Network Communication Quality Research Articles

Influence of network latency and bandwidth on robot-assisted laparoscopic telesurgery: A pre-clinical experiment.

Telesurgery has the potential to overcome spatial limitations for surgeons, which depends on surgical robot and the quality of network communication. However, the influence of network latency and bandwidth on telesurgery is not well understood. A telesurgery system capable of dynamically adjusting image compression ratios in response to bandwidth changes was established between Beijing and Sanya (Hainan province), covering a distance of 3000km. In total, 108 animal operations, including 12 surgical procedures, were performed. Total latency ranging from 170ms to 320ms and bandwidth from 15-20Mbps to less than 1 Mbps were explored using designed surgical tasks and hemostasis models for renal vein and internal iliac artery rupture bleeding. Network latency, jitter, frame loss, and bit rate code were systemically measured during these operations. National Aeronautics and Space Administration Task Load Index (NASA-TLX) and a self-designed scale measured the workload and subjective perception of surgeons. All 108 animal telesurgeries, conducted from January 2023 to June 2023, were performed effectively over a total duration of 3866min. The operations were completed with latency up to 320ms and bandwidths as low as 1-5Mbps. Hemostasis for vein and artery rupture bleeding models was effectively achieved under these low bandwidth conditions. The NASA-TLX results indicated that latency significantly impacted surgical performance more than bandwidth and image clarity reductions. This telesurgery system demonstrated safety and reliability. A total of 320ms latency is acceptable for telesurgery operations. Reducing image clarity can effectively mitigate the potential latency increase caused by decreased bandwidth, offering a new method to reduce the impact of latency on telesurgery.

Edge computing collaborative offloading strategy for space‐air‐ground integrated networks

SummaryDue to geographical factors, it is impossible to build large‐scale communication network infrastructure in remote areas, which leads to poor network communication quality in these areas and a series of delay‐sensitive tasks cannot be timely processed and responded. Aiming at the problem of limited coverage in remote areas, the space‐air‐ground integrated networks (SAGIN) combined with mobile edge computing (MEC) can provide low latency and high reliability transmission for offloading delay‐sensitive tasks for users in remote areas. Considering the strong limitation of satellite resources in the space‐ground integrated network and insufficient energy of local user equipment, firstly, a satellite‐UAV cluster‐ground three‐layer edge computing network architecture is proposed in this paper. Under the condition that the delay requirements of various ground tasks are met, the task offloading problem is transformed into a Stackelberg game between ground user equipment and edge servers. In addition, it is proved that the existence of Nash equilibrium in non‐cooperative game between ground user equipment by using potential game. Finally, a Nash equilibrium iterative offloading algorithm based on Stackelberg game (NEIO‐SG) is proposed to find the optimal offloading strategy for tasks to minimize the system offloading cost and the optimal forwarding percentage strategy for offloading tasks to maximize the utility function of the edge server. Simulation results show that compared to other baseline algorithms, NEIO‐SG reduces the total system latency during task offloading by about 13 and the energy consumption of the edge server by about 35.

Improvement of post BER performance in computer communication on Viterbi algorithm

Computer communication is the pivotal exchange of information and data among computing devices, exerting substantial influence over network communication quality. The conventional approach has typically centred on enhancing Bit Error Rate (BER) performance to bolster information quality during the transmission process. However, our research pioneers a novel strategy, focusing on post-BER improvement. Our innovative method prioritizes enhancing information quality at the receiver's end by implementing a unique approach. We employ the Viterbi algorithm to elevate the quality of individual words, ensuring accurate word recognition and precise comprehension. The ultimate goal is to provide end-users with an unambiguous and accurate understanding of transmitted words. Our simulation results conclusively demonstrate the effectiveness of this approach. Following the reception of words, we successfully attain the correct word information with remarkable accuracy. This approach transforms word-level information processing, safeguarding against inaccuracies and ambiguities that may otherwise compromise the integrity of data transfer. In summary, our research introduces a paradigm shift in optimizing information quality within computer communication networks. By focusing on post-BER improvements and harnessing the power of the Viterbi algorithm, we enable the receiver to decode words with precision and clarity. This breakthrough promises to enhance the overall quality and reliability of information exchange, further solidifying the foundation of modern computer communication.

