Cloud Computing - grid+asia+HP+sept16

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HP刀片：Oracle网格计算的最优平台

ＨＰ刀片是Ｏｒｃｅ阕格的ａｌ理想架构
０ａｌ格计算解决方案ｒｃｅ于Ｏｒｃｅｇ产品包实现，主要ａ１ｌ０包括Ｏｒｃｅ］ｇ卡ＯｒｃｅＲＡＣ，这ａｌ０ｕａｌ些方一－ｚＯｒｃｅ数据库能够将￣１＂１．导ａ１
也实现了简化。
ＨＰ拥有完整的刀片服务器战略和产线，既有支持２路或４路的ＰｒＬｉｎｏａｔ刀片服务器，也有采
用安腾芯片的Ｉｔｇｉｙ片系统，ｎｅｒｔ
务器，
为这些服务器捉供了
ｐ刀片国 ④
Ｏｒａｃｌｅ网格计算的最优平台
网格汁算可以｝Ｔ环境增强卜Ｉ
阚格计算环境需求，成为部署
Ｏｒｃｅ网格计算的最佳选择ａ１
险，缩短Ｉ报时问，实现Ｉ投资旦ＪＴ
回报最人化。
企业应用运行在服务器集群之上，从而提供良好的性能币Ｊ展性。ｕ ‘ ｕ扩
为了充分发挥Ｏｒｃｅａ１ＲＡＣ的效
客户既可以选择广泛采，的英特｝｝｛
尔至强处理器，也以选用ＡＭＤ处理器。同时，ＨＰ针对客户的不
０ｃｅ数据库或应用服务器所需ｒ１ａ
要的ＩＯ连接能力和内存容量，并／支持Ｌｉｕｎｘ或Ｗｉｄｗｓ作系统，ｎｏ操为Ｏｒｃｅ１ｇ和ＲＡＣ集群提供了ａｌ０非常灵活的计算引擎。ＨＰ实现ｒ

边缘云协同术语

边缘云协同术语"边缘云协同"是一个涉及边缘计算（Edge Computing）和云计算（Cloud Computing）的领域，具有以下相关术语和概念：* 边缘计算（Edge Computing）：边缘计算是一种分布式计算范式，将计算资源和数据存储推近到数据生成的源头，减少数据传输和延迟。

在边缘云协同中，边缘计算起到了至关重要的作用，使得处理和分析数据的能力更加灵活高效。

* 云计算（Cloud Computing）：云计算是通过网络提供计算服务、存储服务、数据库服务等的一种技术。

在边缘云协同中，云计算通常指的是中心云（Central Cloud），它与边缘计算协同工作，实现分布式的计算和存储。

* 边缘云（Edge Cloud）：边缘云是指在离用户更近的位置提供云计算服务的一种架构。

它通常位于网络边缘，与中心云一同为用户提供服务，降低了数据传输的时延。

* 协同计算（Cooperative Computing）：边缘云协同强调了边缘计算和中心云之间的协同工作。

协同计算指的是不同计算节点之间相互合作，共同完成任务，以提高整体的计算能力和效率。

* 边缘设备（Edge Devices）：边缘设备是指在边缘计算中负责数据生成和处理的终端设备，如传感器、摄像头、智能手机等。

这些设备与边缘云和中心云之间形成一个端到云的计算体系。

* 边缘智能（Edge Intelligence）：边缘智能是指在边缘计算中集成智能化和机器学习的能力，使得边缘设备能够更智能地处理和分析数据，减轻中心云的负担。

* 边缘感知（Edge Sensing）：边缘感知是指边缘设备对周围环境的感知和数据采集能力，为边缘计算提供实时、精确的数据。

边缘云协同的概念旨在实现更加高效、响应迅速的计算体系，特别适用于需要低时延和大规模数据处理的应用场景，如物联网、智能城市、工业自动化等。

Cloud-Computing-(英文PPT)(共50张)

200+ clusters
Filesystem clusters of up to 5000+ machines Pools of 10000+ clients 5+ Petabyte Filesystems
All in the presence of frequent HW failure
Utility Computing
Don’t buy computers, lease computing power Upload, run, download Ownership model
第ep: Cloud Computing
Service and data are in the cloud, accessible with any
第2页，共50页。
Evolution of Computing with Network (2/2)
Grid Computing
Resource sharing across several domains
Decentralized, open standards
Global resource sharing
第5页，共50页。
Applications on the Web
The Cloud
第6页，共50页。
Cloud Computing
Definition
Cloud computing is a concept of using the internet to allow people to access technology-enabled services.
device connected to the cloud with a browser A key technical issue for developer:

