基于云电脑业务场景的算网智能调度研究

本文旨在研究云电脑业务场景的算网感知和调度能力,通过云电脑业务场景特点分析,结合算网融合机制,提出了基于算网调度系统的创新解决方案,实现了资源的智能调度与优化,大幅提升了用户体验与业务效率。本文中的算网调度系统以其高效的信息处理能力、智能化的自我优化及强大的协同能力,为云电脑服务提供了强大的技术支撑,也为后续实践应用提供了有益参考。

基于云计算与大数据技术的算网调度管理系统建设研究

算网调度管理系统是一种高度智能化、高效化、安全化、可靠化的企业级资源调度和管理平台,可以为企业提供全方位的资源管理和调度服务,从而实现企业的可持续发展和高质量的业务增长。随着大带宽、低时延、强算力的需求越来越广,传统的系统由于算力资源与网络资源分布杂乱,没有一体化统一呈现算网资源及服务,导致组网不可视。同时,因为当前资源多以固定规格、配额为主,无法面对业务需求灵活、动态地调整算网资源。因此,在信息技术高速发展的背景下,如何利用新兴信息技术推进算网调度管理系统建设就成为各行各业亟须解决的重要课题。

算力网络与交易风控

算力作为数字经济的核心生产力,已经成为全球战略竞争的新焦点。传统计算模式不足以满足网络环境下的业务对于自身敏捷构造需求和外部大数据应用需求。在对比分析了网格计算、云计算、边缘计算、多云与云际计算的优缺点后,提出了一种新型计算模式:方舱计算,并介绍了方舱计算系统的三大组成部分。在此基础上,进一步提出了基于方舱计算构建算网系统的设想。作为方舱计算的典型应用,介绍了当前网络交易风控遇到的难题,结合方舱计算模式,通过建立并发系统行为理论与流量计算方法,发明了业务流程网络横切并发的调度技术,提出网络交易风控的行为认证方法,设计并实现了系统高并发、高辨识、高时效的目标。

FAULT LOCATION AND RECORDING SYSTEM OF TRANSMISSION LINES BASED ON COMPUTER NETWORK

In this paper a fault location and recording system based on a computer network is presented. A brief description of the system structure and main features are given. Emphasis is placed on the accurate fault location method for extra high voltage and long distance transmission lines.

Distributed Computation Models for Data Fusion System Simulation

An attempt has been made to develop a distributed software infrastructure model for onboard data fusion system simulation, which is also applied to netted radar systems, onboard distributed detection systems and advanced C3I systems. Two architectures are provided and verified: one is based on pure TCP/IP protocol and C/S model, and implemented with Winsock, the other is based on CORBA (common object request broker architecture). The performance of data fusion simulation system, i.e. reliability, flexibility and scalability, is improved and enhanced by two models. The study of them makes valuable explore on incorporating the distributed computation concepts into radar system simulation techniques.

Computer Network Control System in Automatic Automobile Detection

An automobile test controlling and managing system with computer network is introduced. The architecture of the local network, hardware structure, software structure, design of the test process, and error tolerating redundant design in work position substituting are presented. At last, the pivotal questions solved are discussed. With an advanced structure, this system is multi functional and flexible. Furthermore, advanced computer technology is adopted to improve its technical degree.

Global Optimization for the Synthesis of Integrated Water Systems with Particle Swarm Optimization Algorithm

The problem of optimal synthesis of an integrated water system is addressed in this study, where water using processes and water treatment operations are combined into a single network such that the total cost of fresh water and wastewater treatment is globally minimized. A superstructure that incorporates all feasible design alterna- tives for wastewater treatment, reuse and recycle, is synthesized with a non-linear programming model. An evolutionary approach--an improved particle swarm optimization is proposed for optimizing such systems. Two simple examples are .Presented.to illustrate the global op.timization of inte.grated water networks using the proposed algorithm.