Reconstruction of Communication Signal in Wireless Networks Based on Perturbation Compression Perception

<p>With the maturity and development of new generation communication technology, the demand for wireless network communication quality is getting higher and higher. However, the existing wireless network data transmission models are greatly affected by the signal quality in the data transmission process, which seriously affects the quality of data transmission. To address the problem of signal perturbation affecting communication quality in wireless network communication, this study designs an improved perturbation compression reconstruction algorithm that can be used to process block-structured data based on the block sparse structure in the original signal, and constructs a single-user wireless network communication data transmission model based on this algorithm. The performance simulation test of the model shows that the MSE values of the model are lower than those of the conventional and perfect schemes used as comparisons under the same noise conditions and the transmitted compressed data length conditions. When the variance of Gaussian white noise is 0.125, the MSEs of the research design model, the conventional scheme and the perfect scheme are 0.031, 0.048, and 0.047, respectively. Experimental data show that the improved disturbance compressed sensing reconstruction algorithm can better reconstruct the compressed information and reduce the information loss caused by the disturbance in the compression process on the premise of removing the signal disturbance. This research result has reference significance for improving the signal quality of wireless network communication.</p> <p> </p>

Software defined network‐based multipath state‐aware routing with traffic prediction in satellite network

AbstractUneven traffic demand in satellite networks can lead to link congestion and influence network communication quality. To tackle this problem, we propose a state‐aware routing algorithm based on traffic prediction to disperse network traffic. Reducing the onboard processing requirements, the routing algorithm in this paper introduces a software‐defined network to decouple the control plane and data plane of the satellite network. Also, to better sense the trend of network state, the routing algorithm devises a Spatial‐Temporal Attention Fusion Graph Neural Network (STAFGNN) to predict the future network state by capturing the spatial‐temporal correlation of satellite network traffic. In the control plane, the routing algorithm senses the network state by predicting the future satellite traffic and aggregates the real‐time states of neighboring satellites to identify the load level of the zone. The data plane forwards data based on the control information. Based on the routing algorithm in this paper, multipath routing is designed to reduce the probability of link congestion by dispersing each end‐to‐end traffic. The simulation results demonstrate that the routing algorithm in this paper reduces the number of congestion links and balances the load distribution. The proposed algorithm provides an idea to introduce deep learning to solve the load balancing problem in satellite networks.

Deep reinforcement learning‐based full‐duplex link scheduling in federated learning‐based computing for IoMT

SummaryThe rapid developments in mini‐hardware manufacturing and wireless network communications have enabled the Internet of Medical Things (IoMT) to provide continuous healthcare services over the Internet. Federated learning (FL) combined with blockchain technology has been a popular way to resolve privacy‐preserving data sharing in IoMT‐based wireless body area networks (WBANs), on the other side, communication payloads become much heavier than traditional healthcare sensor network, because central server should aggregate the model updates and orchestrate the training tasks. The high latency will lead to FL's low system efficiency. However, the existing studies on FL mainly focus on the system design and algorithm optimization, which ignore a critical problem of data transmission in the FL system. To improve the communication performance, we proposed a two‐tier scheduling algorithm in which a full‐duplex (FD) multiple access based scheduling algorithm is employed to improve channel utility and network throughput, and decrease the delay in tier II. A deep reinforcement learning (DRL) framework is used to generate the FD links between hubs and access points (APs) which jointly considers the channel state, fairness, and delay. Therefore, the DRL‐based FD Link Scheduling (R‐FDLS) algorithm is proposed. When the traffic volume is different or in various distribution scenarios, the evaluation results demonstrate that the proposed algorithm significantly improves the network communication quality, as well as has obvious advantages compared to several baselines.

