4S congestion control (aL4S-CC). aL4S-CC is designed to prevent the target service from surpassing a required end-to-end latency. It is evaluated against existing congestion controls GCC and ScreamV2 across two configurations: 1) standard L4S (sL4S) which has no knowledge of Explicit Congestion Notification (ECN) marking scheme information; 2) conscious L4S (cL4S) which recognizes the ECN marking scheme information. The results show that aL4S-CC achieves high link utilization with low latency while maintaining good performance in terms of fairness, and cL4S improves sL4S's performance by having an efficient trade-off between link utilization and latency. In the entire simulation, the gain of link utilization on cL4S is 1.4%, 4%, and 17.9% on average compared to sL4S, GCC, and ScreamV2, respectively, and the ratio of duration exceeding the target queuing delay achieves the lowest values of 1% and 0.9% for cL4S and sL4S, respectively.

The development of new technological applications is driving the need for deterministic network communication that exhibits reliable behavior. This is particularly relevant for applications like automation and autonomous vehicles, which require real-time network responsiveness. This has led to the development of various technologies, including Time-Sensitive Networking (TSN). Recent studies have explored the optimization of scheduling and routing in TSN, as this is crucial for meeting TSN’s objectives. Current methods primarily focus on scheduling Time-Triggered (TT) transmissions, often overlooking the scheduling of lower-priority traffic types. Many of these methods do not optimize routing, and only a few consider reliability. In this paper, we present the Optimized Hybrid Deterministic Scheduling and Routing Plus (OHDSR+) approach. This method prioritizes communications, optimizing both scheduling and routing of TT communications, while also addressing the requirements of lower-priority best-effort (BE) communications, and ensuring the reliability of TT communications. We evaluated our approach using various problem instances. The results demonstrate our approach’s effectiveness in managing different traffic types and ensuring reliable transmission for TT traffic. Our model achieves significant improvements compared to the state-of-the-art REU-CP-R method, with reductions in total latency of up to 1.03%, total response time of up to 34.70%, and scheduling response time of up to 63.97%. Notably, OHDSR+ exhibits superior scalability, successfully finding solutions for all tested network sizes with a 100% success rate, while REU-CP-R achieved only an 87.5% success rate. This highlights OHDSR+’s ability to provide optimal solutions for networks of various sizes with minimal latency and response times.

Introduction/purpose: All data exchanged over the Internet as well as other computer networks should be considered exposed to various types of security threats. In light of this, the transmission of voice over applications that do not use any type of crypto-protection allows anyone to discern the content of communication. Since voice transmission requires as little delay as possible, various protocols are used to enable crypto protected real-time communication. This paper presents one solution in a desktop application variant. Methods: The essence in voice exchange systems as well as in other systems where real-time communication is necessary is the establishment of a crypto-protected session which is a virtual secure channel for communication to which only the communicating parties have access. Voice sessions in the application are established with the SIP (Session Initiation Protocol) protocol. The sessions are further protected using the ZRTP (Zimmerman Real-time Transport Protocol) protocol. FusionPBX was used as the SIP server (registrar) for testing purpouses. The application is developed in C++ language using the Qt framework. Results: The final version of the application demostrates that ZRTP and SIP protocols are well suited for establishing crypto protected voice communications with low delay. Conclusion: This solution provides cryptographic functions for data secrecy and the management of cryptographic keys. Improving the solution with digital signatures and certificates will result in additional cryptographic functions: data integrity and personal identification. With this improvement, this solution will be able to withstand modern security threats with low delay.

Introduction/purpose: This paper conducts a comprehensive analysis of a potential implementation of Voice over Internet Protocol (VoIP) systems, focusing on network architecture, VoIP phones, and servers. The study explores potential vulnerabilities and proposes solutions. The paper concludes by advocating for a holistic approach to securing VoIP systems, incorporating supplementary services to ensure the confidentiality, integrity, and availability of voice communications in the digital landscape. Methods: Review of the underlying theory, analysis of the end-user needs and potential solutions, practical viability assesment. Results: The theoretical points discussed were proven in practice, using commercially available resources. Communication was established in an expected manner. Conclusions: Implementing solutions similar to the one presented in the paper would be a relatively inexpensive way to make diverse improvements to the operation of tactical level units, both in peacetime and during war.

Attendance systems are a critical tool to track attendance in various organizations. The integration of Internet of Things (IoT) technology has brought new advancements to attendance systems, with the inclusion of biometric sensors. Biometric sensors, such as fingerprint or facial recognition, ensure the accuracy of attendance records by verifying the identity of the individual. This paper focuses on the implementation of a smart attendance system that leverages the latest IoT technology. The system utilizes a compact and powerful microcontroller board, the ESP32, with in-built Bluetooth and Wi-Fi module for real-time communication through webSocket. The ESP32 also has a low power functionality, operating on a voltage of 3.3V, making it an ideal choice for IoT applications. By combining biometric sensors with webSocket, an instant communication protocol, attendance systems can deliver real-time updates on employee attendance. This allows for increased efficiency, accountability, and security, making IoT-enabled attendance systems an ideal solution for modern businesses. [ABSTRACT FROM AUTHOR]

