Early warning of core network capacity in space-terrestrial integrated networks

With the rapid development of low-orbit satellite com-munication networks both domestically and internationally,space-terrestrial integrated networks will become the future development trend.For space and terrestrial networks with limi-ted resources,the utilization efficiency of the entire space-terres-trial integrated networks resources can be affected by the core network indirectly.In order to improve the response efficiency of core networks expansion construction,early warning of the core network elements capacity is necessary.Based on the inte-grated architecture of space and terrestrial network,multidimen-sional factors are considered in this paper,including the number of terminals,login users,and the rules of users’migration during holidays.Using artifical intelligence(AI)technologies,the regis-tered users of the access and mobility management function(AMF),authorization users of the unified data management(UDM),protocol data unit(PDU)sessions of session manage-ment function(SMF)are predicted in combination with the num-ber of login users,the number of terminals.Therefore,the core network elements capacity can be predicted in advance.The proposed method is proven to be effective based on the data from real network.

Blockchain Based Secure Relay Scheme for Space-Terrestrial Integrated Networks

The future 6G networks will integrates space and terrestrial networks to realize a fully connected world with extensive collaboration.However,how to build trust between multiple parties is a difficult problem for secure cooperation without a reliable third-party.Blockchain is a promising technology to solve this problem by converting the trust between multi-parties to the trust to the common shared data.Several works have proposed to apply the incentive mechanism in blockchain to encourage effective cooperation,but how to evaluate the cooperation performance and avoid breach of contract is not discussed.In this paper,a secure relay scheme is proposed based on the consortium blockchain system composed by different operators.In particular,smart contract checks the integrity of the message based on RSA accumulator,and executes transactions automatically when the message is delivered successfully.Detailed procedures are introduced for both uplink and downlink relay.Implementation based on Hyperledger Fabric proves the effectiveness of the proposed scheme and shows that the complexity of the scheme is low enough for practical deployment.

An Adaptive Routing Algorithm for Integrated Information Networks

The integrated information network is a large capacity information network that integrates various communication platforms on the ground, at sea, in the air and in the deep air through the inter-satellite and satellite-ground links to acquire information accurately, process it quickly, and transmit it efficiently. The satellite communication, as an important part of integrated information networks, is one of main approaches to acquire, process and distribute communication information and resources. In this paper, based on current researches of the satellite communication network, we put forward a 3-layer satellite communication network model based on the Software Defined Network (SDN). Meanwhile, to improve current routing policies of the Low Earth Orbit (LEO) satellite communication network, we put forward an Adaptive Routing Algorithm (ARA) to sustain the shortest satellite communication link. Experiment results show that the proposed method can effectively reduce link distance and communication delay, and realize adaptive path planning.

A Study on Integrated Wavelet Neural Networks in Fault Diagnosis Based on Information Fusion

The tight wavelet neural network was constituted by taking the nonlinear Morlet wavelet radices as the excitation function. The idiographic algorithm was presented. It combined the advantages of wavelet analysis and neural networks. The integrated wavelet neural network fault diagnosis system was set up based on both the information fusion technology and actual fault diagnosis, which took the sub-wavelet neural network as primary diagnosis from different sides, then came to the conclusions through decision-making fusion. The realizable policy of the diagnosis system and established principle of the sub-wavelet neural networks were given. It can be deduced from the examples that it takes full advantage of diversified characteristic information, and improves the diagnosis rate.

UAV-Aided Data and Energy Integrated Network: System Design and Prototype Development

Terminal devices deployed in outdoor environments are facing a thorny problem of power supply.Data and energy integrated network(DEIN)is a promising technology to solve the problem,which simultaneously transfers data and energy through radio frequency signals.State-of-the-art researches mostly focus on theoretical aspects.By contrast,we provide a complete design and implementation of a fully functioning DEIN system with the support of an unmanned aerial vehicle(UAV).The UAV can be dispatched to areas of interest to remotely recharge batteryless terminals,while collecting essential information from them.Then,the UAV uploads the information to remote base stations.Our system verifies the feasibility of the DEIN in practical applications.

Integration and development of energy and information network in the Pan-Arctic region

The Global Energy Interconnection is an important strategic approach used to achieve efficient worldwide energy allocation.The idea of developing integrated power,information,and transportation networks provides increased power interconnection functionality and meaning,helps condense forces,and accelerates the integration of global infrastructure.Correspondingly,it is envisaged that it will become the trend of industrial technological development in the future.In consideration of the current trend of integrated development,this study evaluates a possible plan of coordinated development of fiber-optic and power networks in the Pan-Arctic region.Firstly,the backbone network architecture of Global Energy Interconnection is introduced and the importance of the Arctic energy backbone network is confirmed.The energy consumption and developmental trend of global data centers are then analyzed.Subsequently,the global network traffic is predicted and analyzed by means of a polynomial regression model.Finally,in combination with the current construction of fiber-optic networks in the Pan-Arctic region,the advantages of the integration of the fiber-optic and power networks in this region are clarified in justification of the decision for the development of a Global Energy Interconnection scheme.

