Cutting-Edge Challenges in Communication Technology and Computer Network Security

The rapid development of communication technology and computer networks has brought a lot of convenience to production and life,but it also increases the security problem.Information security has become one of the severe challenges faced by people in the digital age.Currently,the security problems facing the field of communication technology and computer networks in China mainly include the evolution of offensive technology,the risk of large-scale data transmission,the potential vulnerabilities introduced by emerging technology,and the dilemma of user identity verification.This paper analyzes the frontier challenges of communication technology and computer network security,and puts forward corresponding solutions,hoping to provide ideas for coping with the security challenges of communication technology and computer networks.

FINDING THE OPTIMAL LENGTH OF DATA FRAME IN PLC COMPUTER NETWORK

The length of data frame is an important parameter in Medium Access Control(MAC) layer protocol. A method of finding the optimal length of data frame when impulsive disturbance is involved in PowerLine Communications (PLC) is proposed. Having analyzed the characteristics of impulsive disturbance in powerline and the collision mechanism between the disturbance and data frame, this letter gives the function of the network channel utilization with the length of data frame in MAC layer and the impulsive disturbance. Our stochastic process simulation shows that it is feasible to get the optimal length of data frame.

PLC-Oriented Access Point Location Planning Algorithm in Smart-Grid Communication Networks

In this study, we investigate the optimal location of access points （APs） to connect end nodes with a service provider through power-line communication in smartgrid communication networks. APs are the gateways of power-distribution communication networks, connecting users to control centers. Hence, they are vital for the reliable, safe, and economical operation of a power system. This paper proposes a planning method for AP allocation that takes into consideration economics, reliability, network delay, and （n-l） resilience. First, an optimization model for the AP location is established, which minimizes the cost of installing APs, while satisfying the reliability, network delay, and （n-1） resilience constraints. Then, an improved genetic algorithm is proposed to solve the optimization problem. The simulation results indicate that the proposed planning method can deal with diverse network conditions satisfactorily. Furthermore, it can be applied effectively with high flexibility and scalability.

The 23rd International Conference on Computer Communication and Networks (ICCCN 2014)

August 4-August 7, 2014 Shanghai, China http:/www.icccn.org/icccn14/ICCCN is one of the leading international conferences for presenting noel ideas and fundamental advances in the fields of computer communications and networks. ICCCN serves to foster communication among researchers and practitioners with

Implementation of CAN-bus Intelligent Network Communication Equipment Based on PLC

The development trend of PLC is that the functions are more, the integration level is greater and the network function is greater. Nowadays, the manufacturers of PLC develop there own network. PLC technique has two development trends. On one hand, PLC network system is not a self-contained closed system any longer and develops towards open system. Various PLC not only has distinctive PLC network systems and completes device control task, but also network with the superior computer management system to realize information exchange, which makes it become one part of information management system. On the other hand, the field-bus technique is widely applied. PLC is connected with the intelligent equipments installed on site such as intelligent instrument, sensor, intelligent solenoid valve, intelligent drive actuator by a transmission media （ such as twisted pair, coaxial cable and cable）, and they transmit information mutually according to the same communication protocol, which can form a field industrial control network. Compared with single PLC remote network, the network not only has the advantages of flexible configurations, easy expansion, low cost and higher cost perfomaance, but also has opening significance.

Falcon Optimization Algorithm-Based Energy Efficient Communication Protocol for Cluster-Based Vehicular Networks