Two-stage evolutionary algorithm for dynamic multicast routing in mesh network

In order to share multimedia transmissions in mesh networks and optimize the utilization of network resources, this paper presents a Two-stage Evolutionary Algorithm (TEA), i.e., unicast routing evolution and multicast path composition, for dynamic multicast routing. The TEA uses a novel link-duplicate-degree encoding, which can encode a multicast path in the link-duplicate-degree and decode the path as a link vector easily. A dynamic algorithm for adding nodes to or removing nodes from a multicast group and a repairing algorithm are also covered in this paper. As the TEA is based on global evaluation, the quality of the multicast path remains stabilized without degradation when multicast members change over time. Therefore, it is not necessary to rearrange the multicast path during the life cycle of the multicast sessions. Simulation results show that the TEA is efficient and convergent.

Design and Implementation of Verification Code Identification Based on Anisotropic Heat Kernel

Many websites use verification codes to prevent users from using the machine automatically to register,login,malicious vote or irrigate but it brought great burden to the enterprises involved in internet marketing as entering the verification code manually.Improving the verification code security system needs the identification method as the corresponding testing system.We propose an anisotropic heat kernel equation group which can generate a heat source scale space during the kernel evolution based on infinite heat source axiom,design a multi-step anisotropic verification code identification algorithm which includes core procedure of building anisotropic heat kernel,settingwave energy information parameters,combing outverification codccharacters and corresponding peripheral procedure of gray scaling,binarizing,denoising,normalizing,segmenting and identifying,give out the detail criterion and parameter set.Actual test show the anisotropic heat kernel identification algorithm can be used on many kinds of verification code including text characters,mathematical,Chinese,voice,3D,programming,video,advertising,it has a higher rate of 25%and 50%than neural network and context matching algorithm separately for Yahoo site,49%and 60%for Captcha site,20%and 52%for Baidu site,60%and 65%for 3DTakers site,40%,and 51%.for MDP site.

A nonlinear PCA algorithm based on RBF neural networks

Traditional PCA is a linear method, but most engineering problems are nonlinear. Using the linear PCA in nonlinear problems may bring distorted and misleading results. Therefore, an approach of nonlinear principal component analysis (NLPCA) using radial basis function (RBF) neural network is developed in this paper. The orthogonal least squares (OLS) algorithm is used to train the RBF neural network. This method improves the training speed and prevents it from being trapped in local optimization. Results of two experiments show that this NLPCA method can effectively capture nonlinear correlation of nonlinear complex data, and improve the precision of the classification and the prediction.

Multi-agent reinforcement learning using modular neural network Q-learning algorithms

Reinforcement learning is an excellent approach which is used in artificial intelligence,automatic control, etc. However, ordinary reinforcement learning algorithm, such as Q-learning with lookup table cannot cope with extremely complex and dynamic environment due to the huge state space. To reduce the state space, modular neural network Q-learning algorithm is proposed, which combines Q-learning algorithm with neural network and module method. Forward feedback neural network, Elman neural network and radius-basis neural network are separately employed to construct such algorithm. It is revealed that Elman neural network Q-learning algorithm has the best performance under the condition that the same neural network training method, i.e. gradient descent error back-propagation algorithm is applied.

Data Mapping Principles and Algorithm for Self-Configurable Systems

With the challenges brought by the expansion of network scale,as well as the diversity of the equipments and the complexity of network protocols,many self-configurable systems have been proposed combining formal specification and model finding techniques.In this paper,we pay more attention to formal specifications of network information,i.e.,exploring principles and algorithm to map network information(topology,devices and status,etc.) to Alloy specifications.We first model network information in relational form,which is easy to realize because of the structured feature of network information in nature.Then we map the relational data to Alloy specifications according to our novel data mapping principles and algorithm.Based on the transition of relational data,it is possible to automatically map network information to Alloy specifications.We evaluate our data mapping principles and algorithm by applying them to a practical application scenario.The results illustrate that we can find a model for the task within a tolerant time interval,which implies that our novel approach can convert relational data to Alloy specifications correctly and efficiently.

