From Earth to Space:A First Deployment of 5G Core Network on Satellite

Recent developments in the aerospace industry have led to a dramatic reduction in the manufacturing and launch costs of low Earth orbit satellites.The new trend enables the paradigm shift of satelliteterrestrial integrated networks with global coverage.In particular,the integration of 5G communication systems and satellites has the potential to restructure nextgeneration mobile networks.By leveraging the network function virtualization and network slicing,the satellite 5G core networks will facilitate the coordination and management of network functions in satellite-terrestrial integrated networks.We are the first to deploy a 5G core network on a real-world satellite to investigate its feasibility.We conducted experiments to validate the satellite 5G core network functions.The validated procedures include registration and session setup procedures.The results show that the satellite 5G core network can function normally and generate correct signaling.

ML-SLD:A message-level stateless design for cloud-native 5G core network

The Internet of Things(IoTs)has become an essential component of the 5th Generation(5G)network and beyond,accelerating the transition to digital society.The increasing signaling traffic generated by billions of IoT devices has placed significant strain on the 5G Core network(5GC)control plane.To address this issue,the 3rd Gener-ation Partnership Project(3GPP)first proposed a Service-Based Architecture(SBA),intending to create a flexible,scalable,and agile cloud-native 5GC.However,considering the coupling of protocol states and functions,there are still many challenges to fully utilize the benefits of the cloud computing and orchestrate the 5GC in a cloud-native manner.We propose a Message-Level StateLess Design(ML-SLD)to provide a cloud-native 5GC from an architectural standpoint in this paper.Firstly,we propose an innovative mechanism for servitization of the N2 interface to maintain the connection between Radio Access Network(RAN)and the 5GC,avoiding interruptions and dropouts of large-scale user data.Furthermore,we propose an On-demand Message Forwarding(OMF)al-gorithm to reduce the impact of cloud fluctuations on the performance of cloud-native 5GC.Finally,we create a prototype that is based on the OpenAirInterface(OAI)5G core network projects,with all Network Functions(NFs)packaged in dockers and deployed in a kubernetes-based cloud environment.Several experiments have been built with UERANSIM and Chaosblade simulation tools.The findings demonstrate the viability and efficiency of our proposed methods.

Research on Construction Scheme of Cloud Platform for Core Network Equipment of Railway 5G Private Network

This paper studies and analyzes the rigorous requirements of railway 5G private network core network(5GC)equipment based on network function virtualization(NFV)technology in terms of reliability,security,latency and other aspects of communication cloud,compares cloud platform schemes with different decoupling modes,and proposes that railway 5GC should be implemented by software and hardware integration scheme or software and hardware two-layer decoupling scheme.At the same time,the redundancy and disaster recovery schemes and measures that can be taken by 5GC based on cloud platform are proposed.Finally,taking the products of ZTE Corporation as an example,the implementation architecture of railway 5GC cloud platform in 1+1 redundancy mode is given.It serves as a reference for the engineering construction of 5G-R core network.

BC-AKA:Blockchain Based Asymmetric Authentication and Key Agreement Protocol for Distributed 5G Core Network

Secure authentication between user equipment and 5G core network is a critical issue for 5G system.However,the traditional authentication protocol 5 G-AKA and the centralized key database are at risk of several security problems,e.g.key leakage,impersonation attack,MitM attack and single point of failure.In this paper,a blockchain based asymmetric authentication and key agreement protocol(BC-AKA)is proposed for distributed 5G core network.In particular,the key used in the authentication process is replaced from a symmetric key to an asymmetric key,and the database used to store keys in conventional 5G core network is replaced with a blockchain network.A proof of concept system for distributed 5G core network is built based on Ethereum and ECC-Secp256 k1,and the efficiency and effectiveness of the proposed scheme are verified by the experiment results.