Rapid development in Information Technology(IT)has allowed several novel application regions like large outdoor vehicular networks for Vehicle-to-Vehicle(V2V)transmission.Vehicular networks give a safe and more effective driving experience by presenting time-sensitive and location-aware data.The communication occurs directly between V2V and Base Station(BS)units such as the Road Side Unit(RSU),named as a Vehicle to Infrastructure(V2I).However,the frequent topology alterations in VANETs generate several problems with data transmission as the vehicle velocity differs with time.Therefore,the scheme of an effectual routing protocol for reliable and stable communications is significant.Current research demonstrates that clustering is an intelligent method for effectual routing in a mobile environment.Therefore,this article presents a Falcon Optimization Algorithm-based Energy Efficient Communication Protocol for Cluster-based Routing(FOA-EECPCR)technique in VANETS.The FOA-EECPCR technique intends to group the vehicles and determine the shortest route in the VANET.To accomplish this,the FOA-EECPCR technique initially clusters the vehicles using FOA with fitness functions comprising energy,distance,and trust level.For the routing process,the Sparrow Search Algorithm(SSA)is derived with a fitness function that encompasses two variables,namely,energy and distance.A series of experiments have been conducted to exhibit the enhanced performance of the FOA-EECPCR method.The experimental outcomes demonstrate the enhanced performance of the FOA-EECPCR approach over other current methods.

Covert LEO Satellite Communication Aided by Generative Adversarial Network Based Cooperative UAV Jamming

In this paper,we study the covert performance of the downlink low earth orbit(LEO)satellite communication,where the unmanned aerial vehicle(UAV)is employed as a cooperative jammer.To maximize the covert rate of the LEO satellite transmission,a multi-objective problem is formulated to jointly optimize the UAV’s jamming power and trajectory.For practical consideration,we assume that the UAV can only have partial environmental information,and can’t know the detection threshold and exact location of the eavesdropper on the ground.To solve the multiobjective problem,we propose the data-driven generative adversarial network(DD-GAN)based method to optimize the power and trajectory of the UAV,in which the sample data is collected by using genetic algorithm(GA).Simulation results show that the jamming solution of UAV generated by DD-GAN can achieve an effective trade-off between covert rate and probability of detection errors when only limited prior information is obtained.

Ultimately Bounded Output Feedback Control for Networked Nonlinear Systems With Unreliable Communication Channel: A Buffer-Aided Strategy

This paper concerns ultimately bounded output-feedback control problems for networked systems with unknown nonlinear dynamics. Sensor-to-observer signal transmission is facilitated over networks that has communication constraints.These transmissions are carried out over an unreliable communication channel. In order to enhance the utilization rate of measurement data, a buffer-aided strategy is novelly employed to store historical measurements when communication networks are inaccessible. Using the neural network technique, a novel observer-based controller is introduced to address effects of signal transmission behaviors and unknown nonlinear dynamics.Through the application of stochastic analysis and Lyapunov stability, a joint framework is constructed for analyzing resultant system performance under the introduced controller. Subsequently, existence conditions for the desired output-feedback controller are delineated. The required parameters for the observerbased controller are then determined by resolving some specific matrix inequalities. Finally, a simulation example is showcased to confirm method efficacy.

Secrecy Outage Probability Minimization in Wireless-Powered Communications Using an Improved Biogeography-Based Optimization-Inspired Recurrent Neural Network

This paper focuses on wireless-powered communication systems,which are increasingly relevant in the Internet of Things(IoT)due to their ability to extend the operational lifetime of devices with limited energy.The main contribution of the paper is a novel approach to minimize the secrecy outage probability(SOP)in these systems.Minimizing SOP is crucial for maintaining the confidentiality and integrity of data,especially in situations where the transmission of sensitive data is critical.Our proposed method harnesses the power of an improved biogeography-based optimization(IBBO)to effectively train a recurrent neural network(RNN).The proposed IBBO introduces an innovative migration model.The core advantage of IBBO lies in its adeptness at maintaining equilibrium between exploration and exploitation.This is accomplished by integrating tactics such as advancing towards a random habitat,adopting the crossover operator from genetic algorithms(GA),and utilizing the global best(Gbest)operator from particle swarm optimization(PSO)into the IBBO framework.The IBBO demonstrates its efficacy by enabling the RNN to optimize the system parameters,resulting in significant outage probability reduction.Through comprehensive simulations,we showcase the superiority of the IBBO-RNN over existing approaches,highlighting its capability to achieve remarkable gains in SOP minimization.This paper compares nine methods for predicting outage probability in wireless-powered communications.The IBBO-RNN achieved the highest accuracy rate of 98.92%,showing a significant performance improvement.In contrast,the standard RNN recorded lower accuracy rates of 91.27%.The IBBO-RNN maintains lower SOP values across the entire signal-to-noise ratio(SNR)spectrum tested,suggesting that the method is highly effective at optimizing system parameters for improved secrecy even at lower SNRs.

