Operation Of Communication Network Research Articles

Energy-efficient resource allocation for bidirectional wireless power and information transfer over interference channels

Energy efficiency is an important performance metric for the sustainable operation of energy-limited communication networks. This study investigates an energy-efficient resource allocation strategy to maximize the energy efficiency of wireless-powered bidirectional communication over interference channels. The receivers in the system harvest energy and decode information simultaneously using a time switching or power splitting policy from data signals sent by transmitters in the forward link. The harvested energy is subsequently used to send response signals back to the transmitters in the backward link. Our objective is to jointly optimize the transmit power of the transmitters and the energy harvesting ratio of the receivers to maximize the energy efficiency of the entire system while maintaining the minimum required data rates in both the forward and backward links. Considering the non-convexity and NP-hardness of this optimization problem, we first apply nonlinear fractional programming and a dual method to derive an analytical expression for each control parameter and then propose an iterative algorithm to find suboptimal solutions with low computational complexity. The simulation results show that the proposed algorithm adjusts both the transmit power and energy harvesting ratio adaptively considering the co-channel interference and thus achieves near-optimal energy efficiency performance within a short computation time.

Secure State Estimation for Artificial Neural Networks With Unknown-But-Bounded Noises: A Homomorphic Encryption Scheme.

This article is concerned with the secure state estimation problem for artificial neural networks (ANNs) subject to unknown-but-bounded noises, where sensors and the remote estimator are connected via open and bandwidth-limited communication networks. Using the encoding-decoding mechanism (EDM) and the Paillier encryption technique, a novel homomorphic encryption scheme (HES) is introduced, which aims to ensure the secure transmission of measurement information within communication networks that are constrained by bandwidth. Under this encoding-decoding-based HES, the data being transmitted can be encrypted into ciphertexts comprising finite bits. The emphasis of this research is placed on the development of a secure set-membership state estimation algorithm, which allows for the computation of estimates using encrypted data without the need for decryption, thereby ensuring data security throughout the entire estimation process. Taking into account the unknown-but-bounded noises, the underlying ANN, and the adopted HES, sufficient conditions are determined for the existence of the desired ellipsoidal set. The related secure state estimator gains are then derived by addressing optimization problems using the Lagrange multiplier method. Lastly, an example is presented to verify the effectiveness of the proposed secure state estimation approach.

Fractional-Order Sliding Mode Load Frequency Control and Stability Analysis for Interconnected Power Systems With Time-Varying Delay

The universal use of open communication networks in interconnected power systems has changed the constant delay in the formerly dedicated channels into time-varying delay. The delay will deteriorate the dynamic performance of the load frequency control and lead to system frequency instability. This paper presents a fractional-order sliding mode controller for interconnected power systems with time-varying delay and performs stability analysis based on the Lyapunov direct method. Firstly, fractional-order integral sliding mode control is used to improve the stability of interconnected power systems containing time-varying delay. This expands the delay margin by taking advantage of the scalability of the fractional-order to the sliding mode surface. Then, the Riemann-Liouville fractional-order Lyapunov functional is introduced to stability analysis. This reduced the conservatism of the stability analysis by adjusting the upper limit of the functional integral. Lastly, combining Lyapunov's theory and integral inequality to obtain the stability conditions of the time-varying delay power system described by linear matrix inequality, and bring the stability margin of the system. The simulation results show that the designed controller can guarantee that the maximum delay time of the system is less than a predefined upper limit. The proposed control strategy obtains a larger stability margin than the other four scenarios. Additional simulation study was also conducted to verify its robustness to load variations and wind fluctuations.

