二三维一体化GIS Server在城市信息模型(CIM)中的应用

城市信息模型(CIM)是新型智慧城市的数字基础设施和城市数字化转型的关键抓手,而无缝集成二维地理信息、三维模型和建筑信息模型(BIM)等实现二三维一体化是建设城市信息模型(CIM)基础平台中的关键技术。本文在分析研究CIM平台关键技术基础上提出了一套跨平台、自主化、界面化、B/S网络化的二三维一体化GIS Server解决方案,重点介绍该系统的总体框架及关键技术,并展示了其在城市信息模型(CIM)中的应用成效,为CIM基础平台的建设提供借鉴。

Distributed event region fault-tolerance based on weighted distance for wireless sensor networks

Event region detection is the important application for wireless sensor networks（WSNs）, where the existing faulty sensors would lead to drastic deterioration of network quality of service.Considering single-moment nodes fault-tolerance, a novel distributed fault-tolerant detection algorithm named distributed fault-tolerance based on weighted distance（DFWD） is proposed, which exploits the spatial correlation among sensor nodes and their redundant information.In sensor networks, neighborhood sensor nodes will be endowed with different relative weights respectively according to the distances between them and the central node.Having syncretized the weighted information of dual-neighborhood nodes appropriately, it is reasonable to decide the ultimate status of the central sensor node.Simultaneously, readings of faulty sensors would be corrected during this process.Simulation results demonstrate that the DFWD has a higher fault detection accuracy compared with other algorithms, and when the sensor fault probability is 10%, the DFWD can still correct more than 91% faulty sensor nodes, which significantly improves the performance of the whole sensor network.

A Fault Detection Mechanism in Erasure-Code Byzantine Fault-Tolerance Quorum

Fault-tolerance is increasingly significant for large-scale storage systems in which Byzantine failure of storage nodes may happen. Traditional Byzantine Quorum systems that tolerate Byzantine failures by using replication have two main limitations： low space-efficiency and static quorum variables. We propose an Erasure-code Byzantine Fault-tolerance Quorum that can provide high reliability with far lower storage overhead than replication by adopting erasure code as redundancy scheme. Through read/write operations of clients and diagnose operation of supervisor, our Quorum system can detect Byzantine nodes, and dynamically adjust system size and fault threshold. Simulation results show that our method improves performance for the Quorum with relatively small quorums.

Adaptive fault-tolerant control of heavy lift launch vehicle via differential algebraic observer

A novel adaptive fault-tolerant control scheme in the differential algebraic framework was proposed for attitude control of a heavy lift launch vehicle （HLLV）. By using purely mathematical transformations, the decoupled input-output representations of HLLV were derived, rendering three decoupled second-order systems, i.e., pitch, yaw and roll channels. Based on a new type of numerical differentiator, a differential algebraic observer （DAO） was proposed for estimating the system states and the generalized disturbances, including various disturbances and additive fault torques. Driven by DAOs, three improved proportional-integral- differential （PID） controllers with disturbance compensation were designed for pitch, yaw and roll control. All signals in the closed-loop system were guaranteed to be ultimately uniformly bounded by utilization of Lyapunov＇s indirect method. The convincing numerical simulations indicate that the proposed control scheme is successful in achieving high performance in the presence of parametric perturbations, external disturbances, noisy corruptions, and actuator faults.

Disturbance observer-based fuzzy fault-tolerant control for high-speed trains with multiple disturbances

The fault-tolerant control problem is investigated for high-speed trains with actuator faults and multiple disturbances.Based on the novel train model resulting from the Takagi–Sugeno fuzzy theory, a sliding-mode fault-tolerant control strategy is proposed. The norm bounded disturbances which are composed of interactive forces among adjacent carriages and basis running resistances are rearranged by the fuzzy linearity technique. The modeled disturbances described as an exogenous system are compensated for by a disturbance observer. Moreover, a sliding mode surface is constructed, which can transform the stabilization problem of position and velocity into the stabilization problem of position errors and velocity errors, i.e., the tracking problem of position and velocity. Based on the parallel distributed compensation method and the disturbance observer, the fault-tolerant controller is solved. The Lyapunov theory is used to prove the stability of the closed-loop system. The feasibility and effectiveness of the proposed fault-tolerant control strategy are illustrated by simulation results.

