A Probabilistic Trust Model and Control Algorithm to Protect 6G Networks against Malicious Data Injection Attacks in Edge Computing Environments

Future 6G communications are envisioned to enable a large catalogue of pioneering applications.These will range from networked Cyber-Physical Systems to edge computing devices,establishing real-time feedback control loops critical for managing Industry 5.0 deployments,digital agriculture systems,and essential infrastructures.The provision of extensive machine-type communications through 6G will render many of these innovative systems autonomous and unsupervised.While full automation will enhance industrial efficiency significantly,it concurrently introduces new cyber risks and vulnerabilities.In particular,unattended systems are highly susceptible to trust issues:malicious nodes and false information can be easily introduced into control loops.Additionally,Denialof-Service attacks can be executed by inundating the network with valueless noise.Current anomaly detection schemes require the entire transformation of the control software to integrate new steps and can only mitigate anomalies that conform to predefined mathematical models.Solutions based on an exhaustive data collection to detect anomalies are precise but extremely slow.Standard models,with their limited understanding of mobile networks,can achieve precision rates no higher than 75%.Therefore,more general and transversal protection mechanisms are needed to detect malicious behaviors transparently.This paper introduces a probabilistic trust model and control algorithm designed to address this gap.The model determines the probability of any node to be trustworthy.Communication channels are pruned for those nodes whose probability is below a given threshold.The trust control algorithmcomprises three primary phases,which feed themodel with three different probabilities,which are weighted and combined.Initially,anomalous nodes are identified using Gaussian mixture models and clustering technologies.Next,traffic patterns are studied using digital Bessel functions and the functional scalar product.Finally,the information coherence and content are analyzed.The noise content and abnormal information sequences are detected using a Volterra filter and a bank of Finite Impulse Response filters.An experimental validation based on simulation tools and environments was carried out.Results show the proposed solution can successfully detect up to 92%of malicious data injection attacks.

Statistical Channel Modeling for Indoor VLC Communications Based on Channel Measurements

Visible light communication(VLC)has attracted much attention in the research of sixthgeneration(6G)systems.Furthermore,channel modeling is the foundation for designing efficient and robust VLC systems.In this paper,we present extensive VLC channel measurement campaigns in indoor environments,i.e.,an office and a corridor.Based on the measured data,the large-scale fading characteristics and multipath-related characteristics,including omnidirectional optical path loss(OPL),K-factor,power angular spectrum(PAS),angle spread(AS),and clustering characteristics,are analyzed and modeled through a statistical method.Based on the extracted statistics of the above-mentioned channel characteristics,we propose a statistical spatial channel model(SSCM)capable of modeling multipath in the spatial domain.Furthermore,the simulated statistics of the proposed model are compared with the measured statistics.For instance,in the office,the simulated path loss exponent(PLE)and the measured PLE are 1.96and 1.97,respectively.And,the simulated medians of AS and measured medians of AS are 25.94°and 24.84°,respectively.Generally,the fact that the simulated results fit well with measured results has demonstrated the accuracy of our SSCM.

Energy-optimal DNN model placement in UAV-enabled edge computing networks

Unmanned aerial vehicle(UAV)-enabled edge computing is emerging as a potential enabler for Artificial Intelligence of Things(AIoT)in the forthcoming sixth-generation(6G)communication networks.With the use of flexible UAVs,massive sensing data is gathered and processed promptly without considering geographical locations.Deep neural networks(DNNs)are becoming a driving force to extract valuable information from sensing data.However,the lightweight servers installed on UAVs are not able to meet the extremely high requirements of inference tasks due to the limited battery capacities of UAVs.In this work,we investigate a DNN model placement problem for AIoT applications,where the trained DNN models are selected and placed on UAVs to execute inference tasks locally.It is impractical to obtain future DNN model request profiles and system operation states in UAV-enabled edge computing.The Lyapunov optimization technique is leveraged for the proposed DNN model placement problem.Based on the observed system overview,an advanced online placement(AOP)algorithm is developed to solve the transformed problem in each time slot,which can reduce DNN model transmission delay and disk I/O energy cost simultaneously while keeping the input data queues stable.Finally,extensive simulations are provided to depict the effectiveness of the AOP algorithm.The numerical results demonstrate that the AOP algorithm can reduce 18.14%of the model placement cost and 29.89%of the input data queue backlog on average by comparing it with benchmark algorithms.