Space-Terrestrial Integrated Architecture for Internet of Things

To realize the ultimate vision of Internet of Things(IoT),only depending on terrestrial network is far from enough.As a supplement and extension of terrestrial network,satellite network can offer powerful support to realize the depth and breadth of the coverage.However,existing satellite networks are usually designed for particular purposes.Moreover,traditional satellite networks and terrestrial networks are developed and operated separately,consequently they cannot meet the need of network flexibility required by IoT.In this paper,a space-terrestrial architecture is conceived for constructing a spaceterrestrial based IoT(ST-IoT) system.Additionally,a reliable identification procedure,an integrated access and communication procedure,as well as a clustering cooperative transmission strategy are also presented.

Three-Dimensional Cooperative Localization via Space-Air-Ground Integrated Networks

The space-air-ground integrated network(SAGIN)combines the superiority of the satellite,aerial,and ground communications,which is envisioned to provide high-precision positioning ability as well as seamless connectivity in the 5G and Beyond 5G(B5G)systems.In this paper,we propose a three-dimensional SAGIN localization scheme for ground agents utilizing multi-source information from satellites,base stations and unmanned aerial vehicles(UAVs).Based on the designed scheme,we derive the positioning performance bound and establish a distributed maximum likelihood algorithm to jointly estimate the positions and clock offsets of ground agents.Simulation results demonstrate the validity of the SAGIN localization scheme and reveal the effects of the number of satellites,the number of base stations,the number of UAVs and clock noise on positioning performance.

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.

Fuzzy Integral Based Information Fusion for Water Quality Monitoring Using Remote Sensing Data

To improve the monitoring precision of lake chlorophyll a (Chl-a), this paper presents a fusion method based on Choquet Fuzzy Integral (CFI) to estimate the Chl-a concentration. A group of BPNN models are designed. The output of multiple BPNN model is fused by the CFI. Meanwhile, to resolve the over-fitting problem caused by a small number of training sets, we design an algorithm that fully considers neighbor sampling information. A classification experiment of the Chl-a concentration of the Taihu Lake is conducted. The result shows that, the proposed approach is superior to the classification using a single neural network classifier, and the CFI fusion method has higher identification accuracy.

基于VMD-Informer-BiLSTM模型的超短期光伏功率预测

由于光伏出力的波动性和随机性给电网的规划和运行带来了挑战,因此提高光伏功率预测的精度对提升新能源系统的稳定性具有重要意义。为此提出了一种结合模态分解、多维特征建模、Informer、双向长短期神经网络(bidirectional long short-term memory network,BiLSTM)的超短期光伏组合预测模型。首先通过变分模态分解将光伏功率序列分解成不同频率的本征模态函数(intrinsic mode function,IMF),降低光伏功率信号的非平稳性与复杂度;随后使用离散小波变换提取天气因素中的细节分量,实现不同分解算法的优势互补,并用随机森林算法为每个IMF筛选冗余特征,然后将特征矩阵送入Informer进行建模,提取不同时间步中关键时刻的信息,提高对长时间序列的预测效率;最后为进一步提高模型预测精度,分析误差序列特性,利用BiLSTM进行误差校正。采用实际光伏数据进行算例分析,结果表明所提方法提高了超短期光伏功率预测精度。

Exploration of Rural Informatization and Urban-rural Information Fusion

Based on the status quo of rural informatization and information service,this article conducts analysis and discussion of problems in rural informatization and urban-rural information fusion,using statistics. And corresponding countermeasures are put forward as follows: building rural information platform; strengthening information literacy training in rural areas and cultivating new farmers; making information network serve production and operation to increase jobs and income for farmers; developing rural e-commerce; enhancing network information security and prevention.

PIR-based data integrity verification method in sensor network

Since a sensor node handles wireless communication in data transmission and reception and is installed in poor environment, it is easily exposed to certain attacks such as data transformation and sniffing. Therefore, it is necessary to verify data integrity to properly respond to an adversary's ill-intentioned data modification. In sensor network environment, the data integrity verification method verifies the final data only, requesting multiple communications. An energy-efficient private information retrieval(PIR)-based data integrity verification method is proposed. Because the proposed method verifies the integrity of data between parent and child nodes, it is more efficient than the existing method which verifies data integrity after receiving data from the entire network or in a cluster. Since the number of messages for verification is reduced, in addition, energy could be used more efficiently. Lastly, the excellence of the proposed method is verified through performance evaluation.

On the Phenomenon of Information Silo in the E- government Construction in China

In the past decade,the e-government affairs keep developing,which prom otes the reform of governmental affairs and the enhancement of administrative efficiency.However,the phenomenon of inform ation silo has bad influence upon the governm ental information resources sharing and the efficiency of the e-government affairs,hindering inform ation connectivity,so that the government management cannot meet the need of society,nor can the e-governm ent develop in the long run.This paper attempts to analyze the embodiment and causes of the phenomenon of information silo,putting forward measures of solving the problem of inform ation silo.