A Secure Trust Model for P2P Systems Based on Trusted Computing

Trust is one of the most important security requirements in the design and implementation of peer-to-peer （P2P） systems. In an environment where peers＇ identity privacy is important, it may conflict with trustworthiness that is based on the knowledge related to the peer＇s identity, while identity privacy is usually achieved by hiding such knowledge. A trust model based on trusted computing （TC） technology was proposed to enhance the identity privacy of peers during the trustworthiness evaluation process between peers from different groups. The simulation results show that, the model can be implemented in an efficient way, and when the degree of anonymity within group （DAWG） is up to 0.6 and the percentage of malicious peers is up to 70%7 the service selection failure rate is less than 0.15.

Topology-aware Overlay Multicast over IP Multicast Networks

Most existing overlay multicast approaches refuse to consider any network layer support no matter whether it is available or not. This design principle greatly increases the complexity of the routing algorithms and makes the overlay topologies incompatible with the underlying network. To address these issues, topology-aware overlay multicast over IP multicast networks (TOMIMN) was proposed as a novel overlay multicast protocol, which exploits the cooperation between end-hosts and IP multicast routers to construct a topology-aware overlay tree. Through a little modification to protocol independent multicast sparse mode (PIM-SM), a multicast router is able to receive registration from nearby group members and redirect passing-by join requests to them. Due to the multicast router's support, TOMIMN organizes its group members into an overlay multicast tree efficiently, which matches the physical network topology well.

Impacts of Packet Collisions on Link Throughput in CSMA Wireless Networks

It is known that packet collisions in wireless networks will deteriorate system performance, hence substantial efforts have been made to avoid collision in multi-user access designs. Also, there have been many studies on throughput analysis of CSMA wireless networks. However, for a typical CSMA network in which not all nodes can sense each other, it is still not well investigated how link throughputs are affected by collisions. We note that in practical 802.11-like networks, the time is divided into mini-timeslots and packet collisions are in fact unavoidable. Thus, it is desirable to move forward to explore how collisions in such a network will affect system performance. Based on the collision-free ideal CSMA network(ICN) model, this paper attempts to analyze link throughputs when taking the backoff collisions into account and examine the effect of collisions on link throughputs. Specifically, we propose an Extended Ideal CSMA Network(EICN) model to characterize the collision effects as well as the interactions and dependency among links in the network. Based on EICN, we could directly compute link throughputs and collision probabilities. Simulations show that the EICN model is of high accuracy. Under various network topologies and protocol parameter settings, the computation error of link throughputs using EICN is kept to 4% or below. Interestingly, we find that unlike expected, the effect of collisions on link throughputs in a modest CSMA wireless network is not significant, which enriches our understanding on practical CSMA wireless networks such as Wi-Fi.

Integrated and Intelligent Manufacturing： Perspectives and Enablers

With ever-increasing market competition and advances in technology, more and more countries are prioritizing advanced manufacturing technology as their top priority for economic growth. Germany announced the Industry 4.0 strategy in 2013. The US government launched the Advanced Manufacturing Partnership （AMP） in 2011 and the National Network for Manufacturing Innovation （NNMI） in 2014. Most recently, the Manufacturing USA initiative was officially rolled out to further ＂leverage existing resources... to nurture manufacturing innovation and accelerate commercialization＂ by fostering close collaboration between industry, academia, and government partners. In 2015, the Chinese government officially published a 10- year plan and roadmap toward manufacturing： Made in China 2025. In all these national initiatives, the core technology development and implementation is in the area of advanced manufacturing systems. A new manufacturing paradigm is emerging, which can be characterized by two unique features： integrated manufacturing and intelligent manufacturing. This trend is in line with the progress of industrial revolutions, in which higher efficiency in production systems is being continuously pursued. To this end, 10 major technologies can be identified for the new manufacturing paradigm. This paper describes the rationales and needs for integrated and intelligent manufacturing （i2M） systems. Related technologies from different fields are also described. In particular, key technological enablers, such as the Intemet of Things and Services （IoTS）, cyber-physical systems （CPSs）, and cloud computing are discussed. Challenges are addressed with applica- tions that are based on commercially available platforms such as General Electric （GE）＇s Predix and PTC＇s ThingWorx.

