A Transport Framework for Distributed Brokering Systems
C#高级编程《第7版》读书笔记(1-3章)
本文档是学习《C#高级编程》第七版的读书笔记，对于一些资源参考了网络相关文章。
本文档仅供个人学习，不可用于商业行为。
第Ⅰ部分部分 C#C#语言语言语言第一章第一章 .NET 体系结构1. 什么是 .NET Framework？2. C#语言和 .NET Framework 关系是什么？3. 什么是公共语言运行库？4. 什么是托管代码? 其与非托管代码有什么不同? 他们执行效率如何？5. IL 是什么？6. 什么是程序集？7. 值类型和引用类型的区别？答1：.NET Framework 是用于Windows 的新托管代码编程模型。
.NET Framework 又称 .Net 框架。
一个致力于敏捷软件开发（Agile software development Agile software developmentAgile software development）、快速应用开发（Rapid Rapid application developmentapplication development）、平台无关性和网络透明化的软件开发平台。
.NET 框架是以一种采用系统虚拟机运行的编程平台，以通用语言运行库（Common Language Runtime Common Language Runtime Common Language Runtime）为基础，支持多种语言（C#、VB、C++、Python 等）的开发。
答2：C#本身只是一种语言，尽管它是用于生成面向.NET 环境的代码，但它本身不是.net 的一部分。
.net 支持的一些特性，C#并不支持。
而C#语言支持的另一些特性，.net 却不支持。
但C#语言是和.NET 一起使用的，所以如果要使用C#高效地开发应用程序，理解Framework 就非常重要。
答3：.NET Framework 的核心是其运行库的执行环境， 称为公共语言运行库公共语言运行库 （CLR） 或 .NET 运行库。
Agent
Agent-Based Approaches to Transport LogisticsPaul Davidsson, Lawrence Henesey, Linda Ramstedt,Johanna Törnquist and Fredrik WernstedtAbstract.This paper provides a survey of existing research on agent-based approaches to transportation and traffic management. A framework for describing and assessing this work will be presented and systematically applied. We are mainly adopting a logistical perspective, thus focusing on freight transportation. However, when relevant, work of traffic and transport of people will be considered. A general conclusion from our study is that agent-based approaches seem very suitable for this domain, but that this still needs to be verified by more deployed system.1 IntroductionThe research area of agent technology continues to yield techniques, tools, and methods that have been applied or could be applied to the area of traffic and transportation management. The aim of this paper is to present a consistent view of the research efforts made in this area.We are mainly adopting a logistical perspective, thus focusing on transportation rather than traffic, and on freight rather than people. In particular, we will not survey the extensive work on agent-based modeling of driver and commuter behavior. Also we will not consider approaches to supply-chain management.In the next section, the areas where agent technology may be useful will be identified. We then present a framework that will be used to classify and assess the research in the area. This is followed by a systematic survey of the work found in the literature. Finally, we analyze our findings and present some conclusions.2 BackgroundThe development of distributed and heterogeneous systems, such as software for automation of, and decision support for logistics management, poses significant challenges for system developers. Agent technology [73], [75] aims to provide new concepts and abstractions to facilitate the design and implementation ofsystems of this kind. Parunak [51] lists the following characteristics for an ideal application of agent technology:- Modular, in the sense that each entity has a well-defined set of state variables that is distinct from those of its environment and that the interface to the environment can be clearly identified.- Decentralized, in the sense that the application can be decomposed into standalone software processes capable of performing useful tasks without continuous direction from some other software process.- Changeable, in the sense that the structure of the application may change quickly and frequently.- Ill-structured, in the sense that all information about the application is not available when the system is being designed.- Complex, in the sense that the system exhibits a large number of different behaviours which may interact in sophisticated ways.As most transport logistics applications actually fit Parunak’s characterisation rather well, this would suggest that agent technology indeed is a promising approach for this area. However, it is not suitable for all applications. For instance, in applications that are monolithic, centralized, static, well-structured, and simple, agent technology will probably not provide any added value, only unnecessary complexity.3. Evaluation frameworkFor each paper surveyed we describe the problem studied, the approach taken to solve it, and assess the results.3.1 Problem descriptionEach problem description includes the following three parts: the domain studied, the mode of transportation, and the time horizon considered.3.1.1 DOMAIN We have chosen to divide the problem descriptions into three domains: transport, traffic and terminal. A transport is an activity where something is moved between point A and B by one or several modes of transport. Problem areas that fall under the category transport are e.g. route planning, fleet management, different sorts of scheduling, functionalities that takes place to supporttransportation.While transport refer to the movement of cargo from one point to another, traffic refers to the flow of