Resurrection of GSM Core Network at WCDMA Age

The developing mobile technologies have resulted in operators focusing on how to optimize their 2G networks and ensure a smooth network end, there are two approaches for upgrade: one core network with a 2G-radio network, while the other is (Mobile Switching Center) with WCDMA MSCS (Mobile Gateway) to optimize the Core network

Design of CERNET2-One of the Core Networks in CNGI

This article presents the network design schemes of CERNET2 including overall architecture, the backbone, core nodes, access solutions and the CNGI peer centers. CERNET2 connects 25 core nodes distributed in 20 cities of China at the speed of 2.5-10 Gb/s. CERNET2 has four unique features. First, its backbone adopts native IPv6 protocols, rather than IPv4/IPv6 dual stack. It is the largest pure IPv6 network in the world. Second, it provides an environment for testing and trial operation of China-made IPv6 core routers. It also allows tests of interconnection, interworking and interoperation among multiple vendors. Third, the large IPv6 address space enables the study on network addresses in a real network environment, which ensures the construction of a secured and trusted CNGI. Last, it is a test-bed for NGI applications.

An SDN/NFV Based Framework for Management and Deployment of Service Based 5G Core Network

The traffic explosion and the rising of diverse requirements lead to many challenges for traditional mobile network architecture on flexibility, scalability, and deployability. To meet new requirements in the 5 G era, service based architecture is introduced into mobile networks. The monolithic network elements(e.g., MME, PGW, etc.) are split into smaller network functions to provide customized services. However, the management and deployment of network functions in service based 5 G core network are still big challenges. In this paper, we propose a novel management architecture for 5 G service based core network based on NFV and SDN. Combined with SDN, NFV and edge computing, the proposed framework can provide distributed and on-demand deployment of network functions, service guaranteed network slicing, flexible orchestration of network functions and optimal workload allocation. Simulations are conducted to show that the proposed framework and algorithm are effective in terms of reducing network operating cost.

The Evolution Trend of Optical Core Network

Optical network is the infrastructure of telecommunicationnetwork. More than 95% of information istransported over optical network in China, wherecore network is the main trunk. How to increase thebit rate of the single wavelength channel, raise thetotal capacity of the DWDM system, extend theoptical transportation distance of electrical repeaterfree of the DWDM system and optical network intelligenceare key problems demanding high attention.The evolution trend of the optical core network isdescribed with some examples in this paper.

Variation-Aware Task Mapping on Homogeneous Fault-Tolerant Multi-Core Network-on-Chips

A variation-aware task mapping approach is proposed for a multi-core network-on-chips with redundant cores, which includes both the design-time mapping and run-time scheduling algorithms. Firstly, a design-time genetic task mapping algorithm is proposed during the design stage to generate multiple task mapping solutions which cover a maximum range of chips. Then, during the run, one optimal task mapping solution is selected. Additionally, logical cores are mapped to physically available cores. Both core asymmetry and topological changes are considered in the proposed approach. Experimental results show that the performance yield of the proposed approach is 96% on average, and the communication cost, power consumption and peak temperature are all optimized without loss of performance yield.

Joint system consumption minimization and workload allocation in edge-core network

The explosive increase of smart devices and mobile traffic results in heavy burden on backhaul and core network,intolerable network latency and degraded service to the end-users. As a complement to core network,edge network contributes to relieving network burden and improving user experience. To investigate the problem of optimizing the total consumption in an edge-core network, the system consumption minimization problem is fromulated,considering the energy consumption and delay. Given that the formulated problem is a mixed nonlinear integer programming( MNIP),a low-complexity workload allocation algorithm is proposed based on interior-point method.The proposed algorithm has an extremely short running time in practice. Finally,simulation results show that edge network can significantly complement core network with much reduced backhaul energy consumption and delay.