云计算Cloud Computing-外文翻译

毕业设计说明书英文文献及中文翻译学生姓名：学号：计算机与控制工程学院：专指导教师：2017 年 6 月英文文献Cloud Computing1. Cloud Computing at a Higher LevelIn many ways, cloud computing is simply a metaphor for the Internet, the increasing movement of compute and data resources onto the Web. But there’s a difference: cloud computing represents a new tipping point for the value of network computing. It delivers higher efficiency, massive scalability, and faster, easier software development. It’s about new programming models, new IT infrastructure, and the enabling of new business models.For those developers and enterprises who want to embrace cloud computing, Sun is developing critical technologies to deliver enterprise scale and systemic qualities to this new paradigm:(1) Interoperability — while most current clouds offer closed platforms and vendor lock-in, developers clamor for interoperability. Sun’s open-source product strategy and Java™ principles are focused on providing interoperability for large-scale computing resources. Think of the existing cloud “islands” merging into a new, interoperable “Intercloud” where applications can be moved to and operate across multiple platforms.(2) High-density horizontal computing —Sun is pioneering high-power-density compute-node architectures and extreme-scale Infiniband fabrics as part of our top-tier HPC deployments. This high-density technology is being incorporated into our large-scale cloud designs.(3)Data in the cloud —More than just compute utilities, cloud computing is increasingly about petascale data. Sun’s Open Storage products offer hybrid data servers with unprecedented efficiency and performance for the emerging data-intensive computing applications that will become a key part of the cloud.These technology bets are focused on driving more efficient large-scale cloud deployments that can provide the infrastructure for next-generation business opportunities: social networks, algorithmic trading, continuous risk analysis, and so on.2. Why Cloud Computing?(1)Clouds: Much More Than Cheap ComputingCloud computing brings a new level of efficiency and economy to delivering IT resources on demand — and in the process it opens up new business models and market opportunities.While many people think of current cloud computing offerings as purely “pay by the drink” compute platforms, they’re really a convergence of two major interdependent IT trends:IT Efficiency —Minimize costs where companies are converting their IT costs from capital expenses to operating expenses through technologies such as virtualization. Cloud computing begins as a way to improve infrastructure resource deployment and utilization, but fully exploiting this infrastructure eventually leads to a new application development model.Business Agility —Maximize return using IT as a competitive weapon through rapid time to market, integrated application stacks, instant machine image deployment, and petascale parallel programming. Cloud computing is embraced as a critical way to revolutionize time to service. But inevitably these services must be built on equally innovative rapid-deployment-infrastructure models.To be sure, these trends have existed in the IT industry for years. However, the recent emergence of massive network bandwidth and virtualization technologies has enabled this transformation to a new services-oriented infrastructure.Cloud computing enables IT organizations to increase hardware utilization rates dramatically, and to scale up to massive capacities in an instant — without constantly having to invest in new infrastructure, train new personnel, or license new software. It also creates new opportunities to build a better breed of network services, in less time, for less money.IT Efficiency on a Whole New ScaleCloud computing is all about efficiency. It provides a way to deploy and access everything from single systems to huge amounts of IT resources — on demand, in realtime, at an affordable cost. It makes high-performance compute and high-capacity storage available to anyone with a credit card. And since the best cloud strategies build on concepts and tools that developers already know, clouds also have the potential to redefine the relationship between information technology and the developers and business units that depend on it.Reduce capital expenditures — Cloud computing makes it possible for companies to convert IT costs from capital expense to operating expense through technologies such as virtualization.Cut the cost of running a datacenter — Cloud computing improves infrastructure utilization rates and streamlines resource management. For example, clouds allow for self-service provisioning through APIs, bringing a higher level of automation to the datacenter and reducing management costs.Eliminate over provisioning —Cloud computing provides scaling on demand, which, when combined with utility pricing, removes the need to overprovision to meet demand. With cloud computing, companies can scale up to massive capacities in an instant.For those who think cloud computing is just fluff, take a closer look at the cloud offerings that are already available. Major Internet providers , Google, and others are leveraging their infrastructure investments and “sharing” their large-scale economics. Already the bandwidth used by Amazon Web Services (AWS) exceeds that associated with their core e-tailing services. Forward-looking enterprises of all types —from Web 2.0 startups to global enterprises — are embracing cloud computing to reduce infrastructure costs.Faster, More Flexible ProgrammingCloud computing isn’t only about hardware —it’s also a programming revolution. Agile, easy-to-access, lightweight Web protocols — coupled with pervasive horizontally scaled architecture — can accelerate development cycles and time to market with new applications and services. New business functions are now just a script away.Accelerated cycles — The cloud computing model provides a faster, more efficientway to develop the new generation of applications and services. Faster development and testing cycles means businesses can accomplish in hours what used to take days, weeks, or months.Increase agility —Cloud computing accommodates change like no other model. For example, Animoto Productions, makers of a mashup tool that creates video from images and music, used cloud computing to scale up from 50 servers to 3,500 in just three days. Cloud computing can also provide a wider selection of more lightweight and agile development tools, simplifying and speeding up the development process.The