different transports within a network. One train set is thus a transport, or part of a transport, that takes part in the train traffic flow. Hence, a transport can be part of several traffic networks (air, waterborne, road, rail,) and a traffic network constitutes of several transports. Typical traffic activities are traffic flow scheduling such as railway slot allocation, air traffic management, and railway traffic management.Within for example a transport chain where the cargo is transported by truck, rail, ship and truck again, there are interfaces between the different modes. These interfaces represent nodes for re-loading and are referred to as terminals. Terminals can be any fixed place where the cargo is handled and require access to different kinds of resources. Typical terminal activities are resource allocation and scheduling of cranes, forklifts and parts of a facility.3.1.2 TRANSPORT MODE There are five basic modes of transportation: road, rail, air, water, and pipeline [64]. Although the use of pipelines often offers the cheapest method in transporting bulk fluids in long distances, we will in this paper not regard this modality.The water transport via sailing vessels offers one of the most used and less costlymeans of transporting bulk goods. The use of rail is often associated with bulk itemstransported less costly than road to far distant markets. The flexibility and ofteninevitable use of road for the beginning or final transport mode in a transportation chain makes this the most often used form of transport. Road transport is often associated with faster delivery in short distances and is attractive to shippers and customers that demand choice and flexibility in scheduling. Finally, air transport mode offers the fastest means of transport and usually the most expensive. This mode is usually reserved for highvalued goods that need to be transported across large distances. The use of air is also considered in short supply times, as in the case of disaster relief.All freight transport modes can include, for example, fleet management techniques, route and maintenance planning, on-board loading/unloading techniques and on-board computers. In all cases, the emphasis will be on the impact on organizational costs and service levels. Usually in freight logistics, transportation represents the most important single element in logistics costs for most firms [5].Transportation is a key decision area within logistics due to, on average, a higher percentage of logistics costs associated with this activity than any other logistics activity [5]. The selection of which mode of transport is to be used is dependent on several factors associated with the type of cargo/goods, e.g., requirements on speed, handling, costs, distance, flexibility etc.Intermodal transportation, refe rs to “movement of goods in one and the same loading unit or vehicle that uses successively several modes of transport without handling of the goods themselves in changing modes” according to the definition of The European Conference of Ministers of Transport [24]. The definition is valid also for personal travelling that includes two or more different modes of transportation.One of the primary challenges in intermodal transport management is to coordinate several inter-dependent activities within the transport as well as the communication between the multiple actors involved.3.1.3 TIME HORIZON Historically, the term logistics referred mainly to issues regarding technical and physical flows of products on an operational level. Today, the term includes both strategic and tactical issues beside the operational ones and includes the information flow connected to the physical flow. Therefore, the applications and concepts studied and presented are divided into levels of time perspective; strategic, tactical and operational level of decision-making. This is an established classification that is widely used. It can also be seen as a hierarchy in decision time [61]. We will here by time horizon refer to at what stage in the decision-making process the application is used, or is intended to be used. There are two dimensions often distinguished, the level of decision-making and its time frame. There is no definite line of separation,but strategic decision-making typically involves long-term decisions concerning determining what to do, while tactical deals with medium-term issues of setting up an action-list, and operational how to conduct the work set out in more specific terms, i.e. short term issues [61]. The time horizon for these levels is highly domain dependent.In this study we also include the execution of tasks and real-time controlling functionalities within the operational decision-making. For a transport operator, as an example, a strategic issue to address would be where to locate distribution centres, while a tactical issue would be to tailor the vehicle fleet to satisfy the customer demands, and the operational level