空天信息网络中通导融合技术综述

空天信息网络是推动社会经济发展和保障国家安全的重要基础设施。空天信息网络将陆基网络、卫星网络及航空网络构成一体化网络架构,深度耦合通信、导航、遥感等功能,实现信息的高效传输和高精度位置服务。文章分析卫星网络、移动通信网络、局域通信网等多种无线网络通信导航融合定位技术的发展现状,并阐述其面临的挑战,提出多网融合方法可以提升室内外广域无缝高精度位置服务的可靠性。利用5G移动通信网络,与北斗/GNSS卫星导航系统结合,实现相互增强。最后,从天地一体定位导航与授时体系和仿生通信定位导航两方面探讨空天信息网络中通信导航融合定位技术的未来发展趋势。

Learning-Based Joint Resource Slicing and Scheduling in Space-Terrestrial Integrated Vehicular Networks

In this paper,we investigate the resource slicing and scheduling problem in the space-terrestrial integrated vehicular networks to support both delay-sensitive services(DSSs)and delay-tolerant services(DTSs).Resource slicing and scheduling are to allocate spectrum resources to different slices and determine user association and bandwidth allocation for individual vehicles.To accommodate the dynamic network conditions,we first formulate a joint resource slicing and scheduling(JRSS)problem to minimize the long-term system cost,including the DSS requirement violation cost,DTS delay cost,and slice reconfiguration cost.Since resource slicing and scheduling decisions are interdependent with different timescales,we decompose the JRSS problem into a large-timescale resource slicing subproblem and a small-timescale resource scheduling subproblem.We propose a two-layered reinforcement learning(RL)-based JRSS scheme to find the solutions to the subproblems.In the resource slicing layer,spectrum resources are pre-allocated to different slices via a proximal policy optimization-based RL algorithm.In the resource scheduling layer,spectrum resources in each slice are scheduled to individual vehicles based on dynamic network conditions and service requirements via matching-based algorithms.We conduct extensive trace-driven experiments to demonstrate that the proposed scheme can effectively reduce the system cost while satisfying service quality requirements.

Space-Terrestrial Integrated Mobility Management via Named Data Networking

In Future Space-Terrestrial Integrated Networks （FSTINs）, mobility is the norm rather than the exception, the current TCP/IP architecture is not competent. As a promising future network architecture, Named Data Networking （NDN） can support content consumer mobility naturally, but the content producer mobility support remains a challenging problem. Most previous research simply considered this problem in terrestrial scenarios, which involve stable infrastructures to achieve node mobility management. In this paper, we consider the problem in an FSTIN scenario without special handover management infrastructures. Specifically, we propose a tracing-based producer mobility management scheme and an addressing-assisted forwarding method via NDN architecture. We formally describe Multi-Layered Satellite Networks via a Time Varying Graph model and define the foremost path calculating problem to calculate the route of space segment, as well as an algorithm that can function in both dense （connected） and sparse （delay/disruption tolerant） scenarios. Finally, we discuss the acceleration method that can improve the Space-Terrestrial Integrated forwarding efficiency. Performance evaluation demonstrates that the proposed scheme can support fast handover and efficient forwarding in the FSTIN scenario.

基于神经网络信息融合的油气藏信息存储系统设计

针对现行油气藏信息存储系统鲁棒性、安全性较低的问题,提出了基于神经网络信息融合的油气藏信息存储系统设计方案。在系统硬件方面,通过对信息存储器选型与设计,完成系统硬件设计;在系统软件方面,利用神经网络信息融合技术对油气藏信息分类,并设计数据库对分类的油气藏信息存储。实验结果表明,在信息存储过载情况下系统崩溃率未超过2%,系统安全性系数在0.8以上,具有较强的鲁棒性与安全性。

基于区块链分级存储与国产商用密码技术的高校图书馆信息系统网络安全保障

为了提升图书馆信息系统网络安全保障能力,确保图书馆信息系统安全稳定运行,对数字图书馆信息系统面临的身份假冒、数据泄露、数据篡改、数据破坏、重要操作难以溯源等突出网络安全问题进行研究,提出了解决思路和方法,包括基于区块链分级存储实现图书馆信息系统数据存储安全,基于国产商用密码技术实现图书馆信息系统身份认证、数据加密保护、数据完整性保护、操作真实性和抗抵赖保护,对建设完善有效的图书馆信息系统网络安全整体保障体系、提升图书馆信息系统网络安全保障能力具有指导意义。

空间信息网络时变图建模方法

空间信息网络是星地融合网络中一个重要组成部分,其拓扑具有时变性和可预测性。采用一个合适的时变图模型来表征时变的空间信息网络,对于空间信息网络性能分析至关重要。首先阐述了空间信息网络的特性,然后介绍了多种空间信息网络时变图模型的建模方法,包括快照序列图、时间扩展图、存储时间聚合图和多功能时间扩展图,并且分析了它们的特征和优缺点,为6G星地融合网络的研究奠定基础,为网络性能分析提供了理论支撑。