This research delves into the transformation of agriculture through precision techniques and advanced technology. The focus is on an autonomous AI weed cutter, utilising TinyML, the ESP32 camera module, and a proximity sensor to revolutionise weed management. The study introduces a holistic approach by integrating TinyML's advanced computer vision techniques for real-time weed detection and classification. The ESP32 camera captures field images, processed by TinyML algorithms to identify crops and weeds accurately. Augmenting visual perception, a proximity sensor ensures safe navigation, detecting obstacles and maintaining safe distances from crops. This fusion empowers the system to make informed decisions. Field trials confirm exceptional weed detection and removal accuracy. Integration of TinyML-based vision, ESP32 camera tech, and the proximity sensor optimises efficiency, adaptability, and safety. Economic and environmental analyses highlight benefits: sustainable practices, potential yield increase, and reduced herbicide usage. In conclusion, this research showcases an autonomous AI weed cutter, seamlessly integrating TinyML, ESP32, and a proximity sensor. This technology amalgamation offers precise weed management, boosting efficiency, reducing environmental impact, and promoting sustainability in agriculture—a pivotal stride toward precision farming's future. [ABSTRACT FROM AUTHOR]

Introduction/purpose: This paper conducts a comprehensive analysis of a potential implementation of Voice over Internet Protocol (VoIP) systems, focusing on network architecture, VoIP phones, and servers. The study explores potential vulnerabilities and proposes solutions. The paper concludes by advocating for a holistic approach to securing VoIP systems, incorporating supplementary services to ensure the confidentiality, integrity, and availability of voice communications in the digital landscape. Methods: Review of the underlying theory, analysis of the end-user needs and potential solutions, practical viability assesment. Results: The theoretical points discussed were proven in practice, using commercially available resources. Communication was established in an expected manner. Conclusions: Implementing solutions similar to the one presented in the paper would be a relatively inexpensive way to make diverse improvements to the operation of tactical level units, both in peacetime and during war. [ABSTRACT FROM AUTHOR]

Introduction/purpose: All data exchanged over the Internet as well as other computer networks should be considered exposed to various types of security threats. In light of this, the transmission of voice over applications that do not use any type of crypto-protection allows anyone to discern the content of communication. Since voice transmission requires as little delay as possible, various protocols are used to enable crypto protected real-time communication. This paper presents one solution in a desktop application variant. Methods: The essence in voice exchange systems as well as in other systems where real-time communication is necessary is the establishment of a crypto-protected session which is a virtual secure channel for communication to which only the communicating parties have access. Voice sessions in the application are established with the SIP (Session Initiation Protocol) protocol. The sessions are further protected using the ZRTP (Zimmerman Real-time Transport Protocol) protocol. FusionPBX was used as the SIP server (registrar) for testing purpouses. The application is developed in C++ language using the Qt framework. Results: The final version of the application demostrates that ZRTP and SIP protocols are well suited for establishing crypto protected voice communications with low delay. Conclusion: This solution provides cryptographic functions for data secrecy and the management of cryptographic keys. Improving the solution with digital signatures and certificates will result in additional cryptographic functions: data integrity and personal identification. With this improvement, this solution will be able to withstand modern security threats with low delay [ABSTRACT FROM AUTHOR]

In an ever-evolving technological landscape, addressing the performance challenges of real-time communication protocols is crucial. Real-time communication, facilitated by streaming media protocols, utilizes peer-to-peer or client-server models to enhance Quality of Service (QoS). WebRTC (Web Real-Time Communication) stands as a widely adopted, browser-based, opensource, peer-to-peer protocol, offering real-time media transmission through JavaScript APIs without third-party plugins. This paper presents an in-depth performance evaluation of a WebRTC-based video conferencing system using Socket.io services on a Node.js server. Our research expands on recent studies by introducing a comprehensive set of performance parameters, including Processing delay, CPU Utilization, Latency, Jitter, and Packet Loss, and packet delay. Our findings indicate that WebRTC performs exceptionally well within specific latency thresholds. However, scalability concerns emerge when a large number of clients are introduced, especially in bandwidth-constrained environments. [ABSTRACT FROM AUTHOR]

Broadband powerline communication is a technology developed mainly with consumer applications and bulk data transmission in mind. Typical use cases include file download, streaming, or last-mile internet access for residential buildings. Applications gaining momentum are smart metering and grid automation, where response time requirements are relatively moderate compared to industrial (real-time) control. This work investigates to which extent G.hn technology, with existing, commercial off-the-shelf components, can be used for real-time control applications. Maximum packet rate and latency statistics are investigated for different G.hn profiles and MAC algorithms. An elevator control system serves as an example application to define the latency and throughput requirements. The results show that G.hn is a feasible technology candidate for industrial IoT-type applications if certain boundary conditions can be ensured. [ABSTRACT FROM AUTHOR]

A high-fidelity optical fiber microphone (HF-OFM) with hybrid frequency and fast response is theoretically and experimentally demonstrated by the nanofabrication techniques for real-time communication, which consists of a graphene oxide (GO) film, an Au nanocoating, and an air cavity. The internal stress of the film is increased by the method of mechanical tensile preparation, and the microphone response flatness is improved. Meanwhile, the structural design of the 3 nm Au nanocoating improves the acoustic pressure detection sensitivity by 2.5 times by increasing the reflectivity. The experimental result shows that single, dual, and triple frequency acoustic signal detection in the frequency range of 0.1 kHz–20 kHz are achieved with acoustic pressure sensitivities of 9.64, 9.66, and 8.9 V/Pa, as well as flat frequency response (