Multi-index joint node selection protocol in UAV ad hoc network

In the application scenario of a UAV ad hoc network, aiming at the problems of low packet forwarding success rate and premature death of some nodes in greedy perimeter stateless routing (GPSR) protocol, a multi-index joint node selection-GPSR protocol (MT-GPSR) is proposed. Based on greedy forwarding, MT-GPSR protocol comprehensively considers the link holding time of adjacent nodes, the residual energy of adjacent nodes, and the node degree to jointly select the next hop node, and proposes an AHP maximum entropy criterion weighting algorithm, which reasonably weights the node index value, adds the weighted index values to obtain the selection priority value, and selects the neighbor node whose priority value is the best under the weighting condition as the next hop node for data forwarding, so as to improve the efficiency of data forwarding. At the same time, the network life is prolonged. The simulation results show that compared with the GPSR algorithm and GPSR-NMP algorithm, this algorithm ensures stable communication between UAVs, improves the network communication quality, and improves the network lifetime.

Digital interference signal filtering on laser interface for optical fiber communication

INTRODUCTION: Fiber laser communication is a communication method that uses laser and fiber medium to realize data transmission and information output OBJECTIVES: In order to reduce the signal interference of optical fiber communication laser interface and ensure the communication quality of optical fiber network. A filtering method of optical fiber communication laser interface interference signal based on digital filtering technology is designed. METHODS: In this paper, the interface model of optical fiber communication network is firstly constructed, and the interface noise signal is input into the digital filter bank. The digital quadrature filtering method and the least square algorithm are used to separate the denoised signals to reduce the crosstalk between the signals in the channel. In this way, the crosstalk component in the signal can be filtered out, and a better filtering processing effect of the laser interface interference signal can be achieved. RESULTS: The results of peak signal-to-noise ratio are above 25, which effectively filters the interference signal in the signal, and retains the effective signal completely. The intelligibility of optical fiber communication network in signal communication is above 0.94, and the highest value is 0.986. The distortion degree are all below 0.025, and the minimum value is 0.004. The communication bit error rate are all below 0.001, which ensures the communication quality of the network. CONCLUSION: The experimental results show that the signal noise reduction effect of the proposed method is good, which provides a reliable basis for filtering and separating interference signals of optical fiber communication laser interface.

Balanced Scheduling Method of Network Information Resources for Cloud Storage

In the network communication environment, the balanced scheduling of network information sharing resources can better improve the service quality of network communication. In the current network communication sharing resource balanced scheduling process, there are some problems, such as the completion time of resource scheduling is too long, the cost consumption is large, and so on. This paper proposes a balanced scheduling method of network information resources for cloud storage. By constructing the storage model of network communication shared resources, the network communication structure under big data is layered. Through the characteristic analysis of shared resource, equilibrium ratio is introduced to obtain the fitness function of network communication shared resources. The fitness function and convergence factor are used to solve the problem. The experimental results show that the network information resource balanced scheduling method for cloud storage needs shorter completion time and lower cost, which fully meets the research requirements.

Connection Quality Prediction and Nonlinear Control of Power Grid Communication Wireless Network

Learn about effective and uncontrolled gambling on wireless networks. Firstly, according to the control purpose, considering the reliability requirement of microgrid for network communication, the characteristics of wireless sensor network communication quality of service in microgrid, the influence of wireless connection reliability, and the mathematical standard of wireless communication are determined. Then, according to the estimation of the occurrence time of wireless communication link reliability, the reliability of wireless sensor network communication link in a smart grid is improved based on a fuzzy nonlinear control algorithm. Finally, the security and reliability of the control system described in this paper are measured by simulation. The experimental results show that the reliability of the wireless communication estimation time estimation algorithm and the power control algorithm based on fuzzy control can estimate the reliability, shortsightedness, and accuracy of good connections in real time. By adjusting the output power of the node, the connection quality and reliability can be controlled stably.

