Common Communication Protocol Research Articles

Use of multi-agent system for industrial production control

This paper describes specific implementation of Asset Administration Shell technology used for an industrial distributed control system. The base of this control system is a multiagent system of digital twins which was created by AAS. This multiagent system was developed for a specific platform CP Factory (mainly based on Simatic PLC) but the implementation is y portable to each common platform. Digital twin of several types of components of typical industrial production process are described in this paper with the implementation of active and passive administration shell. The main focus is on describing the way of integrating digital twins into the production system and the necessary SW tools. Industry 4.0 language was used as a common communication protocol as well as OPC UA and MQTT.

Post-Quantum Authentication in the MQTT Protocol

Message Queue Telemetry Transport (MQTT) is a common communication protocol used in the Internet of Things (IoT). MQTT is a simple, lightweight messaging protocol used to establish communication between multiple devices relying on the publish–subscribe model. However, the protocol does not provide authentication, and most proposals to incorporate it lose their lightweight feature and do not consider the future risk of quantum attacks. IoT devices are generally resource-constrained, and postquantum cryptography is often more computationally resource-intensive compared to current cryptographic standards, adding to the complexity of the transition. In this paper, we use the postquantum digital signature scheme CRYSTALS-Dilithium to provide authentication for MQTT and determine what the CPU, memory and disk usage are when doing so. We further investigate another possibility to provide authentication when using MQTT, namely a key encapsulation mechanism (KEM) trick proposed in 2020 for transport level security (TLS). Such a trick is claimed to save up to 90% in CPU cycles. We use the postquantum KEM scheme CRYSTALS-KYBER and compare the resulting CPU, memory and disk usages with traditional authentication. We found that the use of KEM for authentication resulted in a speed increase of 25 ms, a saving of 71%. There were some extra costs for memory but this is minimal enough to be acceptable for most IoT devices.

Design and Implementation of a Lightweight Security-Enhanced Scheme for Modbus TCP Protocol

The advent of Industry 4.0 has made people pay more and more attention to the security of the industrial control system. As a common and typical communication protocol, Modbus does not consider the problem of data security at the beginning of its design, which provides opportunities for criminals. In this paper, we design a security scheme to protect the traditional Modbus TCP protocol, by using domestic encryption algorithms. As a result, the proposed scheme is able to identity authentication, data encryption, data integrity check, and anti-replay attacks. Security analysis and experimental results show that our proposed scheme solves the security problem of Modbus TCP protocol with minimal overhead increase.

FTP Server Client Using Android Application

On a computer network, the File Transfer Protocol (FTP) is a common communication protocol used to transfer data from a server to a client. FTP uses distinct control and data connections between the client and the server in client-server architecture. FTP offers two transfer methods: an anonymous technique and a password-based authentication method. The primary goal of FTP is to encourage file sharing. Clients can connect to the server using third-party applications (eg. FileZilla). A single FTP object can manage status, connection, settings, etc. is the centre of the Apache Commons Libraries. Obtaining a remote connection to involves a set of details, including the server's hostname or IP address, a username and a password.

АВТОМАТИЗАЦІЯ ВИМІРЮВАНЬ НА ДЕРЖАВНОМУ ЕТАЛОНІ ОДИНИЦІ КУТА ЗСУВУ ФАЗ МІЖ ДВОМА НАПРУГАМИ

The phase is one of the main parameters of the oscillatory process in electric circuits and contains two components – constant and variable. More often, it is not the actual phase that is measured, but the phase shift angle (PSA) between two oscillating processes (voltages or currents) of the same frequency in the range from 0 to 360˚. Then the PSA is equal to the difference between the constant components of the phases of the two oscillations and does not depend on the start of the time count. Most of the modern methods of measuring the phase and PSA are based on the methods of discretization and digital signal processing – complex Fourier transform, least squares, etc. There are many varieties and improvements of these methods, which have different characteristics of measurement accuracy. The LabVIEW graphical programming environment has already become a general- purpose programming environment. Advantages of LabVIEW include simple networking, implementation of common communication protocols, powerful toolkits for process control and data fitting, fast and simple user interface design, and an efficient code execution environment. The article presents the results of the automation of measurements on the State Standard of the PSA between two voltages in the frequency range from 5 Hz to 10 MHz. Automation of precision measurements of PSA using the Lab- VIEW software environment provides advantages in comparison with manual measurements, in particular, reducing the time of measurement and processing of its results by at least three times. This ensures an increase in the productivity of metrological works; increasing their efficiency and quality, and the possibility of increasing the number of measurements (up to 1000), which allows for improve the root mean square deviation of not less than one and a half times, and reduce the overall standard measurement uncertainty, respectively.