would involve scheduling of each and every transport and the controlling function with monitoring and ad-hoc planning if necessary.As can be seen there is no established definition on time frame or content in the different planning hierarchy, and it is highly dependent on what type of business that is addressed.3.2 ApproachEach approach is described by the following three parts: the intended usage of the agent system, the type of agents used, and the type of coordination chosen.3.2.1 USAGE The applications studied can be classified, according to this paper, as either to serve as an automation system, or a decision-support system. An automation system can be defined as “having a self-acting mechanism that performs a required act at a predetermined time or in response to certain conditions” [46]. In this context it refers to a system’s ability to act upon its decisions, i.e. it has a direct influence on the controlled environment and there is no human involved. On the contrary, a decisionsupport system, DSS, has only at most an indirect impact on the decision-making. A DSS is a system that provides output of some specified type to support the decision process for the user. The user, i.e. the decision-maker, takes the suggested decision(s) into consideration, and then acts. Thus, the final decision is made by a person, not the software system.3.2.3 COORDINATION (CONTROL, STRUCTURE AND ATTITUDE) Researchers in many fieldsincluding computer science, economy, and psychology have studied the area of coordination, which can be viewed as “managing the interdependencies among activities” [45]. In any environment where software agents participate, the agents need to engage in cooperative and/or competitive tasks to effectively achieve their design objectives. From the multi-agent systems perspective coordination is a process in which agents engage in order to ensure that a community of individual agents acts in a coherent manner [48]. Coordination techniques are classified here according to the three dimensions control, structure and attitude.We capture the authority relationships between agents in the dimension of control, which is either centralized or distributed (decentralized). The MAS structure corresponds to the set of agents constituting the MAS, their roles, and the communication paths between agents. The structure is either predetermined, i.e., static (the set of agents or their roles do not change during the execution), or is changing dynamically. Finally, the agent attitude dimension captures the behavior of agents, which is classified as either benevolent (cooperative), i.e., they will comply with social laws and global goals, or selfish (comp etitive), where the agents’ individual goals, e.g.,ina market-based economy, will govern their behavior.3.3 ResultsThe main classification of the result of the approaches will be in terms of maturity of the research. However, we will also try to assess the performance and the limitations of the approaches.3.3.1 MATURITY Agent applications can have varying degree of maturity, i.e., how complete and validated an application is. According to Parunak [52], the description of the maturity of an agent application helps the users to assess how much work that remains to carry out the implementation of the agent application. Furthermore, Parunak has suggested a number of degrees of maturity which formed the basis for our refined classification.The lowest degree of maturity in the classification is conceptual proposal. Here the idea or the principles of the proposed application is described withits general characteristics, e.g. if the model is simple or complex. In the literature the term conceptual model is quite well-established and well-defined. However, we prefer the more open term conceptual proposal since it otherwise could be more difficult to fit in all applications according to the classification.The next level in the classification is simulation experiments. Here the application has been tested in a simulation environment. The data used in the simulated experiment can either be real data, i.e. taken from existing systems in the real world, or data that is not real, i.e. artificial, synthetic or generated. Further, the type of data has been divided into limited/partial or full-scale data. The full-scale data represents data for a whole system, while the limited/partial data only covers parts of the system.Field experiment indicates that experiment with the application has been conducted in the environment where the application is supposed to be applied. As in the simulated experiment, the field experiment is also divided into limited/partial and fullscale. The final level, deployed system, indicates that the system has been implemented in the real world and also has been or is in use. This is the most mature type of agent applications.3.3.2 EVALUATION COMPARISON If a new approach is developed to solve a problem which has been solved previously using other approaches, the new approach should be compared to those existing approaches. Such an evaluation could be either qualitative, by comparing the characteristics of the approaches, or quantitative, by different types of experiments.基于代理的物流运输途径摘要：这篇论文提供了基于代理的，现有的关于运输和交通管理的研究调查为基础的方法。
