Research on Computer Network Can and Performance Asalysis

After analysing and discussing the goal and problems of computer networkdesign, the authors developed a computer network CAD with detaileddescriptions. Its architecture, functions and modules are given. Lastly a set ofparameters for performance evaluation are proposed.

A Study on Priority Based ZigBee Network Performance Analysis with Tree Routing Method

The Wireless Sensor Network (WSN) is spatially distributed autonomous sensor to sense special task. WSN like ZigBee network forms simple interconnecting, low power, and low processing capability wireless devices. The ZigBee devices facilitate numerous applications such as pervasive computing, security monitoring and control. ZigBee end devices collect sensing data and send them to ZigBee Coordinator. The Coordinator processes end device requests. The effect of a large number of random unsynchronized requests may degrade the overall network performance. An effective technique is particularly needed for synchronizing available node’s request processing to design a reliable ZigBee network. In this paper, region based priority mechanism is implemented to synchronize request with Tree Routing Method. Riverbed is used to simulate and analyze overall ZigBee network performance. The results show that the performance of the overall priority based ZigBee network model is better than without a priority based model. This research paves the way for further designing and modeling a large scale ZigBee network.

Release and Dynamic Management of CAD Network Graphics Library

We aimed at the release and dynamic management of CAD network graphics library (NGL). The characteristics of realization on network of CAD graphics are analysed, while the existing problems of the presenting share methods of graphics file are also discussed. Release and dynamic management are accomplished with the B/S combined with C/S as well as the file organization based on attribute information, which have essential practical sense to the establishment of CAD NGL, share and cooperation in tech-design as well as the distance education of engineering graphics.

Research on a Dispersed Networked CAD/CAM System of Motorcycle

In order to improve competitive ability of market, mo torcycle enterprises, special the small and middle sized ones must use IT to org anize social resource and adopt effective production mode, namely the dispersed networked design and manufacturing (DNDM), which was put forward and proved to b e one of vitality production modes in recent years. In responding to the new pro duction mode of VMCE, a dispersed networked CAD/CAM system (DNCADMS) of motorcyc le products should be developed. The objective of this paper is to investigate a new design and manufacturing mode and technical environment of motorcycle produ ction based on the concept of the DNDM for the small and meddle sized motorcycle enterprises. Because there are various CAx software systems, including differen t kinds of isolated CD, CAD, CAE, CAPP, CAM, PDM, and so on, are used at differe nt stages of the life period of motorcycle products under heterogeneous environm ents, to build a DNCADMS of motorcycle with high performance, some key issues, n amely the architecture of the DNCADMS, the integration of the isolated CAx softw are systems (CAxs), the data communication and exchange between these isolated s ystems and the data share problem under the dispersed heterogeneous database env ironment, should be solved well. For this, the idea we propose is the combinatio n of Web, CORBA, STEP and Java, which provides an effective mechanism to support the integration of isolated CAxs, and support communication and interoperabilit y among CAx systems. Each isolated CAx has been encapsulated respectively by a c ontainer, which is implemented by the ORBs and the IDL of the COBRA technology s tandard, and managed by the application index server. Each container is connecte d with the others by a local network or intranet/Extranet/internet and communica tes through network. For exchanging design and manufacturing information and kno wledge via a local network or the Internet, a commmerical product data translato r has been employed as a product data translating server to complete product dat a communication and exchange between the isolated CAx systems. And for solving t he data share problem under the dispersed networked heterogeneous database envir onment, the idea we propose is to build a meta-database for the native database s, which is a dispersed database, and links various native databases into a whol e logical database. For managing the meta-database, the database index server, a Java-based integrating mechanism, has been also put forward in this paper. Th e application and database index servers have been implemented with Java lan guage. Moreover, the native data base and knowledge base related to each isolate d CAx are be integrated into a dispersed database system by a meta-base.

Design of Intelligent Network Performance Analysis & Forecast Support System

A system designed for supporting the network performance analysis and forecast effort is presented, based on the combination of offline network analysis and online real-time performance forecast. The off-line analysis will perform analysis of specific network node performance, correlation analysis of relative network nodes performance and evolutionary mathematical modeling of long-term network performance measurements. The online real-time network performance forecast will be based on one so-called hybrid prediction modeling approach for short-term network, performance prediction and trend analysis. Based on the module design, the system proposed has good intelligence, scalability and self-adaptability, which will offer highly effective network performance analysis and forecast tools for network managers, and is one ideal support platform for network performance analysis and forecast effort.