Information Centric Networking Based Cooperative Caching Framework for 5G Communication Systems

The demands on conventional communication networks are increasing rapidly because of the exponential expansion of connected multimedia content.In light of the data-centric aspect of contemporary communication,the information-centric network(ICN)paradigm offers hope for a solution by emphasizing content retrieval by name instead of location.If 5G networks are to meet the expected data demand surge from expanded connectivity and Internet of Things(IoT)devices,then effective caching solutions will be required tomaximize network throughput andminimize the use of resources.Hence,an ICN-based Cooperative Caching(ICN-CoC)technique has been used to select a cache by considering cache position,content attractiveness,and rate prediction.The findings show that utilizing our suggested approach improves caching regarding the Cache Hit Ratio(CHR)of 84.3%,Average Hop Minimization Ratio(AHMR)of 89.5%,and Mean Access Latency(MAL)of 0.4 s.Within a framework,it suggests improved caching strategies to handle the difficulty of effectively controlling data consumption in 5G networks.These improvements aim to make the network run more smoothly by enhancing content delivery,decreasing latency,and relieving congestion.By improving 5G communication systems’capacity tomanage the demands faced by modern data-centric applications,the research ultimately aids in advancement.

A CSMA/CA based MAC protocol for hybrid Power-line/Visible-light communication networks:Design and analysis

Hybrid Power-line/Visible-light Communication(HPVC)network has been one of the most promising Cooperative Communication(CC)technologies for constructing Smart Home due to its superior communication reliability and hardware efficiency.Current research on HPVC networks focuses on the performance analysis and optimization of the Physical(PHY)layer,where the Power Line Communication(PLC)component only serves as the backbone to provide power to light Emitting Diode(LED)devices.So designing a Media Access Control(MAC)protocol remains a great challenge because it allows both PLC and Visible Light Communication(VLC)components to operate data transmission,i.e.,to achieve a true HPVC network CC.To solve this problem,we propose a new HPC network MAC protocol(HPVC MAC)based on Carrier Sense Multiple Access/Collision Avoidance(CSMA/CA)by combining IEEE 802.15.7 and IEEE 1901 standards.Firstly,we add an Additional Assistance(AA)layer to provide the channel selection strategies for sensor stations,so that they can complete data transmission on the selected channel via the specified CSMA/CA mechanism,respectively.Based on this,we give a detailed working principle of the HPVC MAC,followed by the construction of a joint analytical model for mathematicalmathematical validation of the HPVC MAC.In the modeling process,the impacts of PHY layer settings(including channel fading types and additive noise feature),CSMA/CA mechanisms of 802.15.7 and 1901,and practical configurations(such as traffic rate,transit buffer size)are comprehensively taken into consideration.Moreover,we prove the proposed analytical model has the solvability.Finally,through extensive simulations,we characterize the HPVC MAC performance under different system parameters and verify the correctness of the corresponding analytical model with an average error rate of 4.62%between the simulation and analytical results.

