Distributed Weighted Data Aggregation Algorithm in End-to-Edge Communication Networks Based on Multi-armed Bandit

As a combination of edge computing and artificial intelligence,edge intelligence has become a promising technique and provided its users with a series of fast,precise,and customized services.In edge intelligence,when learning agents are deployed on the edge side,the data aggregation from the end side to the designated edge devices is an important research topic.Considering the various importance of end devices,this paper studies the weighted data aggregation problem in a single hop end-to-edge communication network.Firstly,to make sure all the end devices with various weights are fairly treated in data aggregation,a distributed end-to-edge cooperative scheme is proposed.Then,to handle the massive contention on the wireless channel caused by end devices,a multi-armed bandit(MAB)algorithm is designed to help the end devices find their most appropriate update rates.Diffe-rent from the traditional data aggregation works,combining the MAB enables our algorithm a higher efficiency in data aggregation.With a theoretical analysis,we show that the efficiency of our algorithm is asymptotically optimal.Comparative experiments with previous works are also conducted to show the strength of our algorithm.

Application and Challenge of Edge Computing Based on 5G Communication in Information and Communication Systems

With the rapid development of information technology,5G communication technology has gradually entered real life,among which the application of edge computing is particularly significant in the information and communication system field.This paper focuses on using edge computing based on 5G communication in information and communication systems.First,the study analyzes the importance of combining edge computing technology with 5G communication technology,and its advantages,such as high efficiency and low latency in processing large amounts of data.The study then explores multiple application scenarios of edge computing in information and communication systems,such as integrated use in the Internet of Things,intelligent transportation,telemedicine and Industry 4.0.The research method is mainly based on theoretical analysis and experimental verification,combined with the characteristics of the 5G network to optimize the edge computing model and test the performance of edge computing in different scenarios through experimental simulation.The results show that edge computing significantly improves the data processing capacity and response speed of ICS in a 5G environment.However,there are also a series of challenges in practical application,including data security and privacy protection,the complexity of resource management and allocation,and the guarantee of quality of service(QoS).Through the case analysis and problem analysis,the paper puts forward the corresponding solution strategies,such as strengthening the data security protocol,introducing the intelligent resource scheduling system and establishing a multi-dimensional service quality monitoring mechanism.Finally,this study points out that the deep integration of edge computing and 5G communication will continue to promote the innovative development of information and communication systems,which has a far-reaching impact and important practical significance for promoting the transformation and upgrading in the field of information technology.

Beyond Algorithms: A Comprehensive Analysis of AI-Driven Personalization in Strategic Communications

This comprehensive study investigates the multifaceted impact of AI-powered personalization on strategic communications, delving deeply into its opportunities, challenges, and future directions. Employing a rigorous mixed-methods approach, we conduct an in-depth analysis of the effects of AI-driven personalization on audience engagement, brand perception, and conversion rates across various industries and communication channels. Our findings reveal that while AI-powered personalization significantly enhances communication effectiveness and offers unprecedented opportunities for audience connection, it also raises critical ethical considerations and implementation challenges. The study contributes substantially to the growing body of literature on AI in communications, offering both theoretical insights and practical guidelines for professionals navigating this rapidly evolving landscape. Furthermore, we propose a novel framework for ethical AI implementation in strategic communications and outline a robust agenda for future research in this dynamic field.

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.

Coati Optimization-Based Energy Efficient Routing Protocol for Unmanned Aerial Vehicle Communication

With the flexible deployment and high mobility of Unmanned Aerial Vehicles(UAVs)in an open environment,they have generated con-siderable attention in military and civil applications intending to enable ubiquitous connectivity and foster agile communications.The difficulty stems from features other than mobile ad-hoc network(MANET),namely aerial mobility in three-dimensional space and often changing topology.In the UAV network,a single node serves as a forwarding,transmitting,and receiving node at the same time.Typically,the communication path is multi-hop,and routing significantly affects the network’s performance.A lot of effort should be invested in performance analysis for selecting the optimum routing system.With this motivation,this study modelled a new Coati Optimization Algorithm-based Energy-Efficient Routing Process for Unmanned Aerial Vehicle Communication(COAER-UAVC)technique.The presented COAER-UAVC technique establishes effective routes for communication between the UAVs.It is primarily based on the coati characteristics in nature:if attacking and hunting iguanas and escaping from predators.Besides,the presented COAER-UAVC technique concentrates on the design of fitness functions to minimize energy utilization and communication delay.A varied group of simulations was performed to depict the optimum performance of the COAER-UAVC system.The experimental results verified that the COAER-UAVC technique had assured improved performance over other approaches.