Core-based Shared Tree Multicast Routing Algorithms for LEO Satellite IP Networks

一个新基于核心的分享的树算法， viz 核心簇基于联合的分享的树(CCST ) 算法和加权的版本(即 w-CCST 算法) 被建议以便解决隧道资源浪费问题在典型基于来源多点传送在低地球轨道(狮子座) 的路由算法卫星 IP 网络。CCST 算法包括动态近似中心(数模转换器) 核心选择方法和核心簇联合多点传送线路构造计划。没有复杂机载的计算， DAC 方法特别地为期刊和常规运动的高度有活力的网络被开发。核心簇联合方法作为起始的核心簇拿核心节点，并且扩展它对在最低的树的一棵全部 multicast 树由在最新产生的核心簇和剩余之间的一个最短的路径计划花费了的构造逐步组织成员，它导致大带宽利用。而且， w-CCST 算法能由调整加权的因素满足一些的严格的端对端的延期要求寻求在树费用和端对端的繁殖延期的性能之间的平衡即时多点传送在损坏树的细微增加的情况下的服务花费了。最后，性能比较在狮子座卫星 IP 网络在建议算法和典型算法之间被进行。模拟结果证明 CCST 算法显著地减少平均的树费用对到其它，并且也， w-CCST 算法的平均端对端的繁殖延期比 CCST 算法的低。

Combined Transmission Interference Spectrum of No Core Fiber and BP Neural Network for Concentration Sensing Research

To investigate wavelength response of the no core fiber(NCF)interference spectrum to concentration,a three-layer back propagation(BP)neural network model was established to optimize the concentration sensing data.In this method,the measured wavelength and the corresponding concentration were trained by a BP neural network,so that the accuracy of the measurement system was optimized.The wavelength was used as the training set and got into the input layer of the three layer BP network model which is used as the input value of the network,and the corresponding actual concentration value was used as the output value of the network,and the optimal network structure was trained.This paper discovers a preferable correlation between the predicted value and the actual value,where the former is approximately equal to the latter.The correlation coefficients of the measured and predicted values for a sucrose concentration were 1.000 89 and 1.003 94;similarly,correlations of0.999 51 and 1.018 8 for a glucose concentration were observed.The results demonstrate that the BP neural network can improve the prediction accuracy of the nonlinear relationship between the interference spectral data and the concentration in NCF sensing systems.

Mass concrete strength assessment method by Sonreb and Core combined method using artificial neural network

The Sonreb and Core (SRC) combined method is proposed to assess the concrete compression strength of mass concrete structures.Artificial neural network is employed together with the SRC combined method to obtain the optimal core number.The artificial neural network is trained based on data from different testing methods.The procedure of using artificial neural network to assess the concrete strength is described.It proves that the SRC combined method is superior in many aspects and artificial the presented neural network has a high efficiency and reliability.The combined method using artificial intelligence is promising in the strength assessment of mass concrete structures such as the dam,the anchor of the suspension bridge,etc.

Multi-Core Virtual Concatenation Scheme Considering Inter-Core Crosstalk in Spatial Division Multiplexing Enabled Elastic Optical Networks

Spatial division multiplexing enabled elastic optical networks(SDM-EONs) are the potential implementation form of future optical transport networks, because it can curve the physical limitation of achievable transmission capacity in single-mode fiber and single-core fiber. However, spectrum fragmentation issue becomes more serious in SDM-EONs compared with simple elastic optical networks(EONs) with single mode fiber or single core fiber. In this paper, multicore virtual concatenation(MCVC) scheme is first proposed considering inter-core crosstalk to solve the spectrum fragmentation issue in SDM-EONs. Simulation results show that the proposed MCVC scheme can achieve better performance compared with the baseline scheme, i.e., single-core virtual concatenation(SCVC) scheme, in terms of blocking probability and spectrum utilization.

Predicting the composition of flux-cored wire claded metal by a neural network

In this paper, an artificial neural network method that can predict the chemical composition of deposited weld metal by CO 2 Shielded Flux Cored Wire Surfacing was studied. It is found that artificial neural network is a good approach on studying welding metallurgy processes that cannot be described by conventional mathematical methods. In the same time we explored a new way to study the no equilibrium welding metallurgy processes.