The 5G core network adopts a Control and User Plane Separation (CUPS) architecture to meet the challenges of low-latency business requirements. In this architecture, a balance between management costs and User Experience (UE) is achieved by moving User Plane Function (UPF) to the edge of the network. However, cross-UPF handover during communication between the UE and the remote server will cause TCP/IP session interruption and affect continuity of delay-sensitive real-time communication continuity. Information-Centric Networks (ICNs) separate identity and location, and their ability to route based on identity can effectively handle mobility. Therefore, based on the 5G-ICN architecture, we propose a seamless mobility support method based on router buffered data (BDMM), making full use of the ICN’s identity-based routing capabilities to solve the problem of UE cross-UPF handover affecting business continuity. BDMM also uses the ICN router data buffering capabilities to reduce packet loss during handovers. We design a dynamic buffer resource allocation strategy (DBRAS) that can adjust the buffer resource allocation results in time according to network traffic changes and business types to solve the problem of unreasonable buffer resource allocation. Finally, experimental results show that our method outperforms other methods in terms of average packet delay, weighted average packet loss rate, and network overhead. In addition, our method also has good performance in average handover delay.

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System-of-systems (SoS) have recently been used in several applications and scenarios in the field of safety, defense, and healthcare. In an SoS environment, the entire system is divided into sub-systems, which provides more flexibility and reduces the management cost of the entire system. SoS have been widely used in healthcare monitoring services, where patients are provided with medical sensors that send their medical measurements to a remote unit for further processing and decision-making. These sensors communicate with an access point using the wireless channel, which gives patients flexibility in mobility and makes the monitoring system more convenient and comfortable. However, sending data over the wireless channel presents several challenges, such as contention between the different sensors in accessing the channel and the bit errors associated with the noisy wireless channel. In this paper, an SoS healthcare monitoring framework is proposed, where a wireless communication protocol is proposed that addresses the sensors’ node network access contention and mitigates the bit errors of the communication channel by providing forward error correction bits to the transmitted packets. In addition, the protocol takes into consideration the sensors’ importance and criticality, such that more important sensors are given more network access time and more error correction bits, which in turn results in a robust transmission process with low transmission delay. The simulation results show the proposed wireless communication protocol’s effectiveness in lowering the packet loss, giving higher priority and having higher throughput for the more critical sensors.

Real-time communications characterized by low-latency, deterministic, and reliable behavior are crucial for the advancement of emerging technologies. Consequently, Time-Sensitive Networking (TSN) has been developed to address the distinct demands of sectors such as automation and autonomous vehicles applications. This is currently achieved through various methods that emphasize the scheduling of critical data traffic. However, many of these methods determine routes independently, potentially impacting the schedulability of transmissions. Additionally, there is a noticeable lack of emphasis on the scheduling and routing of low-priority transmissions within TSN. In this paper, we introduce the Optimized Hybrid Deterministic Scheduling and Routing (OHDSR) approach. This method takes into account the priority of communications to jointly optimize the scheduling and routing of Time-Triggered (TT) communications, while also catering to low-priority Best-Effort (BE) communications. Extensive experimental evaluations show the high efficiency of our proposed method. It ensures not only the prompt delivery of TT communications but also the delivery of BE communications within suitable time frames, with a maximum difference of 14.29% from TT communications, meeting their respective deadlines. Moreover, the evaluation demonstrates the high scalability of the proposed approach, providing improved response times compared to the latest work for both routing and scheduling.

English as a foreign language (EFL) instruction places special emphasis on students' active participation in class discussions. EFL learners encounter obstacles which prevent them from oral participation in the classroom. The purpose of this research is to discover why EFL students are not more engaged in class, as well as recognizing factors that impede students' class engagement. Moreover, the study aims at casting the light on the Techniques and Strategies for Enhancing Students Participation. Data was gathered through an interview in this descriptive-analytical study and analyzed using SPSS. The samples of the study consist of forty EFL professors from two Saudi universities. Findings from the study urged educators to help their students form positive self and social perceptions. Better class participation can be achieved through good rapport and the enhancement of the targeted teaching practices. The study concludes that EFL students are often disinclined to be engaged in oral class participation due to a mélange of a poorly managed classroom, language anxiety, and lack of vocabulary. [ABSTRACT FROM AUTHOR]

Terahertz (THz) communication is widely regarded as the key component of future 6G mobile communication systems. Through comparative analysis of some of the main existing technical routes of THz up-conversion and down-conversion in THz wireless communication systems, a novel ultra-wideband (UWB) fiber-THz-fiber seamlessly converged real-time architecture, which utilizes the commercially mature digital coherent optical module to realize ultrahigh-capacity THz real-time wireless communication, is proposed in this study. (1) The proposed architecture employs the dual-polarization photonic up-conversion technique for THz generation and hybrid optoelectronic down-conversion technique for THz reception to facilitate the seamless integration between optical fiber and THz communications. (2) Because of the limited bandwidth of optoelectronic devices, multidimensional modulation techniques are adopted for UWB THz signals to improve spectral efficiency and transmission capacity. (3) An intelligent nonlinear joint compensation technique based on the deep neural network, which can effectively improve the signal-to-noise ratio of the time-varying hybrid fiber-THz-fiber channel, is proposed. Based on the investigations of the aforementioned key techniques, we, for the first time, realize the photonics-assisted record-high 100/200 GbE real-time THz wireless transmission at 360–430 GHz band, the capacity of which is 10–20 times higher than that of 5G. The proposed fiber-THz-fiber architecture can realize the smooth conversion between high-speed THz and lightwave signals. Moreover, the architecture can significantly reduce the research difficulty and development cost, thereby considerably accelerating the commercialization of 6G THz technology by thoroughly reusing commercial digital coherent optical module (DCO) modules, which are compatible with the physical layer transmission protocols, such as IEEE 802.3 and ITU-T G.798. Finally, this study also introduces some potential directions of research and development for higher-capacity, longer-distance, and more-integrated fiber-THz-fiber seamless communication. [ABSTRACT FROM AUTHOR]