大数据开发工程师招聘笔试题与参考答案(某大型国企)2024年
2024年招聘大数据开发工程师笔试题与参考答案(某大型国企)(答案在后面)一、单项选择题（本大题有10小题，每小题2分，共20分）1、以下哪个技术栈是大数据开发工程师常用的核心技术栈之一？A、Java + Hadoop + SparkB、Python + Pandas + NumPyC、C++ + Redis + KafkaD、JavaScript + React + Node.js2、在大数据生态中，以下哪个组件用于实现数据仓库的构建？A、HiveB、HBaseC、ElasticsearchD、Kafka3、某大型国企在进行数据仓库设计时，需要考虑数据仓库的以下哪些特点？（多选）A、数据仓库是面向主题的B、数据仓库是集成的C、数据仓库是非易失的D、数据仓库是实时更新的4、在数据仓库的ETL（Extract, Transform, Load）过程中，以下哪个步骤属于数据转换阶段？（单选）A、数据抽取B、数据清洗C、数据加载D、数据映射5、在以下关于Hadoop的描述中，哪项是错误的？A、Hadoop是一个开源的分布式计算框架，用于处理大规模数据集。
B、Hadoop使用MapReduce编程模型来处理数据。
C、Hadoop的存储系统是HDFS（Hadoop Distributed File System），它不保证数据的原子性。
D、Hadoop的主要组件包括HDFS、MapReduce、YARN和ZooKeeper。
6、以下哪个不是Spark的组件？A、Spark SQLB、Spark StreamingC、Spark MLlibD、Hadoop YARN7、某大型国企的数据仓库中包含了一个用户行为数据表，该表记录了用户在平台上的浏览、购买等行为。
以下关于该数据表的说法，正确的是：A、该数据表应该是时序数据库，因为记录了用户的行为时间序列。
B、该数据表应该是文档数据库，因为存储了用户的具体行为描述。
Refereed Journal Articles
Sam MalekGraduate Research Assistant Immigration Status: U.S. CitizenSoftware Architecture Research Group Center for Systems and Software Engineering Computer Science DepartmentViterbi School of EngineeringUniversity of Southern California E-mail: malek@WWW: /~malek/ Address: 26242 Palmetto PlaceMission Viejo, CA, 92692, U.S.A Phone: +1 (949) 357-3501EducationDoctor of Philosophy Computer Science May 2007 University of Southern California GPA 3.9 Dissertation Title: A User-Centric Approach for Improving a Distributed SoftwareSystem’sDeploymentArchitectureAdvisor: Nenad MedvidovicDissertation Committee Members: Barry Boehm (USC CS), Sandeep Gupta (USC EE)Gaurav Sukhatme (USC CS), and Richard Taylor (UC Irvine) Master of Science Computer Science May 2004 University of Southern California GPA 3.9 Emphasis on Software EngineeringBachelor of Science Information and Computer Science December 2000 University of California Irvine GPA 3.9Research Interests•Software architecture and design•Architecture-based software development and deployment•Software engineering for embedded and distributed systems•Quality of service analysis and improvement•Middleware solutionsHonors and Awards•USC CS Department Outstanding Graduate Student Researcher Award 2005•USC Viterbi School of Engineering Fellowship 2004-2008•SIGSOFT CAPS Travel Scholarship to present at 14th ACM Symposium on Foundations of Software Engineering (FSE 2006), Portland, Oregon•Magna Cum Laude 2000•Cody Thorne Memorial Scholarship Award for the Youngest and Highest Scholastic Student of the Year 1998-1999•1997-2000 Dean’s Honor ListPublicationsRefereed Journal ArticlesJ1. Sam Malek, Marija Mikic-Rakic, and Nenad Medvidovic. “A Style-Aware Architectural Middleware for Resource-Constrained, Distributed Systems.” IEEETransactions on Software Engineering, vol. 31, no. 3, pages 256-272, March 2005.J2. Nenad Medvidovic, Marija Mikic-Rakic, Nikunj Mehta, and Sam Malek.“Software Architectural Support for Handheld Computing.” IEEE Computer –Special Issue on Handheld Computing, vol. 36, no. 9, pages 66-73, September2003. Acceptance rate 5 of 87 (5.7%)Under PreparationJ3. Sam Malek, Nenad Medvidovic, Chiyoung Seo, and Marija Mikic-Rakic. “A User-Centric Approach for Improving a Distributed Software System’s DeploymentArchitecture.” To be submitted to IEEE Transactions on Software Engineering.Book ChaptersB1. Sam Malek, Nels Beckman, Marija Mikic-Rakic, and Nenad Medvidovic. “A Framework for Ensuring and Improving Dependability in Highly DistributedSystems.” In R. de Lemos, C. Gacek, and A. Romanowski, eds., ArchitectingDependable Systems III, Springer Verlag, October 2005.Refereed Conference and Workshop ProceedingsC1. Sam Malek, Chiyoung Seo, Sharmila Ravula, Brad Petrus, and Nenad Medvidovic.“Reconceptualizing a Family of Heterogeneous Embedded Systems via ExplicitArchitectural Support.” In proceedings of the29th International Conference onSoftware Engineering (ICSE 2007), Minneapolis, Minnesota, May 2007.C2. Chiyoung Seo, Sam Malek, George Edwards, Nenad Medvidovic, Brad Petrus, and Sharmila Ravula. “Exploring the Role of Software Architecture in Dynamic andFault Tolerant Pervasive Systems.” In proceedings of the Workshop on SoftwareEngineering of Pervasive Computing Applications, Systems and Environments(SEPCASE 07), Minneapolis, MN, May 2007.C3. George Edwards, Sam Malek, and Nenad Medvidovic. “Scenario-Driven Dynamic Analysis of Distributed Architectures.” In proceedings of the 10th InternationalConference on Fundamental Approaches to Software Engineering (FASE 2007),Braga, Portugal, March 2007.C4. Sam Malek. “A User-Centric Framework for Improving a Distributed Software System's Deployment Architecture.” In proceedings of the doctoral track at the14th ACM SIGSOFT Symposium on Foundation of Software Engineering (FSE2006), Portland, Oregon, November 2006.C5. Sam Malek, Chiyoung Seo, and Nenad Medvidovic. “Tailoring an Architectural Middleware Platform to a Heterogeneous Embedded Environment.” In proceedingsof the 6th International Workshop on Software Engineering and Middleware (SEM2006), Portland, Oregon, November 2006.C6. Sam Malek, Chiyoung Seo, Sharmila Ravula, Brad Petrus, and Nenad Medvidovic.