Modelling seedling development using thermal effectiveness and photosynthetically active radiation

Seedling quality is a prerequisite for successful field performance and therefore influences crop yields. Temperature and illumination are two major factors affecting seedling quality during nursery propagation. Suboptimal temperature or light of nurseries generally result in leggy or weak seedlings and great economic loss. However, production of healthy seedlings is challenging due to the lack of knowledge in systemic management of nursery environments. In this study, we have established simulation models to predict how temperature and illumination coordinately influence the growth of tomato and cabbage seedlings. Specifically, correlation between seedling quality characteristics(root-shoot ratio, G value(growth function: defined as ratio of whole plant dry weight to days of seedling), healthy indexes) and TEP(thermal effectiveness and photosynthetically active radiation) were explored to establish the models, which were validated with independent test data. Our results suggested that the curve of healthy index 1(HI1) and TEP fitted well with high coefficient of determination(R2) in both species, indicating that the model is highly reliable. The HI1 simulation models for tomato and cabbage are HI1=0.0009e0.0308TEP-0.0015 and HI1= 0.0003e0.0671TEP-0.0003, respectively, which can be used for predicting vigors of tomato and cabbage seedlings grown under different temperature and light conditions.

乡村教育服务数字化转型的G-4C协同模式及应用

面向教育强国建设的需要,乡村教育服务数字化转型正成为乡村教育振兴和促进城乡教育一体化的重要命题。然而,多元服务供给主体间协同困难、服务供需总量与结构失衡、服务供给方式待优化、服务监督与治理体系不健全等阻碍了乡村教育服务数字化转型目标的实现。对此,文章以协同学和“服务金三角”模型为理论支持,梳理了乡村教育服务数字化转型的方向,提出了数字环境中乡村教育服务G-4C协同模式:有序联动的多元服务供给主体,群体和个体特色鲜明的多样化需求,连接数据、服务和资源的教育服务数字底座,以及需求导向的教育服务供给方式。利用G-4C协同模式的实践框架,“专递课堂促进乡村小规模学校教师和学生发展”“高职院校助力乡村多样人群学厨脱贫”两个典型案例的多元协同实施乡村教育服务的过程、方法与策略得以剖析,为我国尚属空白的乡村教育服务数字化转型研究与实践提供借鉴与参考。

The Interdisciplinary Research of Big Data and Wireless Channel: A Cluster-Nuclei Based Channel Model

Recently,internet stimulates the explosive progress of knowledge discovery in big volume data resource,to dig the valuable and hidden rules by computing.Simultaneously,the wireless channel measurement data reveals big volume feature,considering the massive antennas,huge bandwidth and versatile application scenarios.This article firstly presents a comprehensive survey of channel measurement and modeling research for mobile communication,especially for 5th Generation(5G) and beyond.Considering the big data research progress,then a cluster-nuclei based model is proposed,which takes advantages of both the stochastical model and deterministic model.The novel model has low complexity with the limited number of cluster-nuclei while the cluster-nuclei has the physical mapping to real propagation objects.Combining the channel properties variation principles with antenna size,frequency,mobility and scenario dug from the channel data,the proposed model can be expanded in versatile application to support future mobile research.