Networks method of hybrid construction and support of data transmission routes in programmed tools of mobile radio communication based on neural networks

The article proposes a method of hybrid construction and support of data transmission routes in programmable means of mobile radio communication based on neural networks. Taking into account the peculiarities of the operation of mobile radio communication networks and means of communication, the article proposes to intellectualize the processes of managing data flows by using knowledge processing technologies in the construction of a control system. The construction of the control system is based on the use of neural networks, the methodology proposes three main steps of its construction, namely the method of hybrid construction of data transmission routes, the method of maintaining data transmission routes and modeling the process of construction and maintenance of data transmission routes in the network using neural networks. Unlike similar methods, which: are used in stationary communication networks with a small number of end nodes, without the possibility of monitoring the functions of data transmission routes; which are characterized by the absence of a clear decision-making hierarchy and the presence of unpredictability when applied in data transmission systems of mobile radio communication networks; do not take into account the peculiarities of the functioning of mobile radio communications. The proposed technique is able to build data transmission routes, increases the time of network operation and reduces the loading of network channels based on the application of a hybrid structure of neural network construction, by minimizing service traffic in the information direction; selection of the type, number and method of control of data transmission routes; introduction of the hierarchy of the decision-making process for the construction of the data transmission route and the selection of data parameters, taking into account the characteristic features of the use of programmable mobile communication tools to ensure the given quality of network service under different conditions of operation of mobile radio communication tools, using neural networks.

A METHOD OF PROTECTING INFORMATION IN CYBER-PHYSICAL SPACE

The subject of the study is the processes of ensuring the reliability and security of information in cyber-physical space. The objective is to develop recommendations for the implementation of a method of information security in cyber-physical space. The development is based on the technology of ultra-wideband signals circulating in wireless communication channels. The task is to ensure the stable and reliable operation of the airborne wireless mobile communication network, which is the main component of cyberspace and its most vulnerable link to destructive influences. Methods used: methods of analytical modelling and time-position pulse coding. The following results were obtained. It is shown that in order to ensure high quality of wireless network operation, it is necessary to expand its bandwidth, which is limited by the physical resource of the radio frequency spectrum. It is proposed to overcome this contradiction by applying the technology of ultra-wideband signals, the base of which is much larger than one. In this case, the information signal is emitted without a carrier frequency simultaneously in the entire frequency band, provided that the signal level is lower than the noise level. The method of positional-time coding is used, in which each information bit is encoded by hundreds of ultra-short chip pulses arriving in a certain sequence. In such wireless communication systems, the use of autocorrelation reception of modulated ultra-wideband signals is proposed. A comparative analysis has shown that the wireless network with the best reliability and noise immunity is the one where the time separation of the reference and information signals is applied. During the first half of the bit interval, the switch closes the transmitter output directly to the ultra-wideband signal generator, forming a reference signal. In the middle of the bit interval, the switcher switches the output to one of two possible positions depending on the signal "zero" or "one", forming the information part of the signal. Conclusions. Systems with autocorrelation reception and separate transmission of reference and information signals provide a high level of structural

Neural network-based fiber optic cable fault prediction study for power distribution communication network

Abstract As the foundation of communication networks, optical fiber carries huge network traffic, so the prediction of fiber optic cable faults is an important guarantee for the operation of communication networks. Based on the combination of fiber optic system networking technology and network management data, this study constructs an alarm correlation analysis method by using data mining technology to obtain the data set of the fault prediction model for the problem of low fault prediction accuracy of traditional communication networks. The dataset is used to balance the sample data by generating a small number of new samples through the generative adversarial network. The memory-based feature generation convolutional network is proposed to enhance the feature interaction to realize fault prediction in communication networks. The prediction model has a high prediction accuracy of 98.68%, which saves about 160 min for repair work through the application of fiber optic cable fault prediction, which compares well with other models. Fault prediction based on neural networks can provide assistance in the operation and maintenance of distribution communication networks.