“Providing Middleware-Level Facilities to Support Architecture-Based Development of Software Systems in Pervasive Environments.” In proceedings of the 4th International Workshop on Middleware for Pervasive and Ad-Hoc Computing (MPAC 2006), Melbourne, Australia, November 2006.C7. Sam Malek, Marija Mikic-Rakic, and Nenad Medvidovic. “A Decentralized Redeployment Algorithm for Improving the Availability of Distributed Systems.”In proceedings of the 3rd International Conference on Component Deployment (CD 2005), Grenoble, France, November 2005.C8. Marija Mikic-Rakic, Sam Malek, and Nenad Medvidovic. “Improving Availability in Large, Distributed, Component-Based Systems via Redeployment.” Inproceedings of the3rd International Conference on Component Deployment (CD2005), Grenoble, France, November 2005.C9. Christian Mattmann, Sam Malek, Nels Beckman, Marija Mikic-Rakic, Nenad Medvidovic, and Daniel Crichton. “GLIDE: A Grid-based LightweightInfrastructure for Data-intensive Environments.” In proceedings of the EuropeanGrid Conference (EGC 2005), Amsterdam, Netherlands, February 2005.C10. Sam Malek, Marija Mikic-Rakic, Nenad Medvidovic. “An Extensible Framework for Autonomic Analysis and Improvement of Distributed DeploymentArchitectures.” In proceedings of the ACM SISGSOFT Workshop on Self-ManagedSystems (WOSS 2004), Newport Beach, California, October 2004.C11. Marija Mikic-Rakic, Sam Malek, Nels Beckman, and Nenad Medvidovic. “A Tailorable Environment for Assessing the Quality of Deployment Architectures inHighly Distributed Settings.” In proceedings of the2nd International Conference on Component Deployment (CD 2004), Edinburgh, Scotland, May 2004.C12. Marija Mikic-Rakic, Sam Malek, Nels Beckman, and Nenad Medvidovic.“Improving Availability of Distributed Event-Based Systems via Run-TimeMonitoring and Analysis.” In proceedings of the Twin Workshop on ArchitectingDependable Systems (WADS 2004), Edinburgh, UK, May 2004, and Florence,Italy, June 2004.C13. Nenad Medvidovic, Sam Malek, and Marija Mikic-Rakic. “Software Architectures and Embedded Systems.” In proceedings of the Monterey Workshop on SoftwareEngineering for Embedded Systems, Chicago, Illinois, September 24-26, 2003.Under SubmissionC14. Chiyoung Seo, Sam Malek, and Nenad Medvidovic. “An Energy Consumption Framework for Distributed Java-Based Systems.” Available as a technical reportUSC-CSE-2006-604.Academic Research ExperienceUniversity of Southern California January 2003 – April 2005, June 2006 – presentGraduate Research Assistant•Participated in a number of research projects supported by NSF, Jet PropulsionLaboratory, Boeing, and Bosch Research and Technology Center•Developed a style-aware architectural middleware, called Prism-MW. Optimized andenhanced the middleware to execute in embedded and resource-constrainedenvironments. This effort was sponsored by research funding from NSF and Bosch.•Developed and maintained a deployment modeling and analysis tool, called DeSi.This effort was sponsored by NSF, Jet Propulsion Lab, Boeing, and Bosch.•Ported Java version of Prism-MW to C++ and adapted it to execute on top of Bosch’ssensor-network hardware platforms. Integrated the original implementation of DeSiwith Prism-MW to provide support for deployment and analysis of Bosch’s sensor-network applications. This effort was sponsored by Bosch.Academic Teaching Experience•Teaching Assistant Fall 2003University of Southern CaliforniaCS 589 – Software Engineering for Embedded Systems (Graduate-level)Syllabus available at: /classes/cs589_2003/•Guest Lecturer Fall 2004, Fall 2006University of Southern CaliforniaCS 589 – Software Engineering for Embedded Systems (Graduate-level)2006 •Guest Lecturer Fall University of Southern CaliforniaCS 377 – Introduction to Software EngineeringIndustrial ExperienceBoeing April 2005 – present; on leave of absence since June 2006Software Architect•Participated in the US Army’s Future Combat Systems project – the largest eversystem of systems integration and development effort attempted by the US Army•Modeled various aspects of the system’s software architecture•Analyzed the models to determine the architectural “gaps” and issues•Resolved the issues and gaps by collaborating with the other software architects andvendors•Leveraged tools such as Generic Modeling Environment, Rational Rose, Matlab, andAsynchronous Discrete Event Simulator to analyze and ensure the architecture’sability to meet its non-functional requirementsIBM December2000 – May 2002 Software Engineer•Gained experience in a variety of technologies through internal training and projects •As a team member of a project for the biggest utility company on the U.S. West Coast, I was responsible for the design and coding of several EAI (enterpriseapplication integration) interfaces. The final result was a systematic method ofmessaging and real-time communication between the client's non-compatible Webservers, SAP systems, Siebel systems and Oracle DBs. Used SeeBeyond EGate 4.1and coded in MONK (a proprietary language of SeeBeyond technologies) toimplement the system.