Big Data with IoT to Develop Sustainability

Things- or internet-oriented perspective, the Internet of Things (IoT) is a collection of unrelated networks that are linked and addressed by a common communications protocol [1]. When using sensors that send complex data at fast speeds via the industrial Internet, it might be challenging to give accurate and practical insights. Since the machine's underlying dynamic patterns vary over time due to a variety of variables, including degradation, processing large amounts of data is a significant problem. The actionable model must now be updated because it has become dated as a result. In the article, a brand-new deep learning technique called Gaussian-dependent dynamic probabilistic clustering (GDPC) is proposed. Models for usage in complicated situations that are built on the fusion and optimization of three well-known techniques. The Page-Hinkley test with the Chernoff constraint had been used to detect concept drifts, and the expectation-maximization (EM) approach had been used to estimate parameter values. In contrast to previous irregular models, GDPC's model gives membership probabilities to clusters. When a concept drift can be identified using a Brier score analysis, this can discover the robustness and evolution of the instance assignment. Additionally, the technique uses a tiny quantity of data, which significantly minimises the amount of processing power needed to determine whether the model should be changed. The method may be evaluated on artificial data and data streams from a test bed where different operational circumstances are automatically recognised with satisfactory results in terms of classification accuracy, sensitivity, and characteristics [2]. The typical behaviour of private autos is derived from trajectory data.

CCgen: Injecting Covert Channels into Network Traffic

Covert channels are methods to convey information clandestinely by exploiting the inherent capabilities of common communication protocols. They can be used to hide malware communication as part of cyber attacks. Here, we present CCgen, a framework for injecting covert channels into network traffic that includes modules for common covert channels at the network and transport layer and allows a smooth integration of novel covert channel techniques. Our tool—openly available and implemented in Python—enables the operation on-the-fly in live communications as well as the manipulation of network traffic packet captures. We evaluate a first prototype by generating a varied assortment of covert channels based on state-of-the-art techniques and check their detectability with Suricata, a popular, open-source intrusion prevention and detection system. The injected covert channels remain mostly undetected. Our proposal fills a gap within the diversity of openly available tools for cybersecurity research and education. It builds a flexible environment for experts to test analysis algorithms, thus also enabling advanced training in applied network steganography.

Data Augmented Hardware Trojan Detection Using Label Spreading Algorithm Based Transductive Learning for Edge Computing-Assisted IoT Devices

IoT devices handle a large amount of information including sensitive information pertaining to the deployed application. Such a scenario, makes IoT devices susceptible to various attacks. In addition to securing IoT devices, it is equally important to secure communication among devices and with the outside world. RS232 is a common communication protocol used in IoT and embedded devices. Hence ensuring, Trojan detection in RS232 plays a major role in providing secured communication among edge assisted IoT devices. The inclusion of malicious circuits known as hardware Trojans can occur at any stage of the IC design and manufacturing. Existing pre-silicon detection schemes with static features is limited by the number of features that are learned by the detection scheme. In contrast, machine learning allows enhanced Trojan space exploration. Existing machine learning-based Trojan detection consists primarily of supervised algorithms that rely on high-quality labeled datasets for efficient Trojan detection. Unsupervised methods, on the other hand, underperform due to limited training data and severe imbalance within the available data. To handle such a situation, a semi-supervised hardware Trojan detection has been proposed. In this work, permutation importance guided principal component analysis, correlation aware data augmentation, and hyper-parameter optimization using genetic algorithm aid in optimal dataset and model generation. Pseudo label generation using semi-supervised schemes is utilized to handle partially labeled datasets. For the Trust-HUB benchmarks, the proposed methodology achieves an average of 88.48% true positive rate and 95.77% true negative rate which, clearly indicates the effectiveness and feasibility of semi-supervised hardware Trojan detection.