Design and Implementation of a Network Performance Analysis System for Space Network Emulation Platforms

Emulation platforms are critical for evaluation and verification in the research of networking technologies and protocols for space networks(SN).High fidelity emulating technologies have been extensively studied for SN in earlier work,while little emphasis has been placed on the performance evaluation part.In this paper,the design of a network performance analysis architecture is presented,with which high-speed network traffic can be captured and indexed,and the performance of the emulated SN can be well analyzed and evaluated.This architecture comprises three components,namely capture layer,storage layer and analysis layer.Analytic Hierarchy Process(AHP)and several analysis methods are adopted to evaluate the network performance comprehensively.In the implementation of the proposed architecture,configuration optimization and parallel processing are applied to handle large amount of high-speed network traffic.Finally,experiment results through the analysis system exhibits the effectiveness of the proposed architecture.

Evaluation of Broadband Network Performance in Nigeria

Broadband provides high speed data transmission to Internet and 4G networks were developed to transform broadband technology with higher data rate and enhanced quality of service. The performance of broadband network in Nigeria in terms of type, purpose and speed was evaluated in this work. Some quarters at Ilesa and Oba-Ile in Akure were chosen as rural areas, while Abuja and Lagos represented the urban areas of the study. Questionnaires were administered among users in these areas randomly. Thereafter, data were analyzed and research questions answered from the analyzed results. The results showed that the majority of the respondents operated on wireless broadband technologies. The download speed is generally above 100 mbps in urban areas and below in rural areas, with MTN having the highest number of subscribers. In addition, most of the Internet surfers download files. With these characteristics, it was discovered that the network operators were deploying 3G systems as broadband instead of 4G systems.

Providing Guaranteed Network Performance across Tenants:Advances,Challenges and Opportunities

The varied network performance in the cloud hurts application performance.This increases the tenant’s cost and becomes the key hindrance to cloud adoption.It is because virtual machines(VMs)belonging to one tenant can reside in multiple physical servers and communication interference across tenants occasionally occurs when encountering network congestion.In order to prevent such unpredictability,it is critical for cloud providers to offer the guaranteed network performance at tenant level.Such a critical issue has drawn increasing attention in both academia and industry.Many elaborate mechanisms are proposed to provide guaranteed network performance,such as guaranteed bandwidth or bounded message delay across tenants.However,due to the intrinsic complexities and limited capabilities of commodity hardware,the deployment of these mechanisms still faces great challenges in current cloud datacenters.Moreover,with the rapid development of new technologies,there are new opportunities to improve the performance of existing works,but these possibilities are not under full discussion yet.Therefore,in this paper,we survey the latest development of the network performance guarantee approaches and summarize them based on their features.Then,we explore and discuss the possibilities of using emerging technologies as knobs to upgrade the performance or overcome the inherent shortcomings of existing advances.We hope this article will help readers quickly Received:Apr.07,2020 Revised:Oct.23,2020 Editor:Haifeng Zheng understand the causes of the problems and serve as a guide to motivate researchers to develop innovative algorithms and frameworks.

《Storage Network Performance Analysis》

《Storage Network Performance Analysis》一书作者Huseyin Simitci博士，是XIOtech公司的工程研究人员，致力于高性能输入、输出系统和并行文件系统自适应技术的研究．并在这些领域发表有研究论文。本书是一本深入指导分析和改进网络存储性能的书籍。

Trajectory tracking guidance of interceptor via prescribed performance integral sliding mode with neural network disturbance observer

This paper investigates interception missiles’trajectory tracking guidance problem under wind field and external disturbances in the boost phase.Indeed,the velocity control in such trajectory tracking guidance systems of missiles is challenging.As our contribution,the velocity control channel is designed to deal with the intractable velocity problem and improve tracking accuracy.The global prescribed performance function,which guarantees the tracking error within the set range and the global convergence of the tracking guidance system,is first proposed based on the traditional PPF.Then,a tracking guidance strategy is derived using the integral sliding mode control techniques to make the sliding manifold and tracking errors converge to zero and avoid singularities.Meanwhile,an improved switching control law is introduced into the designed tracking guidance algorithm to deal with the chattering problem.A back propagation neural network(BPNN)extended state observer(BPNNESO)is employed in the inner loop to identify disturbances.The obtained results indicate that the proposed tracking guidance approach achieves the trajectory tracking guidance objective without and with disturbances and outperforms the existing tracking guidance schemes with the lowest tracking errors,convergence times,and overshoots.

