TCP Communication Research Articles

Integrating machine vision in the development of automatic mounting system for massive electroplating components

Abstract The traditional industrial electroplating parts manufacturing process typically relies on manual labour to suspend them in the electroplating tank, requiring a significant amount of manual work. However, due to a shortage of manpower and frequent staff turnover, this has posed challenges to production efficiency. Therefore, this research proposes an automated mounting system by integrating machine vision technology and the development of robotic arms to replace the conventional manual suspension method. The automated mounting system initially separates individual ring-shaped electroplating components using a disk vibratory feeder. Subsequently, it utilizes a unidirectional reciprocating mechanism and infrared detection to position these electroplating components onto a backlit panel. Then, the IDS uEye XS2 autofocus camera captures images, and in conjunction with machine vision technology, rapidly determines the position, characteristics, and orientation of these ring components. Finally, through TCP communication protocol, commands for gripping points are transmitted to the robotic arm, which uses electromagnetic valves on the arm to pick up the components and suspend them onto the hanger using an optimized path. The final test results demonstrate that the automated installation system can complete 14 installation operations per minute, effectively reducing the time and cost associated with manual labour, significantly enhancing the production output of the assembly line. Therefore, this study combines machine vision technology to propose a solution for the automated installation system of large-scale electroplating components.

The monitoring system of running state data of converter station equipment based on sensor information and 3D positioning algorithm

Abstract The stable operation of multiple equipment in the converter station can ensure the safety of the DC transmission system. Once the fault occurs, it will pose a threat to the safety and stability of the power grid. It is necessary to monitor the running state of all kinds of equipment, and study the monitoring system of the running state data of the converter station equipment based on sensor information and a three-dimensional positioning algorithm. In terms of hardware design, TCP and IP communication protocols are used to connect the sensors, and the sensors are arranged according to the vibration conduction standard, constituting a three-layer monitoring architecture of monitoring center, sensor, and equipment. The sensor module is connected by interface, and the structure of the connecting control board for sensor data transmission is set to increase the flexibility of sensor nodes. In software design, the basic information of converter station equipment is corresponding to sensor technology, and the database of operating equipment is established. A three-dimensional positioning algorithm is used to determine the data output form, detect the running state data of the converter station equipment, and complete the system design. The experiment takes various types of running data as the test object. Under the system application in this paper, different running data can be correctly classified and data monitoring under various states can be realized, which has application value.

Optimized Strategy in Cloud-Native Environment for Inter-Service Communication in Microservices

Cloud computing has become a prominent technology in the software development industry. The term “cloud-native” is derived from cloud computing technologies and refers to the development and deployment of applications in a cloud environment. In the software industry, most enterprise-grade software buildings use the microservice architecture and cloud natively, ultimately leading to an expansive development in the software development framework. Microservices are deployed in a distributed environment and function as independent services. However, they need to communicate with each other in order to fulfill the functional requirement. Additional latency will be introduced when communicating with other services. Hence, it will impact the overall application response time and throughput. This research proposes a solution for the aforementioned problem in the cloud-native environment. A Request-response-based TCP communication solution has been developed and tested in the cloud-native, containerized environment. Experimental results showed that the turnaround time of the proposed solution is shorter than that of traditional HTTP communication methods. Furthermore, the results summarize that both vertical and horizontal scaling are improving the overall performance of the systems performance in terms of response time. Conclusively, the proposed solution improved the microservice performance and preserved the existing cloud-native qualities, such as scalability, maintainability, and portability.

Collaborative Multi-Agent Video Fast-Forwarding

Multi-agent applications have recently gained significant popularity. In many computer vision tasks, a network of agents, such as a team of robots with cameras, could work collaboratively to perceive the environment for efficient and accurate situation awareness. However, these agents often have limited computation, communication, and storage resources. Thus, reducing resource consumption while still providing an accurate perception of the environment becomes an important goal when deploying multi-agent systems. To achieve this goal, we identify and leverage the overlap among different camera views in multi-agent systems for reducing the processing, transmission and storage of redundant/unimportant video frames. Specifically, we have developed two collaborative multi-agent video fast-forwarding frameworks in distributed and centralized settings, respectively. In these frameworks, each individual agent can selectively process or skip video frames at adjustable paces based on multiple strategies via reinforcement learning. Multiple agents then collaboratively sense the environment via either 1) a consensus-based distributed framework called <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">DMVF</b> that periodically updates the fast-forwarding strategies of agents by establishing communication and consensus among connected neighbors, or 2) a centralized framework called <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">MFFNet</b> that utilizes a central controller to decide the fast-forwarding strategies for agents based on collected data. We demonstrate the efficacy and efficiency of our proposed frameworks on a real-world surveillance video dataset VideoWeb and a new simulated driving dataset CarlaSim, through extensive simulations and deployment on an embedded platform with TCP communication. We show that compared with other approaches in the literature, our frameworks achieve better coverage of important frames, while significantly reducing the number of frames processed at each agent.