Self Fault-Tolerance of Protocols: A Case Study

The prerequisite for the existing protocols' correctness is that protocols can be normally operated under the normal conditions, rather than dealing with abnormal conditions. In other words, protocols with the fault-tolerance can not be provided when some fault occurs. This paper discusses the self fault-tolerance of protocols. It describes some concepts and methods for achieving self fault-tolerance of protocols. Meanwhile, it provides a case study, investigates a typical protocol that does not satisfy the self fault-tolerance, and gives a new redesign version of this existing protocol using the proposed approach.

SQL Server性能优化的技术分析

随着客户端/服务器技术和多层架构的进步,系统效率问题日益引发广泛讨论。由于缺乏数据库管理系统(DBMS)提供的优化方法和工具,以及基于微软技术的数据库管理员和应用程序开发人员的知识,无法对设计和服务执行系统进行优化。文章回顾了提高SQL Server实例性能时需要考虑的目标,并阐述了用于优化查询的技术。

基于Windows Server Failover Cluster的Apache故障转移集群应用实践

在当前互联网时代,Web应用程序的高可用性和可靠性是确保业务持续运行的关键因素。针对Apache Web服务器,介绍了利用Windows Server 2019 Failover Cluster构建Apache故障转移集群的实践方案。通过配置两个节点的故障转移集群,当某个节点发生故障时,Apache服务将自动在另一个节点上重新启动,从而最大程度地减少系统中断的时间,提高Web应用的可用性。详细阐述了集群搭建的具体步骤、配置要点、集群验证方法以及运行时的监控与维护方法,为构建高可用Apache Web服务器提供一种实用的解决方案。

CRBFT:A Byzantine Fault-Tolerant Consensus Protocol Based on Collaborative Filtering Recommendation for Blockchains

Blockchain has been widely used in finance,the Internet of Things(IoT),supply chains,and other scenarios as a revolutionary technology.Consensus protocol plays a vital role in blockchain,which helps all participants to maintain the storage state consistently.However,with the improvement of network environment complexity and system scale,blockchain development is limited by the performance,security,and scalability of the consensus protocol.To address this problem,this paper introduces the collaborative filtering mechanism commonly used in the recommendation system into the Practical Byzantine Fault Tolerance(PBFT)and proposes a Byzantine fault-tolerant(BFT)consensus protocol based on collaborative filtering recommendation(CRBFT).Specifically,an improved collaborative filtering recommendation method is designed to use the similarity between a node’s recommendation opinions and those of the recommender as a basis for determining whether to adopt the recommendation opinions.This can amplify the recommendation voice of good nodes,weaken the impact of cunningmalicious nodes on the trust value calculation,andmake the calculated resultsmore accurate.In addition,the nodes are given voting power according to their trust value,and a weight randomelection algorithm is designed and implemented to reduce the risk of attack.The experimental results show that CRBFT can effectively eliminate various malicious nodes and improve the performance of blockchain systems in complex network environments,and the feasibility of CRBFT is also proven by theoretical analysis.

Review of Fault-tolerant Control for Motor Inverter Failure with Operational Quality Considered

In recent years,motor drive systems have garnered increasing attention due to their high efficiency and superior control performance.This is especially apparent in aerospace,marine propulsion,and electric vehicles,where high performance,efficiency,and reliability are crucial.The ability of the drive system to maintain long-term fault-tolerant control(FTC)operation after a failure is essential.The likelihood of inverter failures surpasses that of other components in the drive system,highlighting its critical importance.Long-term FTC operation ensures the system retains its fundamental functions until safe repairs or replacements can be made.The focus of developing a FTC strategy has shifted from basic FTC operations to enhancing the post-fault quality to accommodate the realities of prolonged operation post-failure.This paper primarily investigates FTC strategies for inverter failures in various motor drive systems over the past decade.These strategies are categorized into three types based on post-fault operational quality:rescue,remedy,and reestablishment.The paper discusses each typical control strategy and its research focus,the strengths and weaknesses of various algorithms,and recent advancements in FTC.Finally,this review summarizes effective FTC techniques for inverter failures in motor drive systems and suggests directions for future research.