Finite-time Prescribed Performance Time-Varying Formation Control for Second-Order Multi-Agent Systems With Non-Strict Feedback Based on a Neural Network Observer

This paper studies the problem of time-varying formation control with finite-time prescribed performance for nonstrict feedback second-order multi-agent systems with unmeasured states and unknown nonlinearities.To eliminate nonlinearities,neural networks are applied to approximate the inherent dynamics of the system.In addition,due to the limitations of the actual working conditions,each follower agent can only obtain the locally measurable partial state information of the leader agent.To address this problem,a neural network state observer based on the leader state information is designed.Then,a finite-time prescribed performance adaptive output feedback control strategy is proposed by restricting the sliding mode surface to a prescribed region,which ensures that the closed-loop system has practical finite-time stability and that formation errors of the multi-agent systems converge to the prescribed performance bound in finite time.Finally,a numerical simulation is provided to demonstrate the practicality and effectiveness of the developed algorithm.

Performance of Gas-Steam Combined Cycle Cogeneration Units Influenced by Heating Network Terminal Steam Parameters

The determination of source-side extracted heating parameters is of great significance to the economic operation of cogeneration systems.This paper investigated the coupling performance of a cogeneration heating and power system multidimensionally based on the operating characteristics of the cogeneration units,the hydraulic and thermodynamic characteristics of the heating network,and the energy loads.Taking a steam network supported by a gas-steam combined cycle cogeneration system as the research case,the interaction effect among the source-side prime movers,the heating networks,and the terminal demand thermal parameters were investigated based on the designed values,the plant testing data,and the validated simulation.The operating maps of the gas-steam combined cycle cogeneration units were obtained using THERMOFLEX,and the minimum source-side steam parameters of the steam network were solved using an inverse solution procedure based on the hydro-thermodynamic coupling model.The cogeneration operating maps indicate that the available operating domain considerably narrows with the rise of the extraction steam pressure and flow rate.The heating network inverse solution demonstrates that the source-side steam pressure and temperature can be optimized from the originally designed 1.11 MPa and 238.8°C to 1.074 MPa and 191.15°C,respectively.Under the operating strategy with the minimum source-side heating parameters,the power peak regulation depth remarkably increases to 18.30%whereas the comprehensive thermal efficiency decreases.The operation under the minimum source-side heating steam parameters can be superior to the originally designed one in the economy at a higher price of the heating steam.At a fuel price of$0.38/kg and the power to fuel price of 0.18 kg/(kW·h),the critical price ratio of heating steam to fuel is 119.1 kg/t.The influence of the power-fuel price ratio on the economic deviation appears relatively weak.

人工神经网络与智能 CAD

通过分析目前ＣＡＤ专家系统中存在的问题，对人工神经网络在智能ＣＡＤ中应用的理论和方法进行了探讨。文中介绍了人工神经网络在模拟形象思维、知识获取、知识表示等方面的应用，并对存在的一些问题进行了详细的讨论。

CIOM Intranet 和 CAD 网络工程设计

论述了建立企业内部网和实现ＣＡＤ网的基本构想，并以长春光机所为设计对象，提出了企业内部网和ＣＡＤ网的解决方案。

PerfMon: Measuring Application-Level Performance in a Large-Scale Campus Wireless Network

WiFi has become one of the most popular ways to access the Internet.However,in large-scale campus wireless networks,it is challenging for network administrators to provide optimized access quality without knowledge on fine-grained traffic characteristics and real network performance.In this paper,we implement PerfMon,a network performance measurement and diagnosis system,which integrates collected multi-source datasets and analysis methods.Based on PerfMon,we first conduct a comprehensive measurement on application-level traffic patterns and behaviors from multiple dimensions in the wireless network of T university(TWLAN),which is one of the largest campus wireless networks.Then we systematically study the application-level network performance.We observe that the application-level traffic behaviors and performance vary greatly across different locations and device types.The performance is far from satisfactory in some cases.To diagnose these problems,we distinguish locations and device types,and further locate the most crucial factors that affect the performance.The results of case studies show that the influential factors can effectively characterize performance changes and explain for performance degradation.