Game learning‐based system identification with binary‐valued observations under DoS attacks

SummaryThe rapid progress in computer, communication, and sensor technology has led to the proliferation of cyber‐physical systems (CPSs) which have become integral to various sectors. However, their heavy dependence on open communication networks makes them vulnerable to network‐based attacks. To tackle these security concerns, this paper delves into game learning‐based system identification with binary‐valued observations in the presence of Denial‐of‐Service (DoS) attacks. We first formulate a game model to capture interactions between the attacker and defender. Focusing on piecewise constant DoS attacks, we then devise a defense strategy grounded in game learning principles. This strategy paves the way for crafting estimation algorithms for both the attack strategy and system parameters, with their performance scrutinized in specific stages. Through meticulous analysis and comprehensive numerical simulations, we have observed that the game learning approach outperforms the randomly selected defense strategy in terms of parameter estimation. This provides a novel and reliable approach to address security challenges within CPSs.

Reputation-Based Opportunistic Routing Protocol Using Q-Learning For Manet Attacked By Malicious Nodes: A Survey

Mobile Ad-hoc Networks (MANETs) have emerged as a viable paradigm for creating dynamic communication between mobile nodes in the absence of a permanent infrastructure. However, since MANETs are inherently decentralized and self-organizing, they are vulnerable to a variety of security concerns, especially when hostile nodes seek to interrupt communication and undermine network operations. As a consequence, developing efficient and robust routing protocols is critical to ensuring dependable and secure data transmission in MANETs. This review study gives an in-depth look into Reputation-Based Opportunistic Routing Protocols (RORPs), which use Q-Learning methods to improve MANET resistance against malicious node assaults. We provide a thorough study of current RORPs, delving into their core design ideas, underlying processes, and comparative performance evaluations. We begin with a comprehensive introduction to the fundamental concepts, issues, and security risks associated with MANETs. Following that, we explore the concepts of reputation-based routing, emphasizing the need of reputation management in discriminating between malicious and genuine nodes. The review then goes into further detail on the incorporation of Q-Learning methods into RORPs, emphasizing on how reinforcement learning mechanisms may adaptively change routing choices depending on the developing network state and the dynamic reputations of participating nodes. This article reviews 38 research papers of opportunistic routing protocol and explores the potential of computer-assisted methods for MANET. We next divide the studied RORPs into categories depending on their approach to reputation computation, learning algorithms, and cooperative enforcement methods. Furthermore, we analyze their strengths and weaknesses in terms of resilience to different sorts of attacks, as well as their influence on network performance measures including packet delivery ratio, end-to-end latency, and throughput.

Frequency regulation scheme in power system using an observer-based waiting event-triggered control with random features

Addressed in this paper is the observer-based waiting event-triggered control issue in multi-area load frequency control (LFC) power system subject to random communication delay and data packet dropout. In order to maintain the grid frequency stability of the multi-area LFC power system in an open communication network, an observer-based waiting event-triggered scheme (WETS) is proposed to deal with frequency fluctuation and extend the life of control equipments. Compared with the existing event-triggered mechanism, the proposed WETS has the merits of continuous event-triggered scheme and the periodic sampling event-triggered scheme in the both of theory and application. Then, by well considering the negative factors of data packet dropout and random time delay in data transmission, a stochastic delay-dependent multi-area LFC model is established, which involves the information of observer-based WETS, random communication delay and packet dropout in a unified structure. Further, an improved Lyapunov–Krasovskii functional (LKF) is constructed by dividing the interval of transmitted delay. Based on the constructed Lyapunov functional, Park’s theorem and Jensen’s integral inequality, some less conservative stabilization criteria are obtained. Finally, the validity of the proposed control method is verified via numerical examples.

Tradeoff Techniques for Stabilization of Network-Controlled DC Motor Speed Control System with Uncertainties

This paper details the development of a tradeoff techniques using the conventional time-domain method for stability assurance of network-controlled DC motor speed control system with uncertainties. The DC motor controlled using an open communication network introduces time-delays in the control loop. These time-delays are one of the factors that decides the stability and performance of the dynamical systems. Stabilization of network-controlled DC motor is achieved by tuning the network controller with concern to time-delay. The maximum extend of time-delay called delay margin is computed by developing stability criterion using Lyapunov–Krasvoskii functional and linear matrix inequality techniques. The impact of load disturbances on stability delay margins are investigated and further determining the relationship between delay margin and controller gains for network-controlled DC motor gives a tradeoff between stability and dynamic performance. Finally, proposed results for network-controlled DC motors are validated through Matlab simulation and experimental setup.