Towards 6G: Paradigm of Realistic Terahertz Channel Modeling

Terahertz(THz)communications are envisioned as a key technology for the sixth-generation wireless communication system(6G).However,it is not practical to perform large-scale channel measurements with high degrees of freedom at THz frequency band.This makes empirical or stochastic modeling approaches relying on measurements no longer stand.In order to break through the bottleneck of scarce fulldimensional channel sounding measurements,this paper presents a novel paradigm for THz channel modeling towards 6G.With the core of high-performance ray tracing(RT),the presented paradigm requires merely quite limited channel sounding to calibrate the geometry and material electromagnetic(EM)properties of the three-dimensional(3D)environment model in the target scenarios.Then,through extensive RT simulations,the parameters extracted from RT simulations can be fed into either ray-based novel stochastic channel models or cluster-based standard channel model families.Verified by RT simulations,these models can generate realistic channels that are valuable for the design and evaluation of THz systems.Representing two ends of 6G THz use cases from microscopy to macroscopy,case studies are made for close-proximity communications,wireless connections on a desktop,and smart rail mobility,respectively.Last but not least,new concerns on channel modeling resulting from distinguishing features of THz wave are discussed regarding propagation,antenna array,and device aspects,respectively.

FUNCTIONAL ANALYSIS METHOD FOR THE M/G/1 QUEUEING MODEL WITH OPTIONAL SECOND SERVICE

By studying the spectral properties of the underlying operator corresponding to the M/G/1 queueing model with optional second service we obtain that the time-dependent solution of the model strongly converges to its steady-state solution. We also show that the time-dependent queueing size at the departure point converges to the corresponding steady-state queueing size at the departure point.

Neural Network and GBSM Based Time-Varying and Stochastic Channel Modeling for 5G Millimeter Wave Communications

In this work,a frame work for time-varying channel modeling and simulation is proposed by using neural network(NN)to overcome the shortcomings in geometry based stochastic model(GBSM)and simulation approach.Two NN models are developed for modeling of path loss together with shadow fading(SF)and joint small scale channel parameters.The NN models can predict path loss plus SF and small scale channel parameters accurately compared with measurement at 26 GHz performed in an outdoor microcell.The time-varying path loss and small scale channel parameters generated by the NN models are proposed to replace the empirical path loss and channel parameter random numbers in GBSM-based framework to playback the measured channel and match with its environment.Moreover,the sparse feature of clusters,delay and angular spread,channel capacity are investigated by a virtual array measurement at 28 GHz in a large waiting hall.

Implementation Framework and Validation of Cluster-Nuclei Based Channel Model Using Environmental Mapping for 6G Communication Systems

With the research of the upcoming sixth generation(6 G) systems, new technologies will require wider bandwidth, larger scale antenna arrays and more diverse wireless communication scenarios on the future channel modeling. Considering channel model is prerequisite for system design and performance evaluation of 6 G technologies, we face a challenging task: how to accurately and efficiently model 6 G channel for various scenarios? This paper tries to answer it. Firstly, the features of cluster-nuclei(CN) and principle of cluster-nuclei based channel model(CNCM) are introduced. Then, a novel modeling framework is proposed to implement CNCM,which consists four steps: propagation environment reconstruction, cluster-nuclei identification, multipath parameters generation, and channel coefficients generation. Three-dimensional environment with material information is utilized to map CN with scatterers in the propagation pathway. CN are identified by geometrical and electric field calculation based on environmental mapping, and multipath components within CN are calculated by statistical characteristics of angle, power and delay domains. Finally, we present a three-level verification structure to investigate the accuracy and complexity of channel modeling comprehensively. Simulation results reveal that CNCM can perform higher accuracy than geometrybased stochastic model while lower complexity compared with ray-tracing model for practical propagation environment.