A CSMA/CA based MAC protocol for hybrid Power-line/Visible-light communication networks:Design and analysis

Hybrid Power-line/Visible-light Communication(HPVC)network has been one of the most promising Cooperative Communication(CC)technologies for constructing Smart Home due to its superior communication reliability and hardware efficiency.Current research on HPVC networks focuses on the performance analysis and optimization of the Physical(PHY)layer,where the Power Line Communication(PLC)component only serves as the backbone to provide power to light Emitting Diode(LED)devices.So designing a Media Access Control(MAC)protocol remains a great challenge because it allows both PLC and Visible Light Communication(VLC)components to operate data transmission,i.e.,to achieve a true HPVC network CC.To solve this problem,we propose a new HPC network MAC protocol(HPVC MAC)based on Carrier Sense Multiple Access/Collision Avoidance(CSMA/CA)by combining IEEE 802.15.7 and IEEE 1901 standards.Firstly,we add an Additional Assistance(AA)layer to provide the channel selection strategies for sensor stations,so that they can complete data transmission on the selected channel via the specified CSMA/CA mechanism,respectively.Based on this,we give a detailed working principle of the HPVC MAC,followed by the construction of a joint analytical model for mathematicalmathematical validation of the HPVC MAC.In the modeling process,the impacts of PHY layer settings(including channel fading types and additive noise feature),CSMA/CA mechanisms of 802.15.7 and 1901,and practical configurations(such as traffic rate,transit buffer size)are comprehensively taken into consideration.Moreover,we prove the proposed analytical model has the solvability.Finally,through extensive simulations,we characterize the HPVC MAC performance under different system parameters and verify the correctness of the corresponding analytical model with an average error rate of 4.62%between the simulation and analytical results.

Tunnelling performance prediction of cantilever boring machine in sedimentary hard-rock tunnel using deep belief network

Evaluating the adaptability of cantilever boring machine(CBM) through in-depth excavation and analysis of tunnel excavation data and rock mass parameters is the premise of mechanical design and efficient excavation in the field of underground space engineering.This paper presented a case study of tunnelling performance prediction method of CBM in sedimentary hard-rock tunnel of Karst landform type by using tunneling data and surrounding rock parameters.The uniaxial compressive strength(UCS),rock integrity factor(Kv),basic quality index([BQ]),rock quality index RQD,brazilian tensile strength(BTS) and brittleness index(BI) were introduced to construct a performance prediction database based on the hard-rock tunnel of Guiyang Metro Line 1 and Line 3,and then established the performance prediction model of cantilever boring machine.Then the deep belief network(DBN) was introduced into the performance prediction model,and the reliability of performance prediction model was verified by combining with engineering data.The study showed that the influence degree of surrounding rock parameters on the tunneling performance of the cantilever boring machine is UCS > [BQ] > BTS >RQD > Kv > BI.The performance prediction model shows that the instantaneous cutting rate(ICR) has a good correlation with the surrounding rock parameters,and the predicting model accuracy is related to the reliability of construction data.The prediction of limestone and dolomite sections of Line 3 based on the DBN performance prediction model shows that the measured ICR and predicted ICR is consistent and the built performance prediction model is reliable.The research results have theoretical reference significance for the applicability analysis and mechanical selection of cantilever boring machine for hard rock tunnel.

Event-triggered H_(∞) PI state estimation for delayed switched neural networks

On state estimation problems of switched neural networks,most existing results with an event-triggered scheme(ETS)not only ignore the estimator information,but also just employ a fixed triggering threshold,and the estimation error cannot be guaranteed to converge to zero.In addition,the state estimator of non-switched neural networks with integral and exponentially convergent terms cannot be used to improve the estimation performance of switched neural networks due to the difficulties caused by the nonsmoothness of the considered Lyapunov function at the switching instants.In this paper,we aim at overcoming such difficulties and filling in the gaps,by proposing a novel adaptive ETS(AETS)to design an event-based H_(∞)switched proportional-integral(PI)state estimator.A triggering-dependent exponential convergence term and an integral term are introduced into the switched PI state estimator.The relationship among the average dwell time,the AETS and the PI state estimator are established by the triggering-dependent exponential convergence term such that estimation error asymptotically converges to zero with H_(∞)performance level.It is shown that the convergence rate of the resultant error system can be adaptively adjusted according to triggering signals.Finally,the validity of the proposed theoretical results is verified through two illustrative examples.

手绘 CAD 图形输入的识别

讨论了手绘ＣＡＤ图形输入的识别问题，提出了手绘图形识别方法，对曲线进行线性逼近以抑制噪声并减少识别数据量，提取几何与非几何特征进行粗分段，在此基础上利用基于ＢＰ算法的神经网络分类器进行直线和圆弧的分离和识别，以正确实现分段识别并重构图形。