Sensing and Communication Integrated Fast Neighbor Discovery for UAV Networks

In unmanned aerial vehicle(UAV)networks,the high mobility of nodes leads to frequent changes in network topology,which brings challenges to the neighbor discovery(ND)for UAV networks.Integrated sensing and communication(ISAC),as an emerging technology in 6G mobile networks,has shown great potential in improving communication performance with the assistance of sensing information.ISAC obtains the prior information about node distribution,reducing the ND time.However,the prior information obtained through ISAC may be imperfect.Hence,an ND algorithm based on reinforcement learning is proposed.The learning automaton(LA)is applied to interact with the environment and continuously adjust the probability of selecting beams to accelerate the convergence speed of ND algorithms.Besides,an efficient ND algorithm in the neighbor maintenance phase is designed,which applies the Kalman filter to predict node movement.Simulation results show that the LA-based ND algorithm reduces the ND time by up to 32%compared with the Scan-Based Algorithm(SBA),which proves the efficiency of the proposed ND algorithms.

A Review of Artificial Intelligence Applications in Contemporary Computer Network Technologies

Rapid advancement in science and technology has seen computer network technology being upgraded constantly, and computer technology, in particular, has been applied more and more extensively, which has brought convenience to people’s lives. The number of people using the internet around the globe has also increased significantly, exerting a profound influence on artificial intelligence. Further, the constant upgrading and development of artificial intelligence has led to the continuous innovation and improvement of computer technology. Countries around the world have also registered an increase in investment, paying more attention to artificial intelligence. Through an analysis of the current development situation and the existing applications of artificial intelligence, this paper explicates the role of artificial intelligence in the face of the unceasing expansion of computer network technology.

Generative Adversarial Networks Based Digital Twin Channel Modeling for Intelligent Communication Networks

Integration of digital twin(DT)and wireless channel provides new solution of channel modeling and simulation,and can assist to design,optimize and evaluate intelligent wireless communication system and networks.With DT channel modeling,the generated channel data can be closer to realistic channel measurements without requiring a prior channel model,and amount of channel data can be significantly increased.Artificial intelligence(AI)based modeling approach shows outstanding performance to solve such problems.In this work,a channel modeling method based on generative adversarial networks is proposed for DT channel,which can generate identical statistical distribution with measured channel.Model validation is conducted by comparing DT channel characteristics with measurements,and results show that DT channel leads to fairly good agreement with measured channel.Finally,a link-layer simulation is implemented based on DT channel.It is found that the proposed DT channel model can be well used to conduct link-layer simulation and its performance is comparable to using measurement data.The observations and results can facilitate the development of DT channel modeling and provide new thoughts for DT channel applications,as well as improving the performance and reliability of intelligent communication networking.

Covert Communication in Integrated High Altitude Platform Station Terrestrial Networks

In recent years,Internet of Things(IoT)technology has emerged and gradually sprung up.As the needs of largescale IoT applications cannot be satisfied by the fifth generation(5G)network,wireless communication network needs to be developed into the sixth generation(6G)network.However,with the increasingly prominent security problems of wireless communication networks such as 6G,covert communication has been recognized as one of the most promising solutions.Covert communication can realize the transmission of hidden information between both sides of communication to a certain extent,which makes the transmission content and transmission behavior challenging to be detected by noncooperative eavesdroppers.In addition,the integrated high altitude platform station(HAPS)terrestrial network is considered a promising development direction because of its flexibility and scalability.Based on the above facts,this article investigates the covert communication in an integrated HAPS terrestrial network,where a constant power auxiliary node is utilized to send artificial noise(AN)to realize the covert communication.Specifically,the covert constraint relationship between the transmitting and auxiliary nodes is derived.Moreover,the closed-form expressions of outage probability(OP)and effective covert communication rate are obtained.Finally,numerical results are provided to verify our analysis and reveal the impacts of critical parameters on the system performance.

Mobile Network Computer Can Better Describe The Future of Information Society

In the paper, we illustrate the importance of the concept of mobile network computer from a technological perspective. Because of the usefulness of mobile network computers, with the growth of the Internet of things, mobile network computers may include not only TV box audio-visual equipment, wireless household appliances, and mobile communication equipment, but may also include devices such as intelligent foot rings, smart watches, smart glasses, smart shoes and smart coats. Considering the different types of networks, e.g. IP multimedia Subsystem(IMS), we explain why some network elements are inaccurate and misleading from a technological perspective. We aim to popularize the concept of mobile network computers for its accuracy and importance, which better define modern mobile terminals and reflects the nature of multiple mobile terminals based on the structure of their integrated computers and the capabilities of processing multimedia. In the computer and Internet age, network computers and mobile network computers are the main terminals of fixed and mobile networks, respectively. Therefore, based on the concept of mobile network computers, we discuss the future of information society.