Using Neural Networks for Simulating and Predicting Core-End Temperatures in Electrical Generators: Power Uprate Application

Power uprates pose a threat to electrical generators due to possible parasite effects that can develop potential failure sources with catastrophic consequences in most cases. In that sense, it is important to pay close attention to overheating, which results from excessive system losses and cooling system inefficiency. The end region of a stator is the most sensitive part to overheating. The calculation of magnetic fields, the evaluation of eddy-current losses and the determination of loss-derived temperature increases, are challenging problems requiring the use of simulation methods. The most usual methodology is the finite element method, or linear regression. In order to address this methodology, a calculation method was developed to determine temperature increases in the last stator package. The mathematical model developed was based on an artificial intelligence technique, more specifically neural networks. The model was successfully applied to estimate temperatures associated to 108% power and used to extrapolate temperature values for a power uprate to 113.48%. This last scenario was also useful to test extrapolation accuracy. The method is applied to determine core-end temperature when power is uprated to 117.78%. At that point, the temperature value will be compared to with the values obtained using finite elements method and multivariate regression.

基于Valued ERGMs模型的核心技术网络成长机制研究——以量子计算领域为例

对核心技术网络及其成长机制的研究有助于梳理核心技术之间的依赖和促进关系,为研究核心技术演化提供新的理论视角和方法。以技术演化相关理论为基础,归纳核心技术网络成长的影响因素,基于量子计算领域专利数据,识别以技术概念和技术关系为基础的量子计算领域核心技术网络,并基于Valued ERGMs模型构建核心技术网络成长机制模型。结果表明,技术要素中心性、专利技术研发能力、与TRIZ进化法则匹配程度以及技术要素同配性对核心技术网络成长具有正向促进作用;在技术路径方面,核心技术网络成长受到技术要素路径依赖性和技术突破的双重影响。最后,根据量子计算领域核心技术网络成长机制的实证研究结果,从技术研发层面、企业层面、政府层面为相关领域技术发展提出策略建议。

中国潜在自主可控关键产品识别与突破路径研究

系统分析中国潜在自主可控关键产品突破时序路径,是逆全球化背景下全面防范和化解“卡脖子”潜在风险的关键。基于1995—2021年243个国家(地区)出口产品数据构建产品空间网络模型,识别全球核心产品及中国潜在自主可控关键产品,基于产品能力和网络核心性构建优先度指数,挖掘潜在自主可控关键产品突破路径。研究表明,在2021年核心度前10%的124种全球核心产品中,共有54种中国潜在自主可控关键产品,其突破路径为:充分利用机械与电力设备、基本金属制品、化工产品等领域已有的产品能力基础,优先突破光学显影和金属工艺等领域的基础关键产品,再进一步突破机械与电力设备、光学与医疗等精密仪器、塑料与橡胶制品业等领域高端关键产品。

深度学习在多核缓存预取中的应用研究综述

当前人工智能技术应用于系统结构领域的研究前景广阔,特别是将深度学习应用于多核架构的数据预取研究已经成为国内外的研究热点。针对基于深度学习的缓存预取任务进行了研究,形式化地定义了深度学习缓存预取模型。在介绍当前常见的多核缓存架构和预取技术的基础上,全面分析了现有基于深度学习的典型缓存预取器的设计思路。深度学习神经网络在多核缓存预取领域的应用主要采用了深度神经网络、循环神经网络、长短期记忆网络和注意力机制等机器学习方法,综合对比分析现有基于深度学习的数据预取神经网络模型后发现,基于深度学习的多核缓存预取技术在计算成本、模型优化和实用性等方面还存在着局限性,未来在自适应预取模型以及神经网络预取模型的实用性方面还有很大的研究探索空间和发展前景。