Data Exchange Techniques for Internet of Robotic Things: Recent Developments

The world we live in is where a human-machine connection is a barometer, and this tendency is only growing to provide richer and universal human reminiscences. New technologies, as well as the fusion of different classes of current technologies, are used to create such unique solutions. The Internet of Robotic Things (IoRT) is the product of collaboration between robotics and the Internet of Things (IoT), which has opened up incredible potential for localized self-sufficient solutions. Robots can collect accurate data from the environment and provide a comprehensive service instantaneously. Being an amalgamation of two different concepts i.e. IoT and Robotics, the IoRT system is anticipated to benefit both by expanding their potential to innovative heights. This paper gives a concise introduction to the communication architecture of the IoRT system. The taxonomy of various data exchange protocols used in an IoRT system is proposed. The necessary improvements in protocols that are required to enhance communication in an IoRT system are presented. A Review of some data exchange methodologies based on Artificial Intelligence (AI) for secure and reliable communication is also given in this paper. The key motive of this paper is to understand the data exchange within an IoRT system using common communication protocols.

A UCB-based dynamic CoAP mode selection algorithm in distribution IoT

Lightweight constrained application protocol (CoAP) has emerged as a common communication protocol for resource-constrained equipment in distribution internet of things (IoT). CoAP introduces two modes for data transmission, i.e., non-confirmed mode for reducing transmission delay and confirmed mode for reducing packet-loss ratio, which can be dynamically selected to satisfy the service requirements. However, there are still some challenges in dynamic CoAP mode selection, including incomplete information and differentiated quality of service (QoS) requirements of distributed IoT services. In this paper, we propose a upper confidence bound (UCB)-based dynamic CoAP mode selection algorithm for data transmission to address these challenges. The simulation results validate that, compared with the fixed mode selection algorithm, the proposed algorithm can flexibly balance the tradeoff between packet-loss ratio and transmission delay as well as satisfy the differentiated QoS in distribution IoT.

Asynchronous Floating-Point Adders and Communication Protocols: A Survey

Addition is the key operation in digital systems, and floating-point adder (FPA) is frequently used for real number addition because floating-point representation provides a large dynamic range. Most of the existing FPA designs are synchronous and their activities are coordinated by clock signal(s). However, technology scaling has imposed several challenges like clock skew, clock distribution, etc., on synchronous design due to presence of clock signal(s). Asynchronous design is an alternate approach to eliminate these challenges imposed by the clock, as it replaces the global clock with handshaking signals and utilizes a communication protocol to indicate the completion of activities. Bundled data and dual-rail coding are the most common communication protocols used in asynchronous design. All existing asynchronous floating-point adder (AFPA) designs utilize dual-rail coding for completion detection, as it allows the circuit to acknowledge as soon as the computation is done; while bundled data and synchronous designs utilizing single-rail encoding will have to wait for the worst-case delay irrespective of the actual completion time. This paper reviews all the existing AFPA designs and examines the effects of the selected communication protocol on its performance. It also discusses the probable outcome of AFPA designed using protocols other than dual-rail coding.

An Automatic Online System for Detecting and Analyzing Quality Data of Products in Manufacturing Process

As the business volume is getting bigger, more and more problems are exposed to product quality testing. For example, the application of the traditional statistical process control (SPC) is not flexible on different occasions due to the fixed testing rules and the manual data collection. These problems lead to large deviation and low efficiency. In order to fasten the testing process and optimize the results of testing, we design an online system that integrates the Drools rule engine and automatic collection mechanism based on some common communication protocols and devices into SPC to replace traditional manual quality testing. In this paper, we introduce the principle of the system design in detail. The experimental results show that we can utilize SPC in a more convenient and efficient way.