Deaf-mute individuals encounter substantial difficulties in their daily lives due to communication impediments. These individuals may encounter difficulties in social contact, communication, and capacity to acquire knowledge and engage in employment. Recent studies have contributed to decreasing the gap in communication between deaf-mute people and normal people by studying sign language interpretation. In this paper, a real-time Arabic avatar system is created to help deaf-mute people communicate with other people. The system translates text or spoken input into Arabic Sign Language (ArSL) movements that the avatar makes using deep-learning-based translation. The dynamic generation of the avatar movements allows smooth and organic real-time communication. In order to improve the precision and effectiveness of ArSL translation, this study depends on a state-of-the-art deep learning model, which makes use of YOLOv8, to recognize and interpret sign language gestures in realtime. The avatar is trained on three diverse datasets of Arabic sign language images, namely Sign-language-detection Image (SLDI), Arabic Sign Language (ArSL), and RGB Arabic Alphabet Sign Language (AASL), enabling it to accurately capture the nuances and variations of hand movements. The best recognition accuracy of the suggested approach was 99.4% on the AASL dataset. The experimental results of the suggested approach demonstrate that deaf-mute people will be able to communicate with others in Arabic-speaking communities more effectively and easily. [ABSTRACT FROM AUTHOR]

Broadband powerline communication is a technology developed mainly with consumer applications and bulk data transmission in mind. Typical use cases include file download, streaming, or last-mile internet access for residential buildings. Applications gaining momentum are smart metering and grid automation, where response time requirements are relatively moderate compared to industrial (real-time) control. This work investigates to which extent G.hn technology, with existing, commercial off-the-shelf components, can be used for real-time control applications. Maximum packet rate and latency statistics are investigated for different G.hn profiles and MAC algorithms. An elevator control system serves as an example application to define the latency and throughput requirements. The results show that G.hn is a feasible technology candidate for industrial IoT-type applications if certain boundary conditions can be ensured.

Dependable, safety-critical real-time (SCRT) systems are becoming increasingly important and complex. Examples of such systems are autonomous or self-driving cars which are poised to revolutionise the transport industry. A critical part of these SCRT systems is the network communication protocol that is used by components in an SCRT system to exchange data. Communication protocols for SCRT systems are required to exhibit predictable, worst-case execution times and thus have to be designed in a more static and less flexible way. To ensure this predictability, current state-of-art communication protocols for SCRT systems are based on the Time-Triggered Architecture (TTA), where static and equal-length time-slots are used for all nodes to access the communication channel, irrespective of the size of their transmission payload. This determinism forms the basis of predictable timing, behaviour and fault tolerance. However, this determinism comes at the cost of poor channel and bandwidth utilisation, which hinders the development of SCRT systems. In this paper, we propose a more flexible approach, INCUS+, that allocates the slot length of a node based on its transmission requirements in a Time Division Multiple Access (TDMA) round. We achieve this while retaining the level of dependability required for SCRT systems and ensuring fail-silence. We validate this through formal verification of the timing parameters for the transmission windows of all participating nodes as well as independent bus guardians. Our design exhibits a significant improvement in bandwidth and channel utilisation, as we demonstrate in an autonomous vehicle case study.

Due to recent cyberattacks on the Cyber-Physical Systems, the traditional security schemes face difficulties in dealing with such attacks as the attackers nowadays have adopted many intelligent mechanisms involving advanced information and communication technologies to launch attacks. This recent type of attack provides a significant impact on the resiliency of the software-defined networks. In this paper, we present a real-time delay attack on fault-resilient software-defined networks. The main objective of the time delay attack is to reduce the resiliency in the SDN-RM by adding a delay in the LLDP packets in the OpenFlow Switch. This addition of delay causes degradation in the network performance resulting in a low success rate in the SDN-RM mechanisms. In this paper, we present a machine learning-based detection system for detecting the attacks. The integration of machine learning techniques with network resilience solutions can effectively address the issue of predicting and classifying the LLDP packets that are delayed at a particular switch. Another issue is the detection of the malicious switch at the controller side which results in the improvement of the resiliency in SDN-RM. We propose a machine learning solution to detect the anomalies that are present in the topology and can be detected at the controller side. We use machine learning models such as k-nearest neighbors, support vector machines (SVM), Random Forest, and decision trees to detect the poisonous switches. The delay-based time attack detection system (DTA-DS) helps the controller to take a reactive decision to improve resilience by detecting poisonous network switches. With the help of the preventive approach, we achieve high-fault resiliency in fault resilient-based software-defined networks. [ABSTRACT FROM AUTHOR]