U-G-S模式下现代大学附属学校建设的路径思考

U-G-S(大学-政府-学校)三方联动是上海师范大学近年来建设现代大学附属学校的主要模式,上海师范大学、各区政府与中小学校高效协同合作,发挥各方优势,主动服务上海市政府建设“五个新城”的城市战略,办老百姓家门口的好学校。大学附属学校分为挂牌学校和新建学校两种类型,研究从内在机制、实践路径和建设成效三个方面对两类学校的变革发展进行深度剖析,以期为大学附属学校建设提供宝贵经验。

MIMO-Terahertz in 6G Nano-Communications:Channel Modeling and Analysis

With the development of wireless mobile communication technology,the demand for wireless communication rate and frequency increases year by year.Existing wireless mobile communication frequency tends to be saturated,which demands for new solutions.Terahertz(THz)communication has great potential for the future mobile communications(Beyond 5G),and is also an important technique for the high data rate transmission in spatial information network.THz communication has great application prospects in military-civilian integration and coordinated development.In China,important breakthroughs have been achieved for the key techniques of THz high data rate communications,which is practically keeping up with the most advanced technological level in the world.Therefore,further intensifying efforts on the development of THz communication have the strategic importance for China in leading the development of future wireless communication techniques and the standardization process of Beyond 5G.This paper analyzes the performance of the MIMO channel in the Terahertz(THz)band and a discrete mathematical method is used to propose a novel channel model.Then,a channel capacity model is proposed by the combination of path loss and molecular absorption in the THz band based on the CSI at the receiver.Simulation results show that the integration of MIMO in the THz band gives better data rate and channel capacity as compared with a single channel.

Research on Consumption Structure of Rural Residents in Gansu Province Based on ELES Model

By using cross-section data on consumption structure of rural residents in Gansu Province in 2007 and 2008,this paper adopts ELES model to conduct empirical analysis on consumption structure of rural residents in Gansu Province.It indicates that in the current consumption structure of rural residents in Gansu Province,food expenditure is still at the most important and basic level;the overall consumption level of rural residents in Gansu Province is not high;at present,the consumption of rural residents in Gansu Province still hinges in a large measure on income,vulnerable to the price fluctuation.Consequently,increasing farmers' income and stabilizing the level of commodity price,turns out to be a foundation as well as an important approach to improve consumption structure of rural residents in Gansu Province.

Comprehensive evaluation of 5G+smart distribution network based on combined weighting method-cloud model

With the large-scale application of 5G technology in smart distribution networks,the operation effects of distribution networks are not clear.Herein,we propose a comprehensive evaluation model of a 5G+smart distribution network based on the combination weighting and cloud model of the improved Fuzzy Analytic Hierarchy-Entropy Weight Method(FAHP-EWM).First,we establish comprehensive evaluation indexes of a 5G+smart distribution network from five dimensions:reliable operation,economic operation,efficient interaction,technological intelligence,and green emission reduction.Second,by introducing the principle of variance minimization,we propose a combined weighting method based on the improved FAHP-EWM to calculate the comprehensive weight,so as to reduce the defects of subjective arbitrariness and promote objectivity.Finally,a comprehensive evaluation model of 5G+smart distribution network based on cloud model is proposed by considering the uncertainty of distribution network node information and equipment status information.The example analysis indicates that the overall operation of the 5G+smart distribution network project is decent,and the weight value calculated by the combined weighting method is more reasonable and accurate than that calculated by the single weighting method,which verifies the effectiveness and rationality of the proposed evaluation method.Moreover,the proposed evaluation method has a certain guiding role for the large-scale application of 5G communication technology in smart distribution networks.

用DUG三模型计算满射的个数和等价关系的个数

本文利用DUG三模型给出了有限集之间满射个数和有限集上等价关系个数的简洁计算公式.给出了更一般球盒分配问题的DUG三模型计算公式.

THz Channel Modeling: Consolidating the Road to THz Communications

For the sake of meeting the demand of data rates at terabit(Tbit)per second scale in future networks,the terahertz(THz)band is widely accepted as one of the potential key enabling technologies for next generation wireless communication systems.With the progressive development of THz devices,regrading THz communications at system level is increasing crucial and captured the interest of plenty of researchers.Within this scope,THz channel modeling serves as an indispensable and fundamental element.By surveying the latest literature findings,this paper reviews the problem of channel modeling in the THz band,with an emphasis on molecular absorption loss,misalignment fading and multipath fading,which are major influence factors in the THz channel modeling.Then,we focus on simulators and experiments in the THz band,after which we give a brief introduction on applications of THz channel models with respects to capacity,security,and sensing as examples.Finally,we discuss some key issues in the future THz channel modeling.