Radio Resource Management Satellite Communication Network MCDM Method

Worldwide deployment of heterogeneous wireless networks is growing as a result of consumer demand for connectivity at all times and in all places. These customers' interest in multimedia apps like video streaming and VoIP, which demand tight Quality of Service (QoS) support, is growing at the same time. With such limitations, provisioning network resources is a difficult undertaking. In fact, it might be challenging for a network operator to identify trustworthy criteria to choose the optimum network that ensures user happiness while maximising network utilisation, given the availability of numerous access technologies (WiFi, WiMAX, or cellular networks). To solve this problem, each eNB just needs to learn the traffi c conditions or patterns of its owncell in our proposal. Wireless communication systems depend heavily on radio resource management (RRM). To ensure the efficient and successful operation of wireless networks, it involves the allocation and control of radio frequency spectrum, power, and other resources. RRM is significant because it can use scarce radio resources as efficiently as possible, enhancing capacity, lowering interference, and improving service quality. Successful deployment and operation of wireless communication systems like cellular networks, Wi-Fi, and Bluetooth depend on effective RRM approaches. The need for wireless communication is growing, and new technologies and standards are constantly being developed. The methodology of radio resource management (RRM) involves a variety of techniques and algorithms designed to allocate radio resources in a way that maximizes network performance while minimizing interference. Taken as alternate parameter is Laser communication, optical networks, satellite optical communication, vibrations, satellite networks. Taken as is solar radiation power, thermal bending, micro meteorite impact, solar and lunar gravity, earth oblations method. satellite optical communication has reached near 2000 data set compare other data set. The operation of wireless communication networks depends on radio resource management (RRM). Wireless networks would have interference, congestion, and a lacklustre level of service if effective RRM procedures weren't used. RRM is therefore a key component in ensuring that wireless communication systems can provide users with dependable and high-quality services.

Application of quantum key distribution in intelligent security operation and maintenance of power communication networks

With the continuous development of power communication network and the improvement of intelligent degree, network security and operation and maintenance become more and more important. Therefore, this paper proposes a solution for intelligent security operation and maintenance of power communication network based on Quantum key distribution (QKD). QKD is an encryption technology based on the principle of quantum mechanics, which can realize secure Key exchange and resist attacks of traditional encryption algorithms. We use QKD technology to generate and distribute security keys for protecting communication and data transmission in power communication networks. The results show that the efficiency and accuracy of communication data acquisition, transmission, analysis and processing of the Artificial Intelligence for IT Operations system of the power communication network using the power Internet of Things technology are far higher than that of the traditional operation and maintenance technology, which improves the operation and maintenance accuracy of the power communication network by about 25%. The intelligent operation and maintenance system of the power communication network designed by the author, it effectively improves the communication data processing capability and the reliability of operation and maintenance results, and can meet the current practical engineering application requirements. This study provides an innovative solution for the secure operation and maintenance of power communication networks, which is of great significance for protecting the security and stable operation of power communication networks.

Enhancing LAN Failure Predictions with Decision Trees and SVMs: Methodology and Implementation