Marine submerged buoys can effectively obtain various parameters of seawater, which plays an important role in the research of marine physical phenomena, marine environmental changes, and climate change. However, traditional self-contained submerged buoys usually work underwater at a depth of about 100 m, and the observation data cannot be obtained before their recovery, which cannot satisfy the needs of real-time data acquisition for marine scientific research. To solve this problem, this paper proposes a real-time communication subsurface mooring system that consists of a satellite communication buoy (SCB), conductivity–temperature–depth sensors (CTD), and an inductive coupling mooring cable. The underwater inductive coupling link collects the data from the underwater sensors and transmit it to the SCB. Then, the data will be transmitted to the station receiver via satellite communication module integrated into the SCB. In order to ensure a high success rate of data recovery, the stress analysis and hydrodynamic simulation of the SCB were carried out in this paper. The results show that the SCB maintained a relatively stable attitude in the 3–4 sea state. The attitude data obtained from the subsequent sea trial was consistent with the simulation results, and the success rate of satellite communication during this period was more than 95%. In this paper, a modular embedded hardware circuit was designed to meet the functional requirements of the subsurface mooring system. An efficient data recovery strategy was also developed, which ensured that the average power consumption of the system was low and the success rate of data recovery is not less than 90% when operating in the severe sea state for a long time. The system underwent sea trials in the South China Sea for more than 3 months from the end of 2021 to the beginning of 2022. It transmitted more than 2034 sets of seawater profile temperature, salinity, and depth data in real-time, with a success rate of over 91% of the total sample data. The CTD data returned in real-time from our system is consistent with the data of the HYCOM and World Ocean Atlas (WOA), and a cyclonic mesoscale eddy was detected in the operation area. [ABSTRACT FROM AUTHOR]

It is essential to support real-time communication in networked control systems, such as automotive systems or smart factories. Several studies have been conducted to schedule real-time flows by adjusting their priorities using software-defined networking (SDN). However, because its architecture was not initially designed for real-time communication, unexpected challenges may occur if it is not utilized carefully. In particular, because SDN does not provide an atomic method for priority adjustment, some flows may violate their timing constraints by receiving additional interference during priority adjustment. In this letter, we propose novel schemes to update the flow priorities safely in SDN-based real-time systems. To this end, we first analyze such problems through two types of cases. Then, we develop schemes that determine a safe procedure for priority adjustment and synchronize the priority settings of all switches. By network emulations, we demonstrate that the above problem occurs in 149 out of 300 flow sets, but our schemes can effectively prevent all of them. [ABSTRACT FROM AUTHOR]

The state-of-the-art digital signatures incur undesirable delays, hence are impractical for time-stringent Industrial Control Systems (ICSs). The recent revision to IEC 62351–6 standard stepped back from digital signatures in favor of symmetric key based solutions, thereby sacrificing key properties, e.g., scaling well for multiple destinations, easy key distribution and management, public verifiability, and non-repudiation. Inspired by the Online/Offline signatures, this paper presents a new digital signature model to provide the key properties of digital signatures within the delay requirements, hinting that this step back can be avoided. The Online/Offline signatures concept divides the signature generation into two phases; offline (before the message is given), online (using the outputs of the former for faster signing after the message is given). The conventional solutions following this concept potentially reduce the delay, yet do not meet IEC 61850 delay requirements as they still involve expensive operations in the online phase, and their offline phase hinders throughput. This paper introduces Less-online/More-offline Signatures (LoMoS) to enable minimal end-to-end delay and high message throughput. LoMoS entails avoiding expensive operations entirely during the online phase. We present a construction that converts any digital signature scheme into LoMoS, retains its properties, and unlike existing solutions, benefits from shorter messages. [ABSTRACT FROM AUTHOR]

A time-sensitive network (TSN) extends the conventional Ethernet to support time-sensitive data flow. Thus, it enables simultaneous transmission of high reliability (HR) flow, medium reliability (MR) flow, and low reliability (LR) flow on the same network, thereby improving the reliability of data transmission. A TSN is a symmetric network that connects sensors and other facilities. As a backbone network, it can efficiently connect the underlying sensors and other levels of facilities, as well as ensure the quality of service of the network. For modern supervisory control and data acquisition (SCADA) systems, several types of sensors are widely used. The acquisition cycle of sensors for different purposes varies significantly from milliseconds to seconds. Moreover, these data also have different real-time requirements. Based on satisfiability modulo theories (SMT), this study proposes a TSN routing and scheduling method by adding related scheduling constraints. Compared with other methods, the proposed method can realize the routing and scheduling of hybrid flow in a hyper period and consider MR flow and LR flow, which improves the feasibility and certainty of data flow interaction between substations. [ABSTRACT FROM AUTHOR]

[Introduction] Aiming at the problems of business concentration, fault decision delay and high data transmission overhead for power grid dispatching control center, a fast and intelligent information processing method for fault recorder master station based on edge computing was proposed. [Method] Based on the edge computing design principle and overall framework of fault recording information processing, we used DataSocket asynchronous parallel real-time communication and Hadoop distributed storage scheme to ensure stable transmission, fast storage and retrieval for data, adopted improved SSDA algorithm to sift out the fault information to analysis quickly, and submitted the fault analysis results electronically. [Result] The experimental results show that this method has good application effects in mass data processing, rapid fault diagnosis, auxiliary decision support, etc. It can alleviate the pressure of information processing of dispatching control center and shorten the time delay of fault decision-making. [Conclusion] The proposed method is effective and feasible to handle massive fault recording information reliably combined with the Guangxi power grid operation case.