DCGAN Based Spectrum Sensing Data Enhancement for Behavior Recognition in Self-Organized Communication Network

Communication behavior recognition is an issue with increasingly importance in the antiterrorism and national defense area.However,the sensing data obtained in actual environment is often not sufficient to accurately analyze the communication behavior.Traditional means can hardly utilize the scarce and crude spectrum sensing data captured in a real scene.Thus,communication behavior recognition using raw sensing data under smallsample condition has become a new challenge.In this paper,a data enhanced communication behavior recognition(DECBR)scheme is proposed to meet this challenge.Firstly,a preprocessing method is designed to make the raw spectrum data suitable for the proposed scheme.Then,an adaptive convolutional neural network structure is exploited to carry out communication behavior recognition.Moreover,DCGAN is applied to support data enhancement,which realize communication behavior recognition under small-sample condition.Finally,the scheme is verified by experiments under different data size.The results show that the DECBR scheme can greatly improve the accuracy and efficiency of behavior recognition under smallsample condition.

Reliable transmission of consultative committee for space data systems file delivery protocol in deep space communication

In consultative committee for space data systems（CCSDS） file delivery protocol（CFDP） recommendation of reliable transmission,there are no detail transmission procedure and delay calculation of prompted negative acknowledge and asynchronous negative acknowledge models.CFDP is designed to provide data and storage management,story and forward,custody transfer and reliable end-to-end delivery over deep space characterized by huge latency,intermittent link,asymmetric bandwidth and big bit error rate（BER）.Four reliable transmission models are analyzed and an expected file-delivery time is calculated with different trans-mission rates,numbers and sizes of packet data units,BERs and frequencies of external events,etc.By comparison of four CFDP models,the requirement of BER for typical missions in deep space is obtained and rules of choosing CFDP models under different uplink state informations are given,which provides references for protocol models selection,utilization and modification.

Coping with the Big Data:Convergence of Communications,Computing and Storage

To cope with the impact of big data,it is proposed to integrate the traditionally individual computing,communications and storage systems,which are getting inevitably converged.An effective information system capacity is introduced and discussed,aimed at excavating potentials of information system under a new paradigm with more degrees of freedom.

Achieving Fuzzy Matching Data Sharing for Secure Cloud-Edge Communication

In this paper,we propose a novel fuzzy matching data sharing scheme named FADS for cloudedge communications.FADS allows users to specify their access policies,and enables receivers to obtain the data transmitted by the senders if and only if the two sides meet their defined certain policies simultaneously.Specifically,we first formalize the definition and security models of fuzzy matching data sharing in cloud-edge environments.Then,we construct a concrete instantiation by pairing-based cryptosystem and the privacy-preserving set intersection on attribute sets from both sides to construct a concurrent matching over the policies.If the matching succeeds,the data can be decrypted.Otherwise,nothing will be revealed.In addition,FADS allows users to dynamically specify the policy for each time,which is an urgent demand in practice.A thorough security analysis demonstrates that FADS is of provable security under indistinguishable chosen ciphertext attack(IND-CCA)in random oracle model against probabilistic polynomial-time(PPT)adversary,and the desirable security properties of privacy and authenticity are achieved.Extensive experiments provide evidence that FADS is with acceptable efficiency.