Integration of a Fault-Tolerant H-Bridge Inverter into the Photovoltaic System for DC-AC Conversion of Electrical Energy

The photovoltaic system is experiencing great growth in the production of electrical energy these days.It plays a vital role in the production of electrical energy in isolated towns.It is generally either stand-alone or connected to a network.The energy produced by the photovoltaic generator is in continuous form;the conversion from its continuous form to the alternating form requires a converter:the inverter.In order to improve the quality of the waveform,we moved from the classic solar inverter to multilevel inverters.These multilevel inverters are equipped with power switches which are required to withstand strong fluctuations in the voltage produced by the GPV(photovoltaic generator).It is obvious that the degradation of the inverter leads to a distortion of the wave quality.This article presents the simulation of the GPV-Chopper Boost-Inverter chain in fault-tolerant cascaded H-bridges in order to overcome the difficulties of voltage constraints experienced by power switches(IGBT:insulated gate bipolar transistor).The results of simulations carried out in Matlab/Simulink show good performance of the designed inverter model.

A finite-time fuzzy adaptive output-feedback fault-tolerant control for underactuated wheeled mobile robots systems

This paper investigates the adaptive fuzzy finite-time output-feedback fault-tolerant control (FTC) problemfor a class of nonlinear underactuated wheeled mobile robots (UWMRs) system with intermittent actuatorfaults. The UWMR system includes unknown nonlinear dynamics and immeasurable states. Fuzzy logic systems(FLSs) are utilized to work out immeasurable functions. Furthermore, with the support of the backsteppingcontrol technique and adaptive fuzzy state observer, a fuzzy adaptive finite-time output-feedback FTC scheme isdeveloped under the intermittent actuator faults. It is testifying the scheme can ensure the controlled nonlinearUWMRs is stable and the estimation errors are convergent. Finally, the comparison results and simulationvalidate the effectiveness of the proposed fuzzy adaptive finite-time FTC approach.

基于SQL Server的供销合作社纵向一体化信息管理系统的设计与实现

本文以目前最为成熟的SQLServer数据库为技术基础,以纵向一体化战略作为技术实现的目标和方向,通过战略引领、技术支撑,整合供销合作社纵向一体化过程中的各项数据和信息,充分发挥大数据应用、分析带来的无限价值,期望为本领域或相似领域的技术和管理人员带来启发,为充分有效利用信息化时代带来的红利做好准备。

Python Server Page Performance Analysis and Modeling

Today, in the field of computer networks, new services have been developed on the Internet or intranets, including the mail server, database management, sounds, videos and the web server itself Apache. The number of solutions for this server is therefore growing continuously, these services are becoming more and more complex and expensive, without being able to fulfill the needs of the users. The absence of benchmarks for websites with dynamic content is the major obstacle to research in this area. These users place high demands on the speed of access to information on the Internet. This is why the performance of the web server is critically important. Several factors influence performance, such as server execution speed, network saturation on the internet or intranet, increased response time, and throughputs. By measuring these factors, we propose a performance evaluation strategy for servers that allows us to determine the actual performance of different servers in terms of user satisfaction. Furthermore, we identified performance characteristics such as throughput, resource utilization, and response time of a system through measurement and modeling by simulation. Finally, we present a simple queue model of an Apache web server, which reasonably represents the behavior of a saturated web server using the Simulink model in Matlab (Matrix Laboratory) and also incorporates sporadic incoming traffic. We obtain server performance metrics such as average response time and throughput through simulations. Compared to other models, our model is conceptually straightforward. The model has been validated through measurements and simulations during the tests that we conducted.