Drone technology is considered the most effective solution for the improvement of various industrial fields. As a delivery service, drones need a secure communication system that is also able to manage all of the information data in real-time. However, because the data transmission process occurs in a wireless network, data will be sent over a channel that is more unstable and vulnerable to attack. Thus, this research, purposes a Forward Prediction Scheduling-based Stream Control Transmission Protocol (FPS-SCTP) scheme that is implemented on drone data transmission system. This scheme supports piggybacking, multi-streaming, and Late Messages Filter (LMF) which will improve the real-time transmission process in IEEE 802.11 wireless network. Meanwhile, on the cybersecurity aspect, this scheme provides the embedded option feature to enable the encryption mechanism using AES and the digital signatures mechanism using ECDSA. The results show that the FPS-SCTP scheme has better network performance than the default SCTP, and provides full security services with low computation time. This research contributes to providing a communication protocol scheme that is suitable for use on the internet of drones’ environment, both in real-time and reliable security levels.

MQTT is one of the most popular application-layer protocols used in the scope of the Internet-of-Things (IoT) and Industrial-Internet-of-Things (IIoT), given its suitability for resource-constrained embedded systems. However, MQTT Quality-of-Service policies do not support timeliness requirements, which is common in IIoT. The literature reports several research works that address this limitation, but they are limited in scope (e.g., improvements in the broker's internal operation, control of the publisher's data rate, and path optimizations). Conversely, this paper presents a comprehensive architectural approach, proposing a set of extensions to the MQTT protocol that allow applications to explicitly specify real-time requirements and instantiate corresponding network reservations to enforce the desired temporal behavior. Such reservations are enforced via Software Defined Networking, specifically the OpenFlow protocol, but other protocols that allow bandwidth reservations, e.g., TSN, can also be used. This paper presents the proposed system architecture together with extensive emulation and implementation results that validate the feasibility of the approach, showing that time-sensitive MQTT traffic can be effectively segregated and prioritized to meet application-defined real-time requirements. Using several combinations of network topologies and load levels and comparing to the absence of the proposed real-time mechanisms, both average and worst-case latencies of the time-sensitive traffic decreased to approximately half, while for the normal traffic, they increased by approximately 10%. [ABSTRACT FROM AUTHOR]

With increasing requirements for the amount of data transmitted by train communication networks (TCN), the industrial Ethernet has become a solution with large transmission rates and high compatibility. To ensure safety and real-time communication, the delay of data transmission must be strictly limited in TCN. However, the delay caused by data transmission conflicts is still a problem in the current Ethernet research, which cannot meet the demands of real-time transmission between network devices. To solve the time-delay problem, an improved adaptive genetic algorithm (IAGA) for topology optimization is proposed, in which a new optimization model is established based on the train Ethernet topology. Compared with two traditional algorithms in solving the optimization model, the IAGA achieved better performance in terms of convergence speed and solution accuracy. To verify the effect of the optimized model, the theoretical calculation, simulation, and experiment based on a communication platform are carried out for the real-time index. Experimental results indicated that the end-to-end delay of the optimized network is significantly reduced. In designing and solving the topology optimization problem of TCN, the proposed model and algorithm effectively realized real-time improvement of the data transmission. [ABSTRACT FROM AUTHOR]

Industry 4.0 and Autonomous Driving are emerging resource-intensive distributed application domains that deal with open and evolving environments. These systems are subject to stringent resource, timing, and other non-functional constraints, as well as frequent reconfiguration. Thus, real-time behavior must not preclude operational flexibility. This combination is motivating ongoing efforts within the Time Sensitive Networking (TSN) standardization committee to define admission control mechanisms for Ethernet. Existing mechanisms in TSN, like those of AVB, its predecessor, follow a distributed architecture that favors scalability. Conversely, the new mechanisms envisaged for TSN (IEEE 802.1Qcc) follow a (partially) centralized architecture, favoring short reconfiguration latency. This paper shows the first quantitative comparison between distributed and centralized admission control architectures concerning reconfiguration latency. Here, we compare AVB against a dynamic real-time reconfigurable Ethernet technology with centralized management, namely HaRTES. Our experiments show a significantly lower latency using the centralized architecture. We also observe the dependence of the distributed architecture in the end nodes' performance and the benefit of having a protected channel for the admission control transactions.

In this article, we provide the research community with a dataset for the buffering delays that data packets experience at the TCP sending side in the realm of Cyber-Physical Systems (CPSs) and IoT. We focus on the buffering that occurs at the sender side due to the the adverse interaction between the Nagle algorithm and the delayed acknowledgement algorithm, which both were originally introduced into TCP to prevent sending out many small-sized packets over the network. These two algorithms are turned on (enabled) by default in most operating systems.The dataset is collected using four real-life operating systems: Windows, Linux, FreeBSD, and QNX (a real-time operating system). In each scenario, there are three separate different (virtual) machines running various operating systems. One machine, or an end-host, acts a data source, another acts as a data sink, and a third acts a network emulator that introduces artificial propagation delays between the source and the destination.To measure buffering delay at the sender side, we record for each sent packet the two time instants: when the packet is first generated at the application layer, and when it is actually sent on the physical network. In each case, 10 different independent experiment replications/runs are executed.Here, we provide the full distribution of all delay samples represented by the cumulative distribution function (CDF), which is expressed mathematically byFX(x)=P(X≤x),where x is the delay measured in milliseconds, and P is the probability operator.The data exhibited here gives an impression of the amount and scale of the delay occurring at sender-side in TCP. More importantly, the data can be used to investigate the degree these delays affect the performance of cyber-physical systems and IoT or other real-time applications employing TCP.