Smart substation network quality monitoring and fault prediction

The smart substation communication network is the basis for information sharing of various devices in the substation. Its operation status has an important impact on the safe operation of the substation and even the power grid. Therefore, real-time status monitoring of the smart substation communication network is becoming more and more important. Aiming at the problems of single dimension, insufficient real-time performance and manual fault analysis in existing substation communication network state monitoring technology, this paper proposes a method of smart substation communication network state monitoring and fault prediction based on network communication quality. This paper uses switch ACL technology and coloring technology to obtain communication quality indexes such as bandwidth utilization, delay, and packet loss rate in real time; based on a multi-dimensional evaluation algorithm, a comprehensive evaluation model of network communication quality is constructed; the model of the relationship between abnormal network communication quality and failures is established. Finally, real-time monitoring of network communication quality and fault prediction are realized. The application analysis in a typical 110 kV substation shows that this method can effectively evaluate the network communication quality and accurately predict failures, and can guide operationer and maintenaner to quickly restore the normal operation of the communication network.

Hardware Decoding Accelerator of (73, 37, 13) QR Code for Power Line Carrier in UPIoT

The proposal of the ubiquitous power Internet of Things (UPIoT) has increased the demand for communication coverage and data collection of smart grid; the quantity and quality of communication networks are facing greater challenges. This brief applies (73, 37, 13) quadratic residue (QR) codes to power line carrier technology to improve the quality of local data communication in UPIoT. In order to improve the decoding performance of the QR codes, an induction method for the error pattern is proposed, which can divide the originally coupled error pattern into six parts and reuse the same module for decoding. This method greatly reduces the resource requirements, so that (73, 37, 13) QR code can be implemented on FPGA hardware. Notably, the hardware architecture is a modular framework, which can fit into an FPGA with different sizes. As an example (73, 37, 13), QR code is implemented on Intel Arria10 FPGA; the experimental result shows that the maximum decoding frequency of this architecture is 21.7 M Hz, which achieves 4121x speedup compared to CPU. Moreover, the proposed architecture benefits from high flexibility, such as modular design and decoding framework in the form of the pipeline which can be seen as an alternative scheme for decoding long‐length QR codes.

Research and application of network status prediction based on BP neural network for intelligent production line

In the intelligent production line network communication process of the Industrial IoT, communication node congestion will cause the communication quality to decrease, thereby affecting the production efficiency. Therefore, accurately predicting the status of network and making adjustments to the network in real time is of great significance to improving the quality of network communication. Aiming at the urgent problem of the network communication quality of the intelligent production line, this paper proposes a network status prediction algorithm for the intelligent production line. The algorithm uses the ARMA prediction model to predict the network data, and calculates and predicts the entire network operation through the optimized BP neural network. At the same time, an intelligent production line network prediction system is designed based on the algorithm. The system can predict the network operation status in advance, reducing the impact of network status fluctuations on the production efficiency of the intelligent production line. The simulation results show that after a large number of network data prediction experiments, the optimal data prediction period is obtained. Under this period, the accuracy of network status prediction reaches 90%.

Investigation of real-time optimization based on CAN bus

Aiming at the problem of CAN bus network transmission delay which affects the transmission rate, a bus network transmission delay model is established. The main indicators of network transmission delay are modeled. A hybrid optimization combining message offset compensation and identifier optimization is proposed. In terms of overall optimization, an optimization method for message segmentation and encoding scheme is designed, and a method for offset compensation of delayed messages is designed for partial parts. Symtavision software is used to simulate network conditions of the two CAN buses. Analyse the main indicators of delay after the optimization plan is adopted. The simulation results show that the hybrid optimization scheme can reduce the delay by more than 16% compared with before, which significantly improves the network communication quality, and improves the network transmission rate and scalability.