FedAdaSS: Federated Learning with Adaptive Parameter Server Selection Based on Elastic Cloud Resources

The rapid expansion of artificial intelligence(AI)applications has raised significant concerns about user privacy,prompting the development of privacy-preserving machine learning(ML)paradigms such as federated learning(FL).FL enables the distributed training of ML models,keeping data on local devices and thus addressing the privacy concerns of users.However,challenges arise from the heterogeneous nature of mobile client devices,partial engagement of training,and non-independent identically distributed(non-IID)data distribution,leading to performance degradation and optimization objective bias in FL training.With the development of 5G/6G networks and the integration of cloud computing edge computing resources,globally distributed cloud computing resources can be effectively utilized to optimize the FL process.Through the specific parameters of the server through the selection mechanism,it does not increase the monetary cost and reduces the network latency overhead,but also balances the objectives of communication optimization and low engagement mitigation that cannot be achieved simultaneously in a single-server framework of existing works.In this paper,we propose the FedAdaSS algorithm,an adaptive parameter server selection mechanism designed to optimize the training efficiency in each round of FL training by selecting the most appropriate server as the parameter server.Our approach leverages the flexibility of cloud resource computing power,and allows organizers to strategically select servers for data broadcasting and aggregation,thus improving training performance while maintaining cost efficiency.The FedAdaSS algorithm estimates the utility of client systems and servers and incorporates an adaptive random reshuffling strategy that selects the optimal server in each round of the training process.Theoretical analysis confirms the convergence of FedAdaSS under strong convexity and L-smooth assumptions,and comparative experiments within the FLSim framework demonstrate a reduction in training round-to-accuracy by 12%–20%compared to the Federated Averaging(FedAvg)with random reshuffling method under unique server.Furthermore,FedAdaSS effectively mitigates performance loss caused by low client engagement,reducing the loss indicator by 50%.

A Design of an SMTP Email Server

This study developed a mail server program using Socket API and Python.The program uses the Hypertext Transfer Protocol(HTTP)to receive emails from browser clients and forward them to actual email service providers via the Simple Mail Transfer Protocol(SMTP).As a web server,it handles Transmission Control Protocol(TCP)connection requests from browsers,receives HTTP commands and email data,and temporarily stores the emails in a file.Simultaneously,as an SMTP client,the program establishes a TCP connection with the actual mail server,sends SMTP commands,and transmits the previously saved emails.In addition,we also analyzed security issues and the efficiency and availability of this server,providing insights into the design of SMTP mail servers.

Excel+SQL Server在实验成绩信息管理中的应用研究

深入探讨了如何利用Excel和SQL Server集成化地管理和分析大学物理实验成绩信息。通过建立数据库、导入导出数据、数据查询与分析及使用Excel的数据透视表和图表功能,可以高效地管理实验成绩数据,进而深入分析学生的学习情况和教学效果。

多地图服务管理对象在ArcGIS Server中的设计与实现

在基于ArcGIS Server的WebGIS应用中,服务器在生成海量地图服务时,由于每个地图服务都会占用大量服务器CPU资源,会导致服务器处于瘫痪状态。针对应用中遇到的瓶颈问题,提出建立基于ArcGIS Server的动态多地图服务管理对象的方案,将多地图服务管理对象置于GIS服务器端。当客户端发出新的地图请求时,进行多地图服务管理对象检验,根据设定的地图服务上限,向ArcGIS Server发出创建新的地图服务的请求或是发出删除某地图服务的请求,从而解决服务器经常处于瘫痪的问题。

基于Excel Server的高校实验室安全管理系统设计

针对目前高校实验室安全管理信息化程度较低和管理理念滞后以及缺乏科学性和规范性的现状,设计了一种基于Excel Server技术的实验室安全管理系统。此系统以校园网为平台,利用Excel Server技术,构建实验操作人员、实验责任教师、实验药品储存库管理员、系统管理员以及学校安全主管部门之间的信息交流。经过数据分析,可以快捷直观地了解各实验室、实验药品储存库的详细数据流程以及实验药品的出入库、实验数据、废弃物处理情况,同时也可以通过网页Web在学校安全工作领导小组内部办公网络中发布,让安全信息得到分享。

基于ArcGIS Server和VML的气象信息发布平台

该文采用ESRI公司的ArcGIS Server配合ArcSDE,Oracle数据库软件,结合ASP.NET,JavaScript,VML,Ajax技术开发了基于ArcGIS Server和VML技术的气象信息发布系统。该系统将实时气象资料融入实际的地理信息环境,实现动态信息查询、统计及各种统计图表展示,并充分发挥GIS空间分析能力,实现等值面、面雨量、缓冲区和叠加分析,为气象预报工作提供及时、有效、科学的辅助决策支持,为社会提供优质气象服务。