Toward UAV Control via Cellular Networks: Delay Profiles, Delay Modeling, and a Case Study Within the 5-mile Range

While some unmanned aerial vehicles (UAVs) can operate with a given degree of autonomy (e.g., path following, obstacle avoidance, auto return, and other flight modes), many civilian drones have a safety pilot standby all the time for abnormal conditions. This is typically done within line-of-sight (LOS) due to regulations. While flying within LOS, radio frequency communication remains a popular alternative for retail pilots. For beyond line of sight operations, given the availability of cellular technologies, the UAV community has explored the possibility of using the cellular network instead, which could bring benefits such as an additional channel for control and telemetry, extension of range, and allowing the UAV to interact with cloud services while it flies, via a data connection. With the current prevalence of data supporting communication over 3G and 4G networks, the following representative technologies have been used for long-distance control-short message service (SMS), transmission control protocol (TCP), message queue telemetry transport (MQTT), and the so-called “protocol-independent” service PubNub. While the safety of drone flights is highly prioritized by regulators, the issue becomes even more highlighted when control commands are transmitted via cellular network channels (e.g., 4G long-term evolution, SMS) which can introduce time delays in communication chains and degrade pilot's ability to properly control UAVs. This article reviews common UAV communication protocols over cellular links and presents a technique for measuring and modeling delays over such channels. The quality-of-fit for the proposed models is measured for different communication protocols, short versus long-range communication, and different UAV operation modes. Finally, details are presented for a system that manipulates a drone via the cellular network and latency is measured for such system.

Telemonitoring systems for respiratory patients: technological aspects

This review introduces the reader to the available technologies in the field of telemonitoring, with focus on respiratory patients. In the materials and methods section, a general structure of telemonitoring systems for respiratory patients is presented and the sensors of interest are illustrated, i.e., respiratory monitors (wearable and non-wearable), activity trackers, pulse oximeters, environmental monitors and other sensors of physiological variables. Afterwards, the most common communication protocols are briefly introduced.In the results section, selected clinical studies that prove the significance of the presented parameters in chronic respiratory diseases are presented. This is followed by a discussion on the main current issues in telemedicine, in particular legal aspects, data privacy and benefits both in economic and health terms.

Deployment in Cloud Computing

Although clouds have adopted common communication protocols such as HTTP and SOAP, interoperability, integration, and coordination of all clouds remain a concern. Instead, companies are looking for solutions to deploy an infrastructure that spans multiple instances of public and private clouds. Each of the proposed cloud solutions has its own limitations, management APIs, and development cycles that must be monitored and managed to provide a consistent set. The objective of the article is to answer the question: Is there a platform to deploy, run and manage applications in a multi-cloud environment and to ensure their availability, performance, and optimal use of resources?

An Event-Based Neural Network Architecture with Content Addressable Memory

A hybrid analog/digital very large-scale integration (VLSI) implementation of a spiking neural network with programmable synaptic weights was designed. The synaptic weight values are stored in an asynchronous module, which is interfaced to a fast current-mode event-driven DAC for producing synaptic currents with the appropriate amplitude values. It acts as a transceiver, receiving asynchronous events for input, performing neural computations with hybrid analog/digital circuits on the input spikes, and eventually producing digital asynchronous events in output. Input, output, and synaptic weight values are transmitted to/from the chip using a common communication protocol based on the address event representation (AER). Using this representation, it is possible to interface the device to a workstation or a microcontroller and explore the effect of different types of spike-timing dependent plasticity (STDP) learning algorithms for updating the synaptic weights values in the CAM module.