Predicting Local Area Network (LAN) equipment failure is of utmost importance to ensure the uninterrupted operation of modern communication networks. This study explores the use of machine learning algorithms to enhance the accuracy of equipment failure prediction in LAN environments. Using these algorithms to enhance LAN failure predictions involves collecting and analyzing network data, such as packet loss rates and latency, to identify patterns and anomalies. These algorithms can then predict potential LAN failures by recognizing early warning signs and deviations from normal network behavior. By leveraging machine learning, network administrators can proactively address issues, reduce downtime, and improve overall network reliability. In our study, two powerful machine learning algorithms—decision tree and support vector machine (SVM)—are used. To evaluate the effectiveness of the proposed models, a comprehensive dataset comprising various LAN equipment parameters and corresponding failure instances is utilized. The dataset is pre-processed to handle missing values and normalize features, ensuring the algorithms’ optimal performance. Performance metrics, such as accuracy, precision, recall, and F1-score, are employed to assess the predictive capabilities of the models. The excremental results of our study lead to more reliable and stable network operations by allowing early detection of potential issues and preventive maintenance. This leads to reduced downtime, improved network performance, and enhanced overall user satisfaction. They demonstrate the efficacy of both decision tree and SVM algorithms in accurately predicting LAN equipment failure.

A Methodology for Designing an Automated System to Improve the Thermal Performance of a Large Building in Operation

Many buildings built before energy performance regulations are actually in a situation of thermal discomfort and energy inefficiency. The creation of intelligent environments is moving towards new opportunities, based on real-time monitoring and on the development of sensors and technologies. Furthermore, building automation and electronic systems standards enable interoperability and interconnection between control devices and systems. The application of soft computing has significantly improved the energy efficiency; however, it requires prior assessment to design the automation functions. Temperature, humidity, air quality and energy consumption are the most commonly measured parameters, but their relationships with other operational variables such as occupancy or some building states remain as a research challenge. This article presents a methodology to develop the automation of a large existing public building. This methodology consists of two stages: 1. Assessment and diagnosis to set appropriate functions, using EN ISO 52120-1 and EN 50090 for open communication networks, and EN ISO 52120-1 to assign the technical building management. 2. System control deployment of low-cost and low-consumption input and output devices. It has been proven that it is possible to effectively automate an obsolete building with a low-cost, open-source system that can be easily applied to other buildings.

ENHANCING SECURITY IN SOFTWARE-DEFINED NETWORKING THROUGH ROUTING TECHNIQUES EXPLORATION

In today's world, network security is a key issue of information security. Virtual Networks have become an integral part of modern IT infrastructure, which presents us with challenges in the field of security. One solution to this problem is the use of software-defined networking (SDN), which provides a means to control and manage network traffic. However, as with any technology, SDN has its vulnerabilities that must be considered when deploying it. One of the tools that helps to take into account the vulnerabilities of network infrastructure is the Common Vulnerability Scoring System (CVSS) standard. It allows you to quantify the level of vulnerability of the infrastructure, which enables effective network protection. Analysis of the CVSS standard is an important stage in the development of a network security strategy. This paper analyzes the standards for building software-configured networks. It is noted that SDN is a modern approach to the design, construction, and operation of information communication networks. Using SDN makes it possible to directly program and dynamically manage the network, as well as to abstract the functionality of the infrastructure layer. However, the growing interest in SDN has revealed the shortcomings of their application in the fight against cybersecurity threats. The SDN architecture itself, external malicious attacks, and insufficient access control and encryption tools were found to be the main security challenges. The use of secure routing tools based on vulnerability metrics is proposed to increase the level of SDN data plane network security. According to the conducted analysis of SDN data plane vulnerabilities and the functionality of routing tools, the authors recommend using the CVSS standard to quantify the level of infrastructure vulnerability during the development and research of promising approaches to secure routing in the data plane of software-configured networks.

Dynamic memory event-triggered proportional-integral-based [formula omitted] load frequency control for multi-area wind power systems

Aiming at ensuring the stability of multi-area doubly fed induction generator (DFIG)-integrated wind power systems, a dynamic memory event-triggered H∞ load frequency control (LFC) scheme is presented in this article. Firstly, a unified LFC model of multi-area DFIG-integrated wind power systems is constructed considering the grid connection of the DFIG-based wind turbine. Secondly, a dynamic memory event-triggered scheme (DMETS) is proposed to reduce the utilization of communication bandwidth by introducing a dynamic threshold parameter and historical data. Furthermore, the designed multi-area LFC model is reconstructed as a time-delay system under DMETS and proportional-integral (PI) controller with transmission delays introduced by open communication network. Then, asymptotic stability criteria meeting the H∞ attenuation performance index and an H∞ controller design criterion are obtained according to a selected Lyapunov–Krasovskii functional. Finally, numerical examples are presented to demonstrate the availability of the designed control scheme and the advantages of the proposed DMETS in reducing communication burden.