Calorimetric Studies on Enthalpy Relaxation in Maltitol Glass Transition Based on Phenomenological Models

To investigate the enthalpy relaxation behavior of maltitol glass system,differential scanning calorimetry（DSC） was used to obtain the specific heat capacity[C p（T）] near the glass transition temperature（T g） at different cooling rates ranged between 1 and 20 K/min.Three phenomenological models of enthalpy relaxation,ToolNarayanaswamy-Moynihan（TNM） model,Adam-Gibbs-Vogel（AGV） model and Gómez Ribelles（GR） model,were used to simulate the experimental data.The models＇ parameters were obtained via a curve-fitting method.The results indicate that TNM and AGV models gave the almost identical prediction powers and can reproduce the curves of experimental C p（T） very well.However,the prediction power of GR model evolved from configurational entropy approach is not so good as those of TNM and AGV models.In particular,the metastable limit state parameter（δ） introduced by Gómez Ribelles has insignificant effect on the enthalpy relaxation of the small molecular hydrogen-bonding glass system.

A GIS-based Modeling Approach for Fast Assessment of Soil Erosion by Water at Regional Scale, Loess Plateau of China

The objective of this study is to develop a unique modeling approach for fast assessment of massive soil erosion by water at a regional scale in the Loess Plateau, China. This approach relies on an understanding of both regional patterns of soil loss and its impact factors in the plateau area. Based on the regional characteristics of precipitation, vegetation and land form, and with the use of Landsat TM and ground investigation data, the entire Loess Plateau was first divided into 3 380 Fundamental Assessment Units （FAUs） to adapt to this regional modeling and fast assessment. A set of easily available parameters reflecting relevant water erosion factors at a regional scale was then developed, in which dynamic and static factors were discriminated. Arclnfo GIS was used to integrate all essential data into a central database. A resulting mathematical model was established to link the sediment yields and the selected variables on the basis of FAUs through overlay in GIS and multiple regression analyses. The sensitivity analyses and validation results show that this approach works effectively in assessing large area soil erosion, and also helps to understand the regional associations of erosion and its impact factors, and thus might significantly contribute to planning and policymaking for a large area erosion control in the Loess Plateau.

Multilevel Power Modeling of Base Station and Its ICs

A new power estimation method is proposed for base station(BS) in this paper.Based on this method,a software platform for power estimation is developed.The proposed method models power consumption on different abstraction levels by splitting a typical base station into several basic components at different levels in the view of embedded system design.In particular,our focus is on baseband IC(Integrate Circuit) due to it's the dominant power consumer in small cells.Baseband power model is based on arithmetic computing costs of selected algorithms.All computing and storage costs are calibrated using algorithm complexity,hardware architecture,activity ratio,silicon technology,and overheads on all hierarchies.Micro architecture and IC technology are considered.The model enables power comparison of different types of base stations configured with different baseband algorithms,micro architectures,and ICs.The model also supports cellular operators in power estimation of different deployment strategies and transmission schemes.The model is verified by comparing power consumption with a real LTE base station.By exposing more configuration freedoms,the platform can be used for power estimation of current and future base stations.

Arnol＇d＇s Second Nonlinear Stability Theorem for General Multilayer Quasi－geostrophic Model

Arnol'd's second nonlinear stability criterion for motions governed by a general multilayer quasi-geostrophic model is established. The model allows arbitrary density jumps and layer thickness, and at the top and the bottom of the nuid, the boundary condition is either free or rigid. The criterion is obtained by the establishment of the upper bounds of disturbance energy and potential enstrophy in terms of the initial disturbance field.