Context-aware computing-based reducing cost of service method in resource discovery and interaction

Reducing cost of service is an important goal for resource discovery and interaction technologies. The shortcomings of transhipment-method and hibernation-method are to increase holistic cost of service and to slower resource discovery respectively. To overcome these shortcomings, a context-aware computing-based method is developed. This method, firstly, analyzes the courses of devices using resource discovery and interaction technologies to identify some types of context related to reducing cost of service, then, chooses effective methods such as stopping broadcast and hibernation to reduce cost of service according to information supplied by the context but not the transhipment-method’s simple hibernations. The results of experiments indicate that under the worst condition this method overcomes the shortcomings of transhipment-method, makes the “poor” devices hibernate longer than hibernation-method to reduce cost of service more effectively, and discovers resources faster than hibernation-method; under the best condition it is far better than hibernation-method in all aspects.

A fuzzy immune algorithm and its application in solvent tower soft sensor modeling

An improved immune algorithm is proposed in this paper. The problems, such as convergence speed and optimization precision, existing in the basic immune algorithm are well addressed. Besides, a fuzzy adaptive method is presented by using the fuzzy system to realize the adaptive selection of two key parameters （possibility of crossover and mutation）. By comparing and analyzing the results of several benchmark functions, the performance of fuzzy immune algorithm （FIA） is approved. Not only the difficulty of parameters selection is relieved, but also the precision and stability are improved. At last, the FIA is ap- plied to optimization of the structure and parameters in radial basis function neural network （RBFNN） based on an orthogonal sequential method. And the availability of algorithm is proved by applying RBFNN in modeling in soft sensor of solvent tower.

Systematic review of feasibility and safety of laparoscopic gastrectomy for gastric cancer

Objective： The purpose of the present study was to retrospectively and systematically evaluate the feasibility and safety of laparoscopic gastrectomy for gastric cancer. Methods： Research of prospective, randomized, controlled studies addressing laparoscopic gastrectomy versus open gastrectomy was screened through computer-based online system. Meta-analysis of acquired data was performed. The inverse variance method was used to test the significance of continuous data, while the ManteI-Haenszel method was used for dichotomous data. The chi-square test was used for evaluation of data heterogeneity. Homogenous data were calculated using the fixed effect model, and heterogeneous data were calculated using freedom model. Statistical data were expressed as 95% confidence interval （95% CI）. Funnel plot was used for sensitivity analysis to show potential publication bias. Results： Five papers met the inclusion criteria, 164 cases underwent laparoscopic gastrectomy and 162 cases received open gastrectomy. Meta-analysis revealed that laparoscopic gastrectomy took longer operating time and removed fewer lymph nodes than open gastrectomy （both P 〈 0.01）, but for early-stage gastric cancer, laparoscopic gastrectomy was superior to open gastrectomy in terms of blood loss and hospital stay （P 〈 0.01）. But there were no significant differences in terms of time to resumption of oral intake, postoperative complications, postoperative morbidity rate, and tumor recurrence. Sensitive analysis demonstrated that publication bias existed in all indices to different extents with the exception of lymph node. Subgroup analysis showed that for D1 lymph node dissection, laparoscopic gastrectomy took significantly reduced blood loss than open gastrectomy. Conclusion： All these findings indicate that laparoscopic gastrectomy for early stage gastric cancer is feasible and safe.

A Real-time Modeling of Photovoltaic Array

This paper mainly aims at the modeling problem of the photovoltaic (PV) array with a 30 kW PV grid-connected generation system. An iterative method for the time-varying parameters is proposed to model a plant of PV array. The relationship of PV cell and PV array is obtained and the solution for PV array model is unique. The PV grid-connected generation system is used to demonstrate the effectiveness of the proposed method by comparing the calculated values with the actual output of the system.