Low Delay Transmission Scheme of Power Communication Information Based on 5G Network

Power information data transmission is prone to packet loss rate, and communication protocol is required to improve the transmission capacity of power information data. Therefore, a low delay transmission scheme of power communication information based on 5G networking is proposed and constructed, the power communication information data through 5G networking technology is processed and is sent to the corresponding data application module for data classification and mining, and then the information data is converted in different formats to the same data transmission format. TCP communication protocol as the communication protocol is selected for data online transmission to describe the low delay transmission of power communication information. The chaotic sequence is set based on 5G networking, and the connection weight matrix is calculated. Then the power communication information sequence is encrypted in real time according to the row column substitution rule. On this basis, the data encryption module, dynamic key generation module and shared key update module are combined to realize the low delay transmission of power communication information. The experimental results show that with the increase of the network area and the number of nodes, the data transmission volume can be gradually increased. The change range of this method is relatively small, which can effectively improve the feasibility of the low delay transmission scheme of power communication information.

Research on Logic Design of Proton Treatment Control System

The proton treatment control system is the supporting software of the proton therapy device, which specifically coordinates and controls the status and work of each subsystem. In this study, the software architecture and hardware implementation of the proton treatment control system was developed and built a foundation for the overall debugging. Using C# programming language and WPF programming techniques, TCP network communication protocol specified by the proton treatment technical document and MVVM pattern in Windows system, the logic design and implementation of each level were studied. Meanwhile, the communication interface between the subsystems under TCP communication protocol was agreed. The logic design and research of the setup field and treatment field were carried out. And the User Interface was designed and developed using the above technology. The program realizes the communication and interaction between the proton treatment control system and each subsystem, so as to control and monitor the whole treatment process. The proton treatment control system provides a software basis for the remote overall debugging and on-line monitor and control of proton treatment device.

Elliptic Curve Cryptography Considerations for Securing Automation and SCADA Systems

Securing critical infrastructures and manufacturing plants in the Industrial-Internet-Of-Things and Industry 4.0 is a challenge today due to the increased number of attacks against automation and SCADA systems. These systems were built without any security considerations in mind, so the evolution towards interconnection and interoperability makes them vulnerable in the context of exposing data to the outside network. Even though new protocols are considering built-in security, the widely spread legacy standard protocols need to be protected. Hence, this paper attempts to offer a solution for securing the legacy insecure communication protocols based on elliptic curve cryptography while fulfilling the time constraints of a real SCADA network. Elliptic curve cryptography is chosen to respond to the low memory resources available for the low level devices of a SCADA network (e.g., PLCs), and also because it can achieve the same level of security as other cryptographic algorithms using smaller sizes for the secure keys. Furthermore, the proposed security methods have the purpose of assuring that the data transmitted between entities of a SCADA and automation system are authentic and confidential. The experimental results showed good timing performance for the cryptographic operations executed on Industruino and MDUINO PLCs, demonstrating that our proposed concept is deployable for Modbus TCP communication in a real automation/SCADA network on existing devices from the industry.

Research on the Application of Wireless Sensor in the Design of Curtain Automatic Adjustment System

With the development of science and technology and the progress of wireless sensor network technology, a variety of intelligent electronic products are used more and more widely in people's lives. High technology and intelligent technology have entered residential home users from intelligent buildings, and home intelligent technology has become a cutting-edge technology topic. The development of mobile Internet provides a new platform for home decoration, which is of great significance in promoting the formation of smart families and smart communities. Curtain is an important element in interior decoration design. It is of great practical value to develop a mobile virtual display system that can manage curtains and provide curtain decoration effects. The design idea of modularization is adopted, and the design process of wireless communication module, relay module, key module, power protection and level conversion module of the system is emphatically analyzed. The basic working principle and operation method of the system are introduced, and the server and client software based on TCP communication protocol are designed to realize the remote control of curtains through the Internet or personal mobile devices. The actual results show that the scheme can be applied to the home or office environment, and has the characteristics of high stability and simple operation.