Testing of the Wireless Sensor Network for the Express-Diagnostic of the State of Plant

The authors reviewed the types of network testing. The most common are simulation modeling, mock-up modeling, and full-scale experiments. It was examined existing software environments for simulation and debugging kits for mock testing. The main definitions and terms on the theory of experiment planning are given. According to the theory of experiment planning, the authors developed a plan for conducting a full-scale experiment and defined an algorithm for testing a wireless sensor network for express diagnostics of plants' state. Network testing parameters are the quality of network communication; network formation time; network communication distance; and battery life of sensors. The preparation and process of conducting a full-scale experiment for testing a WSN sample is described in detail. Wireless sensor network testing was carried out by different clusters, at different distances in five stages. During the experiment on testing the WSN, the operation of individual network nodes was checked, and the operation of the network as a whole. During the testing period, no abnormal operation of the sensors and the coordinator was revealed. 82 measurements were made in just five stages. The communication quality of the wireless sensor network has been checked. When testing the network, the transmission of data packets from the sensors to the coordinator was mostly successful. The integral estimate of unsuccessful data transmission sessions in the network was calculated. The communication range of the network at a distance of 20, 30, 40 and 60 m was checked. A graph of the dependence of the sensor signal power on the distance was built. Statistics were obtained on the decrease in the battery charge for each sensor. Based on the results of a full-scale experiment, the operation of a wireless sensor network for express diagnostics of the state of plants is considered successful. Keywords: Zigbee, wireless sensor network, sensor, full-scale experiment.

التنبؤ بتغطية أبراج شبكة الاتصالات اللاسلكية 4G للمشغل "أ" باستخدام نظم المعلومات الجغرافية في مدينة جدة (دراسة حالة حي النزهة)

تعتمد أنظمة الاتصالات على إشارات أبراج الهاتف الخلوي التي تؤثر على جودة وكفاءة شبكات الاتصالات. في هذا البحث ، تم توضيح تغطية شبكة التنبؤ لشبكة 4G اللاسلكية للمشغل "A" في مدينة النزهة. الهدف الرئيسي أولاً هو الخروج بخرائط شبكة تنبؤية توضح جودة شبكات الاتصال في منطقة الدراسة وتحديد المناطق ذات التغطية الجيدة والسيئة ، من أجل الحفاظ على التغطية وتحسينها من خلال نقل الأبراج والهوائيات الخلوية ، وزيادة حجمها. الرقم ، أو من خلال تركيب أخرى جديدة في مناطق التغطية السيئة ، وهناك هدف آخر هو مقارنة هذا الناتج بكفاءة تغطية الشبكة الفعلية. في هذه الدراسة ، تم اعتماد برامج نظم المعلومات الجغرافية للتعامل مع البيانات المكانية والسمات وإدارتها ومعالجتها وتحليلها. تم استخدام امتدادات GIS لتصميم شبكات الاتصالات مثل برنامج Mentum-Planet الذي تم من خلاله حساب وتمثيل تغطية شبكة التنبؤ. تم جمع بيانات الأبراج والقطاعات الخلوية أولاً ثم معالجتها لإنشاء تنبؤ بشبكة تغطية 4G للمشغل "A" بناءً على نموذج الانتشار (Q9). تمت مقارنة النتائج لاحقًا بكفاءة الشبكة الناتجة عن اختبار القيادة. وجد أن قوة الإشارة كانت بين -95 و -75 ديسيبل. حوالي 24.2٪ و 75.8٪ من مساحة الدراسة لديها تغطية شبكية متوسطة وممتازة على التوالي. أظهر اختبار القيادة مناطق ضعف تغطية الشبكة موزعة في جميع أنحاء منطقة الدراسة. خلص هذا البحث إلى أن استخدام نظم المعلومات الجغرافية في الاتصالات يقلل من تكلفة ووقت التنفيذ. يوصى بشدة بتضمين ارتفاعات المباني في نموذج الانتشار لأنها تؤثر على انتشار موجات الاتصال ، وزيادة الأبراج الخلوية في مناطق التغطية السيئة ، وتعديل نموذج الانتشار لضمان جودة الخدمة والتغطية الفعالة.

Fault location of power communication network based on dichotomy search algorithm

In the quality degradation fault location of the power communication network, the focus of the power communication network quality degradation fault location is to reduce the test packet transmission and speed up the fault location time on the basis of accurate positioning. This paper first analyzes the traditional solar winds segment-by-segment detection and related research, which has a long positioning time, a large number of packets, and the continuous crowding of communication resources at the normal communication link during the test. In this paper, binary search algorithm is applied in fault location, at the same time, source and destination nodes are orderedly exchanged during fault location. Finally, the advantages of this method in reducing positioning time, reducing the test case packets and resource crowding are verified through simulation and engineering practice.