•As a team member of a 3-tier e-commerce project for a retail company, I was responsible for the code and configuration of several J2EE Servlets and EJBs thatprovided the backbone of the Web site. BEA Weblogic was used as the developmentplatform.FieldCentrix August 1999 – November 2000 Software Engineer•Applied principles of software engineering to the development of applications running on hand-held PCs•Modularized software systems by creating DLLs and separating similar features into separate packages•Used mostly VC++ and some VBNeural Computing Systems Labs May 1998 – September 1999 Software Engineer•Designed and developed GUIs for the data mining tools using VC++ and MFC•Developed an internal database for the company using MS SQL Server in VC++•Enhanced the encryption and security of an off-the-shelf data mining software package using unique encryption algorithmsFormal Presentations• A User-Centric Framework for Improving a Distributed Software System’s Deployment Architecture. Doctoral track of the Symposium on Foundations ofSoftware Engineering (FSE 2006), Portland, Oregon, November 2006.•Tailoring an Architectural Middleware Platform to a Heterogeneous Embedded Environment. International Workshop on Software Engineering and Middleware(SEM 2006), Portland, Oregon, November 2006.• A Decentralized Redeployment Algorithm for Improving the Availability of Distributed Systems. International Conference on Component Deployment (CD2005), Grenoble, France, November 2005•Improving Availability in Large, Distributed, Component-Based Systems via Redeployment. International Conference on Component Deployment (CD 2005),Grenoble, France, November 2005• A User-Centric Approach for Improving a Distributed Software System’s Deployment Architecture. USC Center for Software Engineering Annual Research Review, LosAngeles, California, March 2005•An Extensible Framework for Autonomic Analysis and Improvement of Distributed Deployment Architectures. ACM SISGSOFT Workshop on Self-Managed Systems(WOSS 2004), Newport Beach, California, October 2004• A Tailorable Environment for Assessing the Quality of Deployment Architectures in Highly Distributed Settings. Second International Conference on ComponentDeployment (CD 2004), Edinburgh, Scotland, May 2004•Improving Availability of Distributed Event-Based Systems via Run-Time Monitoring and Analysis. Workshop on Architecting Dependable Systems (WADS 2004) held inconjunction with the International Conference on Software Engineering (ICSE 2004),Edinburgh, Scotland, May 2004•Improving System Availability in Distributed Environments. USC Center for Software Engineering Annual Research Review, Los Angeles, CA, March 2004 Professional Activities•Reviewer, IEEE Software, 2006•Committee member of the 2006 International Conference on Software Engineering Research and Practice (SERP'06), Las Vegas, Nevada, June 2006•External reviewer for the 2007 International Working Conference on Software Architecture (WICSA 2007), Mumbai, India, 2007•External reviewer for the International Symposium on Component-based Software Engineering (CBSE 2006), Vasteras, Sweden, June 2006•Reviewer for the 39th Hawaiian International Conference on System Sciences, Kauai, Hawaii, January 2006•Committee member of the 2005 ISR Graduate Student Research Symposium, Irvine, California, June 2005•External reviewer for the 3rd International Working Conference on Component Deployment, Grenoble, France, November 2005•External reviewer for the 5th International Workshop on Software Engineering and Middleware, Lisbon, Portugal, September 2005•External reviewer for the 8th International Symposium on Component-based Software Engineering, St. Louis, Missouri, May 2005•External reviewer for the International Symposium on Component-based Software Engineering, Edinburgh, Scotland, May 2004•External reviewer for the Twin Workshops on Architecting Dependable Systems (WADS), Edinburgh, Scotland, May 2004•External reviewer for the ACM SISGSOFT Workshop on Self-Managed Systems (WOSS), Newport Beach, California, October 2004Professional Associations•Association for Computing Machinery (ACM)•ACM Special Interest Group on Software Engineering (SIGSOFT) ReferencesNenad MedvidovicAssociate Professor, University of Southern CaliforniaE-mail: neno@WWW: /~neno/Barry BoehmProfessor, University of Southern CaliforniaE-mail: boehm@WWW: /Research_Group/barry.htmlSandeep GuptaProfessor, University of Southern CaliforniaE-mail: sandeep@WWW: /sandeep/Richard TaylorProfessor, University of California, IrvineE-mail: taylor@WWW: /~taylor/Roshanak RoshandelAssistant Professor, Seattle UniversityE-mail: roshanak@WWW:/roshanak/web/。