Empirical Mode Decomposition-empowered Network Traffic Anomaly Detection for Secure Multipath TCP Communications

Empirical Mode Decomposition-empowered Network Traffic Anomaly Detection for Secure Multipath TCP Communications

A multi‐agent based mechanism for collaboratively detecting distributed denial of service attacks in internet of vehicles

AbstractDistributed denial of service (DDoS) attacks have become a hidden danger in the development of the internet of vehicles (IoV). DDoS attacks for TCP protocol are studied to improve the information security environment of IoV. For the distribution characteristics of DDoS attacks, an information sharing and collaborative detection mechanism based on multi‐agent is proposed. Considering the relationship between the features of adjacent moments in the TCP communication, the DDoS detection model based on hidden Markov model is built, and the Viterbi algorithm is improved for the problem of the false alarm in the observation sequence. The optimal communication strategy among agents is determined by deep reinforcement learning, and fusion algorithm is designed to improve the current strategy of agents. Three groups of comparative experiments are designed and analyzed. The simulation results show that proposed algorithms are effective.

Discontinuous Track Recognition System Based on PolyLaneNet for Darwin-op2 Robot.

This paper proposes and demonstrates a single-line discontinuous track recognition system by associating the track recognition problem of a humanoid robot with the lane detection problem. The proposal enables the robot to achieve stable running on the single-line discontinuous track. The system consists of two parts: the robot end and the graphics computing end. The robot end is responsible for collecting track information and the graphics computing end is responsible for high-performance computing. These two parts use the TCP for communication. The graphics computing side uses PolyLaneNet lane detection algorithm to train the track image captured from the first perspective of the darwin-op2 robot as the data set. In the inference, the robot end sends the collected tracking images to the graphics calculation end and uses the graphics processor to accelerate the calculation. After obtaining the motion vector, it is transmitted back to the robot end. The robot end parses the motion vector to obtain the motion information of the robot so that the robot can achieve stable running on the single-line discontinuous track. The proposed system realizes the direct recognition of the first perspective image of the robot and avoids the problems of poor stability, inability of identifying curves and discontinuous lines, and other problems in the traditional line detection method. At the same time, this system adopts the method of cooperative work between the PC side and the robot by deploying the algorithm with high computational requirements on the PC side. The data transmission is carried out by stable TCP communication, which makes it possible for the robot equipped with weak computational controllers to use deep-learning-related algorithms. It also provides ideas and solutions for deploying deep-learning-related algorithms on similar low computational robots.

Machine Learning to Optimize TCP Communications Over High Frequency Communications Links

High Frequency communication is a proven method of beyond line of sight (BLOS) communications for decades. With the advent of Wideband HF (WBHF), the ability to communicate data and more specifically TCP over HF is being researched worldwide. HF-TCP, an optimised TCP for HF links provides improved TCP communication over challenging High Frequency (HF) communication systems. It relies on the modification of Forced Retransmission Timeout (fRTO) and Mean Segment Size (MSS) to improve the reliability of communication sessions. Calculating the fRTO for a communication session that would provide the optimum result over a communication link is a complex task due to the timers that manage the session and the HF channel characteristics. In this paper, we propose the use of Machine Learning (ML) techniques to dynamically predict fRTO and MSS to improve the fRTO calculation process for all communication instances. To achieve this, a Predictor Model is used to predict fRTO and MSS while an Optimiser model optimises the Predictor model’s output. Decision Tree Regression was proven to be the most accurate among the various ML algorithms tested with 82 percent prediction accuracy. The performance of HF-TCP with proposed predicted fRTO and MSS is compared with that of standard TCP and the performance of the Predictor and Optimiser models is also analysed. The results show 72 percent of instances have an improvement in link efficiency when using HF-TCP with predicted fRTO and MSS over standard TCP.