Optimization algorithms/techniques such as genetic algorithm, particle swarm optimization, and Gaussian process have been widely used in the accelerator field to tackle complex design/online optimization problems. However, connecting the algorithm with the optimization problem can be difficult, as the algorithms and the problems may be implemented in different languages, or they may require specific resources. We introduce an optimization platform named Teeport that is developed to address the above issues. This real-time communication-based platform is designed to minimize the effort of integrating the algorithms and problems. Once integrated, the users are granted a rich feature set, such as monitoring, controlling, and benchmarking. Some real-life applications of the platform are also discussed.

Marine submerged buoys can effectively obtain various parameters of seawater, which plays an important role in the research of marine physical phenomena, marine environmental changes, and climate change. However, traditional self-contained submerged buoys usually work underwater at a depth of about 100 m, and the observation data cannot be obtained before their recovery, which cannot satisfy the needs of real-time data acquisition for marine scientific research. To solve this problem, this paper proposes a real-time communication subsurface mooring system that consists of a satellite communication buoy (SCB), conductivity–temperature–depth sensors (CTD), and an inductive coupling mooring cable. The underwater inductive coupling link collects the data from the underwater sensors and transmit it to the SCB. Then, the data will be transmitted to the station receiver via satellite communication module integrated into the SCB. In order to ensure a high success rate of data recovery, the stress analysis and hydrodynamic simulation of the SCB were carried out in this paper. The results show that the SCB maintained a relatively stable attitude in the 3–4 sea state. The attitude data obtained from the subsequent sea trial was consistent with the simulation results, and the success rate of satellite communication during this period was more than 95%. In this paper, a modular embedded hardware circuit was designed to meet the functional requirements of the subsurface mooring system. An efficient data recovery strategy was also developed, which ensured that the average power consumption of the system was low and the success rate of data recovery is not less than 90% when operating in the severe sea state for a long time. The system underwent sea trials in the South China Sea for more than 3 months from the end of 2021 to the beginning of 2022. It transmitted more than 2034 sets of seawater profile temperature, salinity, and depth data in real-time, with a success rate of over 91% of the total sample data. The CTD data returned in real-time from our system is consistent with the data of the HYCOM and World Ocean Atlas (WOA), and a cyclonic mesoscale eddy was detected in the operation area.

Traceability, namely the ability to access information about a product and its movement across all stages of the supply chain, has been emerged as a key criterion of a product's quality and safety. Managing fresh products, such as fruits and vegetables, is a particularly complicated task, since they are perishable with short shelf lives and are vulnerable to environmental conditions. This makes traceability of fresh produce very significant. The present study provides a brief overview of the relative literature on fresh produce traceability systems. It was concluded that the commercially available traceability systems usually neither cover the entire length of the supply chain nor rely on open and transparent interoperability standards. Therefore, a user-friendly open access traceability system is proposed for the development of an integrated solution for traceability and agro-logistics of fresh products, focusing on interoperability and data sharing. Various Internet of Things technologies are incorporated and connected to the web, while an android-based platform enables the monitoring of the quality of fruits and vegetables throughout the whole agri-food supply chain, starting from the field level to the consumer and back to the field. The applicability of the system, named AgroTRACE, is further extended to waste management, which constitutes an important aspect of a circular economy. [ABSTRACT FROM AUTHOR]

In vehicular ad hoc networks (VANETs), the topology information (TI) is updated frequently due to vehicle mobility. These frequent changes in topology increase the topology maintenance overhead. To reduce the control message overhead, cluster-based routing schemes are proposed. In clusterbased routing schemes, the nodes are divided into different virtual groups, and each group (logical node) is considered a cluster. The topology changes are accommodated within each cluster, and broadcasting TI to the whole VANET is not required. The cluster head (CH) is responsible for managing the communication of a node with other nodes outside the cluster. However, transmitting real-time data via a CH may cause delays in VANETs. Such real-time data require quick service and should be routed through the shortest path when the quality of service (QoS) is required. This paper proposes a hybrid scheme which transmits time-critical data through the QoS shortest path and normal data through CHs. In this way, the real-time data are delivered efficiently to the destination on time. Similarly, the routine data are transmitted through CHs to reduce the topology maintenance overhead. The work is validated through a series of simulations, and results show that the proposed scheme outperforms existing algorithms in terms of topology maintenance overhead, QoS and real-time and routine packet transmission. [ABSTRACT FROM AUTHOR]

Adapting to a dynamic environment is a critical challenge in deploying robust systems that will be tasked with transmitting media streams in 5G networks. The Web Real-Time Communication (WebRTC) protocol is one of the most popular solutions for real-time communication, providing sub-second latency. This paper deals with a model-free Deep Reinforcement Learning approach designed to improve the quality of user experience by controlling the data rate of media streams transmitted in the uplink direction by a moving, remote-controlled device. The model incorporates WebRTC-compliant metrics to facilitate its integration into real-world applications and aims to maximize the value of a reward function specifically designed to match user perception of video streams. Training and evaluation are performed in an active, online manner within a 5G simulation environment based on the OMNeT++ network simulator, with the addition of key WebRTC mechanisms. The results are compared to the Google Congestion Control algorithm, a baseline WebRTC rate adaptation mechanism. The results, validated on different scenarios, demonstrate the ability of the proposed Deep Reinforcement Learning model to maintain higher rates at comparable levels of loss rate and delay times to the baseline, thus providing a better quality of experience for an operator in the remote center, resulting in the more reliable control of the device. [ABSTRACT FROM AUTHOR]

The future manufacturing environment is foreseen to be increasingly diverse with multi-vendor industrial wireless devices deployed in the same geographical area. Thus, effective medium resource sharing mechanisms are urgently needed to enable the coexistence of those heterogeneous industrial wireless sensor networks (IWSNs). To accommodate such heterogeneity, this paper proposes a collaborative scheduling algorithm (CSA) for coordinating the activation of each coexisting IWSN while guaranteeing their respective real-time communication requirements. Specifically, the proposed CSA is able to help determine a unique data transmission instantance for each network node that periodically generates time-sensitive data, through which timely data delivery is guaranteed without the interference of each other.