Multivariate Aggregated NOMA for Resource Aware Wireless Network Communication Security

NonorthogonalMultiple Access(NOMA)is incorporated into the wireless network systems to achieve better connectivity,spectral and energy effectiveness,higher data transfer rate,and also obtain the high quality of services(QoS).In order to improve throughput and minimum latency,aMultivariate Renkonen Regressive Weighted Preference Bootstrap Aggregation based Nonorthogonal Multiple Access(MRRWPBA-NOMA)technique is introduced for network communication.In the downlink transmission,each mobile device’s resources and their characteristics like energy,bandwidth,and trust are measured.Followed by,the Weighted Preference Bootstrap Aggregation is applied to recognize the resource-efficient mobile devices for aware data transmission by constructing the different weak hypotheses i.e.,Multivariate Renkonen Regression functions.Based on the classification,resource and trust-aware devices are selected for transmission.Simulation of the proposed MRRWPBA-NOMA technique and existing methods are carried out with different metrics such as data delivery ratio,throughput,latency,packet loss rate,and energy efficiency,signaling overhead.The simulation results assessment indicates that the proposed MRRWPBA-NOMA outperforms well than the conventional methods.

Robust and Efficient Data Transmission over Noisy Communication Channels Using Stacked and Denoising Autoencoders

We study the effects of quantization and additive white Gaussian noise(AWGN) in transmitting latent representations of images over a noisy communication channel. The latent representations are obtained using autoencoders(AEs). We analyze image reconstruction and classification performance for different channel noise powers, latent vector sizes, and number of quantization bits used for the latent variables as well as AEs’ parameters. The results show that the digital transmission of latent representations using conventional AEs alone is extremely vulnerable to channel noise and quantization effects. We then propose a combination of basic AE and a denoising autoencoder(DAE) to denoise the corrupted latent vectors at the receiver. This approach demonstrates robustness against channel noise and quantization effects and enables a significant improvement in image reconstruction and classification performance particularly in adverse scenarios with high noise powers and significant quantization effects.

The safety parameters monitoring system for the coal mine based on CAN bus communication and intelligent data acquisition

In this paper,a monitoring and controlling system for the safety in production and environmental parameters of a small and medium-sized coal mine has been developed after analyzing the current domestic coal production and security conditions. The client computer can convert the analog signal about the safety in production and environmental parameters detected from the monitoring terminal into digital signal,and then,send the signal to the coal mine safety monitoring centre. This information can be analyzed,judged,and diagnosed by the monitoring-management-controlling software for helping the manager and technical workers to control the actual underground production and security situations. The system has many advantages including high reliability,better performance of real-time monitoring,faster data communicating and good practicability,and it can effectively prevent the occurrence of safety incidents in coal mines.

Federated Learning for 6G:A Survey From Perspective of Integrated Sensing,Communication and Computation

With the rapid advancements in edge computing and artificial intelligence,federated learning(FL)has gained momentum as a promising approach to collaborative data utilization across organizations and devices,while ensuring data privacy and information security.In order to further harness the energy efficiency of wireless networks,an integrated sensing,communication and computation(ISCC)framework has been proposed,which is anticipated to be a key enabler in the era of 6G networks.Although the advantages of pushing intelligence to edge devices are multi-fold,some challenges arise when incorporating FL into wireless networks under the umbrella of ISCC.This paper provides a comprehensive survey of FL,with special emphasis on the design and optimization of ISCC.We commence by introducing the background and fundamentals of FL and the ISCC framework.Subsequently,the aforementioned challenges are highlighted and the state of the art in potential solutions is reviewed.Finally,design guidelines are provided for the incorporation of FL and ISCC.Overall,this paper aims to contribute to the understanding of FL in the context of wireless networks,with a focus on the ISCC framework,and provide insights into addressing the challenges and optimizing the design for the integration of FL into future 6G networks.

Create Your Own Data and Energy Integrated Communication Network:A Brief Tutorial and a Prototype System

In order to satisfy the ever-increasing energy appetite of the massive battery-powered and batteryless communication devices,radio frequency(RF)signals have been relied upon for transferring wireless power to them.The joint coordination of wireless power transfer(WPT)and wireless information transfer(WIT)yields simultaneous wireless information and power transfer(SWIPT)as well as data and energy integrated communication network(DEIN).However,as a promising technique,few efforts are invested in the hardware implementation of DEIN.In order to make DEIN a reality,this paper focuses on hardware implementation of a DEIN.It firstly provides a brief tutorial on SWIPT,while summarising the latest hardware design of WPT transceiver and the existing commercial solutions.Then,a prototype design in DEIN with full protocol stack is elaborated,followed by its performance evaluation.