yap-5sa原理
yap-5sa原理English Answer:The YAP-5SA principle is a framework for designing distributed systems that are resilient to network failures. It is based on the idea of using a quorum of nodes to make decisions, which ensures that the system can continue to operate even if some nodes are unavailable.The YAP-5SA principle is named after its five authors: Diego Ongaro, John Ousterhout, Eric Brewer, Andrew Bainbridge, and Jefferey H. Lorch. The paper describing the principle was published in the Proceedings of the 25th ACM Symposium on Operating Systems Principles (SOSP) in 2013.The YAP-5SA principle is based on the following five principles:1. Use a quorum of nodes to make decisions. This ensures that the system can continue to operate even ifsome nodes are unavailable.2. Use a read quorum to read data. This ensures thatthe data will be consistent even if some nodes are unavailable.3. Use a write quorum to write data. This ensures that the data will be durable even if some nodes are unavailable.4. Use a majority of nodes to make decisions. This ensures that the system will be able to tolerate up to half of its nodes failing.5. Use a synchronous protocol to communicate between nodes. This ensures that the system will be able totolerate network failures.The YAP-5SA principle has been used to design a numberof distributed systems, including the Google Spanner database and the Apache Cassandra database. These systems have proven to be highly resilient to network failures, making them ideal for applications that require highavailability.中文回答：YAP-5SA 原理是一个设计分布式系统的框架，该系统对网络故障具有弹性。
德国工业4.0原版
Intense research activities in universities and other research institutions Drastically increasing number of publications in recent years Large amount of funding by the German government
Model predictive control (MPC)
Modern, optimization-based control technique Successful applications in many industrial fields Can handle hard constraints on states and inputs Optimization of some performance criterion Applicable to nonlinear, MIMO systems
A system is strictly dissipative on a set W ⊆ Z with respect to the supply rate s if there exists a storage function λ such that for all (x , u ) ∈ W it holds that λ(f (x , u )) − λ(x ) ≤ s (x , u ) − ρ(x ) with ρ > 0.
k =0 x (k |t + 1) x (t + 1) state x input u t+1 u (k |t + 1) k =N
Basic MPC scheme
rfc3164
Network Working Group Request for Comments: 3164 Category: Informational
C. Lonvick Cisco Systems August 2001
Network Security Map
/securitymap. html
[ Page ]
The BSD syslog Protocol
August 2001
Status of this Memo
This memo provides information for the Internet community. It does not specify an Internet standard of any kind. Distribution of this memo is unlimited.
/colorcardscanner.html
Portable Document Scanner
/portablescanner.html
workdictionary. com
[ Page ]
The BSD syslog Protocol
August 2001
Table of Contents
1. Introduction..................................................................................................2 1.1 Events and Generated Messages........................................................3 1.2 Operations of the Me
cap模型 案例
cap模型案例The CAP model, which stands for Consistency, Availability, and Partition tolerance, is a theoretical framework used to analyze the trade-offs in distributed systems. CAP理论是对分布式系统中一致性，可用性和分区容忍性的抽象描述。
它指导着我们在设计和部署分布式系统时需要做出的折衷选择。
Consistency refers to the guarantee that all nodes in a distributed system have the same view of the data at any given time. In other words, when a client updates data in the system, all nodes should eventually see that update. However, achieving strong consistency in a distributed system can lead to increased latency and reduced availability. 一致性指的是分布式系统中所有节点在任何给定时间都对数据有相同的视图。
换句话说，当客户端更新系统中的数据时，所有节点最终都应该看到该更新。
然而，在分布式系统中实现强一致性可能会导致增加的延迟和降低的可用性。
Availability refers to the ability of a distributed system to continue operating and serving requests even in the presence of node failures. It ensures that clients can still access the system and its data even ifsome nodes are offline. Achieving high availability often involves replicating data and services across multiple nodes to provide redundancy. 可用性指的是分布式系统在节点发生故障时仍能继续运行并提供服务的能力。
- 1、下载文档前请自行甄别文档内容的完整性，平台不提供额外的编辑、内容补充、找答案等附加服务。
- 2、"仅部分预览"的文档,不可在线预览部分如存在完整性等问题,可反馈申请退款(可完整预览的文档不适用该条件!)。
- 3、如文档侵犯您的权益，请联系客服反馈,我们会尽快为您处理(人工客服工作时间：9:00-18:30)。
are suited for different tasks. Multicast works best within a domain where there is a high concentration of clients, most of which are interested in those events. TCP works best where reliable delivery is at a premium. UDP works best for applications that can sustain losses in delivery to clients but cannot afford the premiums – associated with error correction and out of delivery in TCP – that can lead to increased latencies.