Throughput of Customised ZigBee Stack- A Mathematical Modelling

Research work is being done in the field of wireless communication protocols in order to find the desired applicability suitable to the end user. ZigBee protocol is chosen due to its reliable, long range and robust communication. In this direction there is need of designing a common communication protocol to realize a virtual control network by customizing the existing ZigBee protocol stack. It is also required to embed internet support protocols in different layers of the proposed stack so as to enable the entire network with internet connectivity. The proposed application aims at interoperating different devices under user personal area network, this fact has led to propose a new protocol stack with which every device of the network can be easily operated or controlled with enhanced network capabilities like resource sharing, additional middle layer for realising the proposed application using WPAN christened as ZigBee IP [ZI] stack. ZI stack is designed and the corresponding mathematical modelling is done in order to find better stack than ZigBee. This paper presents the design and modelling of throughput which is one of the important design parameters. Both the stacks viz., ZI and ZigBee are also compared w.r.t throughput.

Not just another Internet of Things taxonomy: A method for validation of taxonomies

The Internet of Things (IoT) is a fast-evolving ecosystem. As with any new and popular technology, it includes important design details that need to be refined, such as the standardization of APIs, firmware, architecture, application development, performance, and security. There have been several studies on the IoT architecture, the classification of IoT threats, and the future of these devices. In this paper, our goal is to create a general taxonomy for better understanding the large ecosystem of devices that span from commodity home appliances, such as smart plugs, digital assistants, and web cameras; to industry and health-care machines, such as smart meters and robots. Our first contributions includes an IoT taxonomy, based on generic building blocks that characterize IoT. Our second contribution is to demonstrate that this taxonomy is general and robust, by including a simple yet effective algorithm to prove the taxonomy’s completeness, timelessness, and precision. We compare our proposed taxonomy with another two taxonomies, to identify any weaknesses or differences. We conclude that our taxonomy is more general and precise than the already existent ones. Finally, our third contribution is to list two applications of this taxonomy. The first application demonstrates the classes defined by our taxonomy and how these groups of devices share similar architectures and can be standardized with common APIs, tools, and communication protocols. The second generates IoT models of correct operation that can be applied in intrusion detection or debugging faulty behavior.

Development of Wireless Sensor Node and Controller Complying with Communication Interface Standard for Smart Farming

The sensor node is a basic unit of a greenhouse control system that collects environment data and sends them to an environment controller. It is important for the sensor node and the controller to share a common communication protocol to enable effective communication. The objective of this research was to develop a wireless sensor node complying with a communication interface standard between a sensor node and a controller and to evaluate variation in data transmission rate with distance. The TTAK.KO-06.0288-Part1/R1 standard was selected as a communication interface standard; it was analyzed and implemented with a C++ library. A sensor node and a controller were designed to communicate with the library wirelessly using Bluetooth. The system was tested in a greenhouse to evaluate the variation in data transmission rate with changes in the distance between the components. A C++ library, libgnode, was developed and successfully implemented for transmitting data from the sensor node to the controller, complying with the TTA standards. The data transmission rate was 100% up to a distance of 25 m between the sensor node and the controller. The libgnode library can be utilized to improve the interoperability between components of a greenhouse control system. However, further research into the use of long-distance wireless communication methods (e.g., Zigbee or LoRa) is warranted in order to extend the communication coverage area in the greenhouse.

Dynamical performance analysis of communication-embedded neural networks: A survey

State estimation and synchronization of neural networks (NNs) have recently received ever-increasing research interests due to a large number of successful applications in various fields such as repetitive learning, classification of patterns, nonlinear control, adaptive control, image processing, and so forth. Owing to limited communication bandwidth, the network-induced phenomena and the adopted communication scheduling may cause inevitable negative effects or the degradation of dynamical performance of NNs. This paper, from the perspective of dynamical behavior, renders a comprehensive summary on the recent advances of communication-embedded NNs and their application in nonlinear control. First, some common network-induced phenomena and communication protocols are roughly introduced from both models and mechanisms. Then, the state estimation and synchronization analysis of various NNs with network-induced phenomena are systematically reviewed and some interesting results are separately presented. Furthermore, the latest advances for the cases with communication protocols are profoundly surveyed from three aspects: state estimation, synchronization analysis and applications in control realm. Finally, some challenged problems are listed and several potential future research directions are highlighted.