Design of Observer-Based Discrete-Type PID Control for Reconstructed Jump Model of Interconnected Power System Under Hybrid Attacks

In this article, observed-based discrete proportion-integration-differentiation (PID) control for multi-area interconnected power systems is addressed under hybrid attacks. Firstly, a reconstructed jump model for interconnected power systems is proposed by taking the circumstance of data packet loss into consideration, which caused by the stochastic transmission delay of sampled data. Then, different from the traditional continuous-type PID control, an observer-based discrete-type PID control strategy is designed for discrete-time power system. Besides, due to the sampled data may be tampered or shield in open communication networks, the hybrid attacks, i.e., deception attacks and denial-of-service attacks, with random manners are considered. Furthermore, an input-to-state stable criterion is derived by constructing appropriate Lyapunov-Krasovskii functionals. Finally, the discrete-type PID controllers and observer are achieved, and the validity of proposed approach are also demonstrated in the illustrative examples section.

Resilient Load Frequency Control of Power Systems to Compensate Random Time Delays and Time-Delay Attacks

Load frequency control (LFC) of modern power systems tends to employ open communication networks to transmit measurement/control signals, which makes the LFC scheme more vulnerable to random time delays and time delay attacks. In this paper, a resilient and active time-delay-compensation-based LFC scheme is proposed to compensate the random time delays and time delay attacks. At first, a state observer is employed to estimate the state of the LFC system. Then a networked predictive control method is used to predict the control signals of the system at the future moments. Next, an evaluation and compensation scheme for random time delays and time delay attacks is constructed in the actuator side of the LFC scheme based on the updating period of the actuator and the timestamp technique. Due to the stochastic characteristics of the random time delays or TDAs, the stability condition of the proposed scheme is developed with the aid of the mean square stability theory. Moreover, a dual-loop open communication is employed in the proposed scheme to improve the reliability and resilience. At last, simulation and experiment tests are undertaken to demonstrate the effectiveness of the proposed scheme.

Software Realization of Progress Control Platform for Country House Tourism Development from the Perspective of Integrated Communication Network Operation

This paper aims to build a system platform that meets the current needs of homestay management by introducing a set of progress control platform of an advanced country homestay tourism development system and using the Android operating system as an application object by using smart phones as operating tools. The problem of Internet application in the homestay industry. This research is technically based on Android system, and introduces Java and H5 for system development. Java language can realize the basic framework of App, and H5 can realize the construction of kernel. In terms of software service, the service attitude of customer service and the consulting service provided by the owner affect consumers Buying intentions, good homestay buyers evaluations in terms of booking intentions will speed up consumers’ purchasing decisions.

The Effect of Virtual Inertia and Damping Control on the Stability Region of Load Frequency Control Systems with Time Delays

This article examines the effect of virtual inertia and damping (VID) control on the stability regions of time-delayed load frequency control (LFC) systems. Because of the substantial integration of renewable energy sources (RES) and the utilization of an open communication network for sending/receiving data and control signals, the system inertia significantly decreases, and inevitable delays are observed, both of which adversely affect the controller performance and frequency stability. For improving the stability of LFC systems including RES and delays, this study proposes the integration of the VID control and determines stability regions using the method of stability boundary locus. The regions’ boundaries are substantiated by time-domain simulations and a quasi-polynomial mapping-based root finder (QPmR) algorithm. A wide-ranging evaluation of the VID coefficients’ effects on the stability region and the system’s frequency response are presented. Results evidently divulge that with the integration of the VID control, stability regions get larger, the frequency dynamic is improved, and unstable LFC systems with delays are stabilized.