enough to abstract the communication requirements for most service protocol layers. At the same time, the interfaces should ensure that they are general enough over multiple transports, while not incorporating details pertaining to a specific transport into the framework. 2. Easy extensibility: An ability to incorporate support for new protocols easily. Each implementation of the interfaces might include support for any handshaking protocols that might be necough communications between two nodes in the fabric would be over a specific transport protocol, there might be
A Transport Framework for Distributed Brokering Systems
Shrideep Pallickara1, Geoffrey Fox1, John Yin2, Gurhan Gunduz1,3, Hongbin Liu1, Ahmet Uyar1,3 , Mustafa Varank1
In this paper we suggest that the problem is an important one, and that, a transport framework needs to be incorporated into the messaging infrastructure hosting the services. We may enumerate the issues that need to be addressed within any transport framework designed for distributed brokering systems. These include – 1. Framework Design: Interfaces need to be general
Keywords: transport frameworks, distributed brokering, network monitoring, adaptive systems, messaging middleware.
1. Introduction
Recent years have seen an increase in the number of devices with differing communication, compute and display capabilities. Increasingly, services need to interact with a wide spectrum of devices with varying networking capabilities. In most cases, services and the functions that they perform are independent of the transports deployed for communications. Furthermore, given the scale and the variety of devices that services need to interact with, services are usually hosted on a distributed messaging infrastructure. It is thus entirely conceivable that a message would traverse multiple hops (possibly over different underlying transports) en route to its final destinations.
(ggunduz,auyar}@,
Abstract
Increasingly, services need to interact with a wide spectrum of devices with varying networking capabilities. Services hosted on a messaging infrastructure need to optimally utilize and exploit the conditions that exist within the local networks. The messaging infrastructure must manage the communication between external resources, services and clients to achieve the highest possible system performance and reliability. In this paper we suggest that a transport framework needs to be incorporated into the messaging infrastructure hosting the services. We base our investigations in the context of the NaradaBrokering system.
Services hosted on a messaging infrastructure need to optimally utilize and exploit the conditions that exist within the local networks. Different transport protocols
applications for which communications over that transport protocol might be unacceptable. The transport interfaces need to incorporate support for this need. Performance Monitoring: The ability to incorporate support for measuring network performance over communication links. Performance monitoring is generally the pre-cursor to any remedial measures that might be deployed to assuage network conditions. 4. Migration Support: A lot of times the underlying transport of a communication link might become unsuitable for continued communications under certain network conditions. Links should thus be able to deploy other transports for communications. Link creators specify the conditions under which these migrations should take place. 5. Negotiation of best transports: Two nodes should be able to negotiate the best transport for communications. Finally, a truly dynamic system would allow for adaptability in communications by responding to the changing network conditions. Though self-sustaining, responsive and self-healing systems are not within the scope of this paper, the underpinnings for such systems exist in those systems that provide a flexible transport framework, addressing the issues enumerated above. There are also two other issues, which implementations of these transport interfaces need to address. First, it is inevitable that the realms, over which the nodes try to establish communication links, would be protected by firewalls that would halt application channels dead in their tracks. The messaging infrastructure should thus be able to communicate across firewall, DHCP and NAT boundaries. Sometimes communications would also be through authenticating proxies. Second, and more subtly, there are cases where the transport interfaces themselves would be used to process data received and routed from and to specialized applications. Implementations of transport interfaces would themselves be used to incorporate support for legacy applications, without the need to incorporate complicate logic in the higher layers at a given node. A similar strategy has been used by us to incorporate support for audio/video conferencing while interfacing with legacy clients. Work is also underway on a specialized implementation of the interfaces to incorporate support for PDA device. Note that data preprocessing is done over the transport interfaces. In this paper, we address these issues in the context of our advanced research prototype, NaradaBrokering [1-7]. This paper is organized as follows. Section 2 provides an overview of the related work. In section 3 we provide an overview of the NaradaBrokering system, we then proceed to outline the transport framework in section 4.