A time-sensitive network (TSN) extends the conventional Ethernet to support time-sensitive data flow. Thus, it enables simultaneous transmission of high reliability (HR) flow, medium reliability (MR) flow, and low reliability (LR) flow on the same network, thereby improving the reliability of data transmission. A TSN is a symmetric network that connects sensors and other facilities. As a backbone network, it can efficiently connect the underlying sensors and other levels of facilities, as well as ensure the quality of service of the network. For modern supervisory control and data acquisition (SCADA) systems, several types of sensors are widely used. The acquisition cycle of sensors for different purposes varies significantly from milliseconds to seconds. Moreover, these data also have different real-time requirements. Based on satisfiability modulo theories (SMT), this study proposes a TSN routing and scheduling method by adding related scheduling constraints. Compared with other methods, the proposed method can realize the routing and scheduling of hybrid flow in a hyper period and consider MR flow and LR flow, which improves the feasibility and certainty of data flow interaction between substations.

Reconciling determinism with adaptability and resilience in the design of complex distributed system is a difficult task. In this paper, we argue that theoretical biology, especially biosemiotics and morphogenesis, gives a new perspective into this problem and presents us with new concepts that have been barely studied in the distributed systems literature. Current solutions for real-time systems are based on two simple assumptions, Positional Information and the B-series Time Code, which are only a small portion of the mechanisms used by living organisms. Investigating the application of alternative concepts on deterministic communication systems, such as inter-agential time (the E-series Time Code) and reaction–diffusion mechanisms, represents a promising path forward.

MQTT is one of the most popular application-layer protocols used in the scope of the Internet-of-Things (IoT) and Industrial-Internet-of-Things (IIoT), given its suitability for resource-constrained embedded systems. However, MQTT Quality-of-Service policies do not support timeliness requirements, which is common in IIoT. The literature reports several research works that address this limitation, but they are limited in scope (e.g., improvements in the broker’s internal operation, control of the publisher’s data rate, and path optimizations). Conversely, this paper presents a comprehensive architectural approach, proposing a set of extensions to the MQTT protocol that allow applications to explicitly specify real-time requirements and instantiate corresponding network reservations to enforce the desired temporal behavior. Such reservations are enforced via Software Defined Networking, specifically the OpenFlow protocol, but other protocols that allow bandwidth reservations, e.g., TSN, can also be used. This paper presents the proposed system architecture together with extensive emulation and implementation results that validate the feasibility of the approach, showing that time-sensitive MQTT traffic can be effectively segregated and prioritized to meet application-defined real-time requirements. Using several combinations of network topologies and load levels and comparing to the absence of the proposed real-time mechanisms, both average and worst-case latencies of the time-sensitive traffic decreased to approximately half, while for the normal traffic, they increased by approximately 10%.

In the last decades, a big number of image encryption schemes have been proposed. Most of these schemes reach a high-security level, however, their slow speeds due to their complex process make them unusable in real-time applications. Motivated by this, we propose a new efficient and high-speed image encryption scheme based on the Bülban chaotic map. Unlike most of the existing schemes, we make a wisely use of this simple chaotic map to generate only a few numbers of random rows and columns. Moreover, to further increase the speed, we raise the processing unit from the pixel level to the row/column level. Security of the new scheme is achieved through a substitution-permutation network, where we apply a circular shift of rows and columns to break the strong correlation of adjacent pixels. Then, we combine the XOR operation with the Modulo function to mask the pixels values and prevent any leak of information. High-security tests and simulation analysis have been carried out to demonstrate that the scheme is extremely secure and highly fast for real-time image processing at 80 fps (frames per second). [ABSTRACT FROM AUTHOR]

Cyber-physical Systems（CPS）is an intelligent complex system which is combined with the discrete mode of information space and continuous dynamic mode of the physical world, it consists of perception,computation,communication, control,etc. Firstly,the basic concept and structure of CPS are analyzed. Then,the technical system of CPS is presented. At the same time,the key technologies are discussed which involves three aspects:intelligent perception and automatic control,network communication technology and intelligent platform service technology. Finally, according to industrial application,the main challenges to be deal with for CPS are pointed out, and the future research directions are discussed.

Distance learning can be described as the process of learning between lecturers and students from different locations over the Internet. This paper discusses about a web based video call application using Web Real-Time Communication (WebRTC). It allows lecturers and students to communicate in a real time through the web application for learning purposes. The web application enables users to perform a video call using web browser. However, sometimes the lecturers are not able to attend a class due to unforeseen circumstances. So, they need to find a suitable time to make a replacement class and gather all students to perform a video conference. With the availability of this web application, both students and lecturers can just make a replacement class through video conference. Besides, some students are usually busy with their activities and they do not have time to consult or make appointment with their lecturers. This video call application helps to address the problem by connecting both students and lecturers from different places through a web application. The objectives have been identified, which are to design and develop a web based video call application using WebRTC and to evaluate the performance and functionality of the web application. The result is gathered based on the test conducted, which shows that users will experience a smooth video streaming by using wireless LAN as compared to the broadband, which causes a sluggish video streaming.