Guest editorial: Network architectures and communication protocols for smart industrial IoT applications

The rapid growth in hardware technologies and the fourth industrial revolution-Industry 4.0 have enabled the Internet of Things(IoT)to be smarter.One of the main drivers in Industry 4.0 is smart and secured Industrial IoT(IIoT)[1].The IIoT results from the widespread use of computers and the interconnectedness of machines.It has made software a crucial tool for almost every industry,from bakeries and arts to manufacturing facilities and healthcare systems[2].The IIoT devices can be mobile and geographically distributed over a long distance,which exposes them to network disturbances,Quality of Service(QoS)degradation,and security vulnerabilities.In addition,the IIoT is a complex network at a large scale,and there is a dire need for network architecture and protocol design to accommodate these diverse domains and competencies and handle the increasing levels of complexity.Therefore,in this special issue,we aim to focus on the challenges of network architectures and communication protocol design in the context of the smart industry.This special issue has attracted numerous high-quality research articles and has accepted fourteen research papers[3–16].

Information-Defined Networks:A Communication Network Approach for Network Studies

The research of complex networks facilitates the progress of various disciplines,including biology,chemistry,social science,computer,and communication engineering.Recently,it is popular to utilize complex networks to study the communication networks,such as designing efficient routing strategies and robust communication networks.However,exploiting the advantages of communication networks to investigate networks in various disciplines beyond telecommunications is still in infancy.Because of this situation,this paper proposes an information-defined network(IDN)framework by which a complex network can be abstracted as a communication network associated with multiple intelligent agents.Specifically,each component and dynamic process in this framework can be defined by information.We show that the IDN framework promotes the research of unsolved problems in the current complex network field,especially for detecting new interaction types in realworld networks.

Training-based symbol detection with temporal convolutional neural network in single-polarized optical communication system

In order to reduce the physical impairment caused by signal distortion,in this paper,we investigate symbol detection with Deep Learning(DL)methods to improve bit-error performance in the optical communication system.Many DL-based methods have been applied to such systems to improve bit-error performance.Referring to the speech-to-text method of automatic speech recognition,this paper proposes a signal-to-symbol method based on DL and designs a receiver for symbol detection on single-polarized optical communications modes.To realize this detection method,we propose a non-causal temporal convolutional network-assisted receiver to detect symbols directly from the baseband signal,which specifically integrates most modules of the receiver.Meanwhile,we adopt three training approaches for different signal-to-noise ratios.We also apply a parametric rectified linear unit to enhance the noise robustness of the proposed network.According to the simulation experiments,the biterror-rate performance of the proposed method is close to or even superior to that of the conventional receiver and better than the recurrent neural network-based receiver.

Secure vehicular data communication in Named Data Networking

Vehicular data misuse may lead to traffic accidents and even loss of life,so it is crucial to achieve secure vehicular data communications.This paper focuses on secure vehicular data communications in the Named Data Networking(NDN).In NDN,names,provider IDs and data are transmitted in plaintext,which exposes vehicular data to security threats and leads to considerable data communication costs and failure rates.This paper proposes a Secure vehicular Data Communication(SDC)approach in NDN to supress data communication costs and failure rates.SCD constructs a vehicular backbone to reduce the number of authenticated nodes involved in reverse paths.Only the ciphtertext of the name and data is included in the signed Interest and Data and transmitted along the backbone,so the secure data communications are achieved.SCD is evaluated,and the data results demonstrate that SCD achieves the above objectives.