Industrial Control System Anomaly Detection and Classification Based on Network Traffic

This paper proposes an anomaly detection and classification method for industrial control systems (ICSs). The proposed method is based on network traffic data of industrial field protocols like Modbus TCP and S7 Communication. First, the denoising autoencoder (DAE) is utilized to reduce data noise and extract core features from data. Second, the synthetic minority oversampling technique (SMOTE) and the Tomek link (T-Link) mechanism are employed to oversample and undersample data for addressing the data imbalance problem. Finally, extreme gradient boosting (XGBoost) is used to leverage the ensemble learning concept to avoid overfitting for achieving good performance. A real-life railway industry ICS dataset called Electra is used to evaluate the performance of the proposed method, and the evaluation results are compared with those of other related methods. The proposed method is shown to have the highest (100%) precision, recall and F1-score for anomaly detection, and have fairly high performance of anomaly classification. The contribution of this paper is to show that integrating the DAE, SMOTE, T-Link, and XGBoost schemes can achieve the highest or extremely high performance in the aspect of ICS anomaly detection and classification based on network traffic. The computational complexity and convergence analyses of the proposed method are also provided in this paper. Furthermore, the code implementing the proposed method is released for public access through IEEE Code Ocean so that the effectiveness and the applicability of the method can be validated.

Enhanced packet reordering procedure to improve TCP communication

PurposeThe research work is attained by Spurious Transmission–based Enhanced Packet Reordering Method (ST-EPRM). The packet reordering necessity is evaded by presenting random linear network coding process on wireless network physical layer which function on basis of sequence numbers. The spurious retransmission happening over wireless network is obtained by presenting monitoring concept for reducing number of spurious retransmissions because it might need more than three DUPACKs for triggering fast retransmit. This monitoring node performs as centralized node as well variation amid buffer length and number of packets being sent can be predicted. This information helps in differentiating spurious retransmission from the packet loss.Design/methodology/approachBased on transmission detection, action is accomplished whether to retransmit or evade transmission. Monitoring node selection is achieved by presenting improved cuckoo search algorithm. The modified support vector machine algorithm is greatly used for variation-based spurious transmission.FindingsThe research work which is attained by ST-EPRM. The packet reordering necessity is evaded by presenting random linear network coding process on wireless network physical layer which function on basis of sequence numbers. The spurious retransmission happening over wireless network is obtained by presenting monitoring concept for reducing number of spurious retransmissions because it might need more than three DUPACKs for triggering fast retransmit. This monitoring node performs as centralized node as well variation amid buffer length and number of packets being sent can be predicted. This information helps in differentiating spurious retransmission from the packet loss.Originality/valueBased on transmission detection, action is accomplished whether to retransmit or evade transmission. Monitoring node selection is achieved by presenting improved cuckoo search algorithm. The modified support vector machine algorithm is greatly used for variation-based spurious transmission.

Application of XML and TCP communication on Dynamic customization of the smart home system

Aiming at the problem of personalized customization of a smart home system, a scheme of personalized customization of the smart home system based on parsing XML authorization files is proposed. First, develop an XML authorization file generator, and use it to generate personalized XML authorization files; secondly, use the developed app to parse the XML authorization file to realize the legal authorization of the app and the dynamic generation of the home control interface; finally, click buttons on the control interface to trigger the TCP communication between the app and ESP8266, and then with the help of esp8266 to realize the switch of electrical appliances. Experimental results show that dynamic customization of the smart home system based on XML can implement dynamic customization of control interfaces for various home layouts, and can effectively control the home furnishings.

Industrial robot-based system design of thickness scanning measurement using ultrasonic

Abstract. Wall thickness is one of the core indicators for measuring the quality of large thin-walled parts such as rocket siding and aircraft skin. However, the traditional handheld thickness measurement method has high labor intensity, low efficiency and poor accuracy consistency. Therefore, an in situ ultrasonic automatic scanning thickness measurement method for large thin-walled parts based on industrial robots is proposed. This “industrial robot + ultrasound” integrated function is a compact system, and a set of innovative methodological or technical solutions is presented, such as (i) TCP and UDP communication protocols being constructed to realize a high-speed and stable communication relationship between the upper computer, robot motion controller and ultrasonic thickness measurement unit; (ii) a coupling gap adjustment method based on eddy-current sensors being adopted to ensure the adaptability of the ultrasonic probe to surface topography of the measured part during scanning measurement; and (iii) a multi-sensor coordinate unified model and coupling gap state discrimination model being established for robot-aided thickness measurement. To verify the feasibility of the proposed method, a series of calibrations and experiments were designed based on the KUKA robot platform and the developed ultrasonic pulse measurement system. Finally, the industrial robot-based ultrasonic thickness scanning measurement has been built and tested for performing the measurement of a rocket tank wall.