Separate Dimming Controlling and Data Transmission for an Indoor Visible Light Communication System

Simultaneous dimming controlling and data transmission are usually required in a white LED based indoor visible light communication system.However,the diming controlling of LED normally interferes the data transmission due to the modulation nonlinearity of LED.In order to solve this problem,a scheme by separating the LEDs for the functions of dimming control and data transmission respectively is proposed in this paper.In the scheme,the LEDs used for dimming control function are driven by a dc amplified circuit,and the LEDs for data transmission are driven by a digital modulation circuit respectively.In this way,the modulation distortion to the data signal caused by the modulation nonlinearity can be avoided even if the dimming is at high level dc driven current.The proof-of-concept experiment of a 2.5Mbit/s visible light communication system demonstrates that the dimming controlling and data transmission can be realized simultaneously in a simple way,and the data transmission is not affected by the dimming controlling function.Compared to previous methods,the scheme in this paper is simpler and cost effective,and makes sense when high rate data is transmitted in a visible light communication system.

Enabling Efficient Data Transmission in Wireless Sensor Networks-Based IoT Application

The use of the Internet of Things(IoT)is expanding at an unprecedented scale in many critical applications due to the ability to interconnect and utilize a plethora of wide range of devices.In critical infrastructure domains like oil and gas supply,intelligent transportation,power grids,and autonomous agriculture,it is essential to guarantee the confidentiality,integrity,and authenticity of data collected and exchanged.However,the limited resources coupled with the heterogeneity of IoT devices make it inefficient or sometimes infeasible to achieve secure data transmission using traditional cryptographic techniques.Consequently,designing a lightweight secure data transmission scheme is becoming essential.In this article,we propose lightweight secure data transmission(LSDT)scheme for IoT environments.LSDT consists of three phases and utilizes an effective combination of symmetric keys and the Elliptic Curve Menezes-Qu-Vanstone asymmetric key agreement protocol.We design the simulation environment and experiments to evaluate the performance of the LSDT scheme in terms of communication and computation costs.Security and performance analysis indicates that the LSDT scheme is secure,suitable for IoT applications,and performs better in comparison to other related security schemes.

Utilization of Data Communication according to the IEC61850 Standard for Nuclear Power Plant Electrical Equipment Testing

This paper deals with an integration of directly measured electrical parameters with data acquired by data communication from protections and terminals into an advanced monitoring system. Based on the periodic test, the authors of this paper present the possibility of an extended evaluation and more accurate analysis of transient and failure events. For periodical testing, as implemented during the commissioning of power plants in the Czech Republic, a monitoring system of electrical equipment has been used, to record the courses of important electrical parameters and thus, proving the proper functioning of complex technological systems in various operation modes. Data from monitoring system were used to prove the successful results of the test or as a base data for further analysis of failures. The monitoring system has proved itself as a very useful device also when recording unexpected failure events, the cause of which was very quickly and accurately detected by the follow-up analysis. Initially, only the voltage and current data from measuring transformers, analogue transducers and contact relays were used as input data for the monitoring system. After the implementation of new digital protection technology and controlling terminals with inner data recorder, the data from digital devices could be also utilized for the monitoring system.

A Message Transmission Protocol of a Mobile Data Communication Network

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Design of Power Communication Data Network Management System and Implementation of Data Acquisition Module

The power communication network is a separate network from the power grid whose primary purpose is to ensure the power grid's safe operation.This paper expounds the composition of the comprehensive network management architecture of the power communication data network and the implementation of the data acquisition module in the network management system through theoretical analysis,for the reference of relevant personnel,in order to better promote the collection of power grid communication network data.

Scheduling for constantly-evolving data broadcasting in asymmetric communication networks

Recent advances in wireless sensor networks and GPS have made constantly-evolving data a new type of data which bring a new challenge to traditional data processing methods. Data broadcasting is an effective means for data dissemination in asymmetric communication networks, such as wireless networks. In this paper, definition of the mean uncertainty ratio of data is presented and a broadcasting scheme is proposed for constantly-evolving data dissemination. Simulation results show that the scheme can reduce the uncertainty of the broadcasted constantly-evolving data effectively at the cost of minor increase in data access time, in the case of no transmission error, transmission errors present, and multiple broadcast channels. As a result it benefits the qualities of the query results based on the data.