A Scalable FMI-Compatible Cosimulation Platform for Synchrophasor Network Studies

Rigorous evaluation of a synchrophasor network in terms of communication network quality, cybersecurity, and phasor data concentrator (PDC) performance is presented. To this aim, a cosimulation platform is designed based on the multiagent environment for complex system cosimulation platform. The proposed platform is characterized by particular features including scalability (no limitation in terms of nodes/buses of communication/power systems), compatibility with the functional mock-up interface standard, and capability of synchronized integration of any two abstract simulators (in this article, NS-3 for communication network and MATLAB/Simulink for power system). The simulations are performed for the detailed model of the IEEE-34 bus distribution network including phasor measurement units and the PDC. The simulations include (1) evaluation of widely used synchrophasor communication technologies (i.e., user datagram protocol and transmission control protocol), (2) evaluation of the PDC performance under both relative and absolute wait time logics, and (3) assessment of cybersecurity vulnerabilities of the synchrophasor network. The proposed platform can be utilized for implementation and evaluation of communication technologies/protocols of synchrophasor networks in terms of bandwidth, packet missing, latency, and cybersecurity vulnerabilities. Data pushing mechanism of the PDC can be also evaluated using the proposed platform.

Software defined solutions for sensors in 6G/IoE

In order to widely apply 6G/IoE (Internet of Everything) to various scenarios in real life and link the infrastructure closely related to people through the network, this paper analyzes the dual-channel architecture defined by the software of wireless sensor in 6G/IoE and proposes a reasonable solution to reduce the signal interference, so as to better transmit the related signals. Moreover, the node data in the sensor is processed by fog computing and edge computing, and the network communication quality is judged by transmission energy consumption and packet loss rate. On this basis, the delay, channel transmission, and total network throughput are analyzed to find the problem. The results show that the dual-channel architecture of software-defined wireless sensor can transmit control messages and sensor messages of nodes separately, which not only reduces the traffic load of single channel, but also avoids collision between control messages and sensor messages of nodes. It improves the information transmission performance of the network and facilitates the further application of 6G/IoE. Therefore, the analysis of the software definition of sensor and the solution proposed play an important role in the widespread use of 6G/IoE.

Reinforced Secure Gossiping Against DoS Attacks in Post-Disaster Scenarios

During and after a disaster, the perceived quality of communication networks often becomes remarkably degraded with an increased ratio of packet losses due to physical damages of the networking equipment, disturbance to the radio frequency signals, continuous reconfiguration of the routing tables, or sudden spikes of the network traffic, e.g., caused by the increased user activity in a post-disaster period. Several techniques have been introduced so far (mainly using data retransmission mechanisms) to tolerate such circumstances. Among them, gossiping has been shown to be efficient in the recovery from message losses. However, a conventional gossiping scheme may exhibit security problems, which can be exploited for further attacks (such as Denial of Service - DoS attack). For instance, the flooding method used by the gossiping can be used to forward the traffic towards many vulnerable nodes to drain their resources and compromise them. Typically, protection against DoS attacks is realized by using cryptographic primitives. However, their scalability limits and costs make them improper for emergency communications after a disaster. In this article, we introduce an approach based on reinforcement learning and game theory to protect the gossiping scheme from DoS attacks without incurring the costs of cryptographic primitives. In our method, nodes properly select which requests to satisfy, which in turn helps other nodes to avoid receiving manipulated gossip messages from malicious and colluded nodes. Additionally, our method operates without exploiting any cryptographic primitives, which prevents excessive energy waste that is undesired in post-disaster resilient networking. Simulation experiments performed in OMNeT++ confirmed the advantages of our approach over the reference schemes in terms of reliability, security, overhead, latency, and power efficiency.