An experimental study of the performance of IEEE 802.11ad in smartphones

We present the first extensive measurement study of the performance of the 60 GHz 802.11ad technology on commercial smartphones. We focus on five major perspectives: (i) TCP throughput and communication range in static scenarios, (ii) spatial and temporal variations, (iii) coverage, (iv) performance under realistic smartphone user mobility patterns, and (v) impact of human blockage. We also compare for the first time 802.11ad against its two main competitors in the 5 GHz band: the state-of-the-art 802.11ac and the upcoming 802.11ax, which also promises multi-Gbps data rates. Finally, we present a preliminary evaluation of the 802.11ad power consumption on a smartphone under Gbps data rates. Overall, our results show that, in spite of earlier concerns, 802.11ad has higher potential to address the needs of emerging bandwidth-intensive applications in smartphones than its 5 GHz counterparts. At the same time, our study identifies several open challenges and key research directions towards fully realizing this potential for future smartphone users.

Research on robot catching ball based on binocular vision positioning

In this paper, the robot used to catch the ball is studied, and a faster and more accurate detection and recognition method for high-speed moving objects is proposed, which can automatically judge the position of the ball and output the position information through TCP communication protocol. Based on the binocular vision system, this method identifies the small ball by calibrating the camera, processing the gray-scale image, transforming the image coordinates to spatial coordinates and Hough transform, and then realizes the spatial position and distance detection of the small ball. In addition, the ball receiving system and the robot platform are studied, so that they can be connected in real time and stably. It ensures the real-time and accuracy of the vision system to track the ball and meets the design requirements of the ball-catching robot.

A secure architecture for TCP/UDP-based cloud communications

Cloud communication is an intrinsic aspect of cloud architecture. It is an internet-based communication that enables access to millions of cloud services. These services are provided using TCP/UDP-based communications and protected by traditional security protocols (e.g., SSL/ TLS/DTLS). However, security threats in cloud communications become the most serious issue nowadays. To address some of the shortcomings of traditional security protocols, we propose a secure cloud communication architecture (Graphene) for both TCP- and UDP-based communications. Graphene can provide security for data-in-transit and authenticity of cloud users and cloud service providers. It protects the communication channel against most common attacks such as man-in-the-middle (including eavesdropping, sniffing, identity spoofing, and data tampering), sensitive information disclosure, replay, compromised-key, repudiation, and session hijacking attacks. This work also involves the designing of a novel high-performance cloud-focused security protocol that works for both TCP and UDP communications. Especially for UDP, it uses an asynchronous re-transmission mechanism to ensure datagram delivery. This protocol efficiently utilizes the strength and speed of symmetric block encryption with Galois/Counter mode, cryptographic hash, public key cryptography, and ephemeral key-exchange. It provides faster reconnection facility for supporting frequent connectivity and dealing with connection trade-offs. The security analysis of Graphene shows promising protection against the above discussed attacks. Graphene also outperforms TLSv1.3 (the latest stable version among the SSL successors) and DTLSv1.2 (the latest stable version of datagram TLS) in performance and bandwidth consumption significantly and shows reasonable memory usage at the server side.

Saliency-based bit plane detection for network applications

Transmitting image data without losing significant information is challenging for any network application especially when large color images are transmitted through TCP communication protocol. This is due to network limitations such as buffer overflow, underflow and network traffic flow etc. This paper presents a new method for image size reduction such that the network can transmit data without much loss of information, and hence, quality. The proposed method obtains bit planes for the color input images, which results in eight binary planes. Unlike the existing bit plane based image size reduction methods, which assume that the most significant plane or some other planes contain useful information, the proposed method finds the plane that contains dominant information automatically. For each plane, the proposed method explores the saliency that finds dominant information based on Markov Chain Process and similarity estimation between neighbor pixels. To reduce computational burden, we use Canny edge maps of the saliency of the planes for feature extraction. We propose to explore ring-growing concept for the edge maps to study the spatial distribution of saliency, locally. The proposed method detects the plane based on statistics of saliency distribution. To validate the step of plane detection, we estimate transmission error caused during data transmission through TCP communication protocol for the images at sending and receiving ends. Experimental results on plane detection show that the proposed method is better than the existing methods in terms of detection rate. Our experiments on image transmission through TCP communication protocol show that the proposed method outperforms the existing methods in terms of error estimation and quality analysis. Furthermore, experiments are conducted to analyze packet loss in terms of number of duplicate acknowledgements and retransmission during packets transmission for the color, edge and plane to show that transmitting plane images improves network performance in terms of less number of duplicate acknowledgement, retransmission and time taken in seconds.