immediate impact will be unprecedented flexibility in service creation and accelerated development cycles. But at the same time, development flexibility could become constrained by APIs if they’re not truly open. Cloud computing can usher in a new era of productivity for developers if they build on platforms that are designed to be federated rather than centralized. But there’s a major shift underway in p rogramming culture and the languages that will be used in clouds.Today, the integrated, optimized, open-source Apache, MySQL, PHP/Perl/Python (AMP) stack is the preferred platform for building and deploying new Web applications and services. Cloud computing will be the catalyst for the adoption of an even newer stack of more lightweight, agile tools such as lighttpd, an open-source Web server; Hadoop, the free Java software framework that supports data-intensive distributed applications; and MogileFS, a file system that enables horizontal scaling of storage across any number of machines.(2)Compelling New Opportunities: The Cloud EcosystemBut cloud computing isn’t just about a proliferation of Xen image stacks on a restricted handful of infrastructure prov iders. It’s also about an emerging ecosystem of complementary services that provide computing resources such as on-ramps for cloud abstraction, professional services to help in deployment, specialized application components such as distributed databases, and virtual private datacenters for the entire range of IT providers and consumers.These services span the range of customer requirements, from individualdevelopers and small startups to large enterprises. And they continue to expand the levels of virtualization, a key architectural component of the cloud that offers ever-higher abstractions of underlying services.(3) How Did Cloud Computing Start?At a basic level, cloud computing is simply a means of delivering IT resources as services. Almost all IT resources can be delivered as a cloud service: applications, compute power, storage capacity, networking, programming tools, even communications services and collaboration tools.Cloud computing began as large-scale Internet service providers such as Google, Amazon, and others built out their infrastructure. An architecture emerged: massively scaled, horizontally distributed system resources, abstracted as virtual IT services and managed as continuously configured, pooled resources. This architectural model was immortalized by George Gilder in his October 2006 Wired magazine article titled “The Information Factories.” The server farms Gilder wrote about were architecturally similar to grid computing, but where grids are used for loosely coupled, technical computing applications, this new cloud model was being applied to Internet services.Both clouds and grids are built to scale horizontally very efficiently. Both are built to withstand failures of individual elements or nodes. Both are charged on a per-use basis. But while grids typically process batch jobs, with a defined start and end point, cloud services can be continuous. What’s more, clouds expand the types of resources available — file storage, databases, and Web services — and extend the applicability to Web and enterprise applications.At the same time, the concept of utility computing became a focus of IT design and operations. As Nick Carr observed in his book The Big Switch, computing services infrastructure was beginning to parallel the development of electricity as a utility. Wouldn’t it be great if you could purchase compute resources, on demand, only paying for what you need, when you need it?For end users, cloud computing means there are no hardware acquisition costs, no software licenses or upgrades to manage, no new employees or consultants to hire, nofacilities to lease, no capital costs of any kind — and no hidden costs. Just a metered, per-use rate or a fixed subscription fee. Use only what you want, pay only for what you use.Cloud computi ng actually takes the utility model to the next level. It’s a new and evolved form of utility computing in which many different types of resources (hardware, software, storage, communications, and so on) can be combined and recombined on the fly into the specific capabilities or services customers require. From CPU cycles for HPC projects to storage capacity for enterprise-grade backups to complete IDEs for software development, cloud computing can deliver virtually any IT capability, in real time. Under the circumstances it is easy to see that a broad range of organizations and individuals would like to purchase “computing” as a service, and those firms already building hyperscale distributed data centers would inevitably choose to begin offering this infrastructure as a service.(4)Harnessing Cloud ComputingSo how does an individual or a business take advantage of the cloud computing trend? It’s not just about loading machine images consisting of your entire software stack onto a public cloud like AWS — there are several different ways to exploit this infrastructure and explore the ecosystem of new business models.Use the CloudThe number and quality of public, commercially available cloud-based service offerings is growing fast. Using the cloud is often the best option for startups, research projects, Web 2.0 developers, or niche players who want a simple, low-cost way to “load and go.”If you’re an Internet startup today, you will be mandated by your investors to keep you IT spend to a minimum. This is certainly what the cloud is for.Leverage the CloudTypically, enterprises are using public clouds for specific functions or workloads. The cloud is an attractive alternative for:Development and testing — this is perhaps the easiest cloud use case for enterprises (not just startup developers). Why wait to order servers when you don’t even know if theproject will pass the proof of concept?Functional offloading — you can use the cloud for specific workloads. For example, SmugMug does its image thumbnailing as a batch job in the cloud.Augmentation —Clouds give you a new option for handling peak load or anticipated spikes in demand for services. This is a very attractive option for enterprises, but also potentially one of the most difficult use cases. Success is dependent on the statefulness of the application and the interdependence with other datasets that may need to be replicated and load-balanced across the two sites.Experimenting — Why download demos of new software, and then install, license, and test it? In the future, software evaluation can be performed in the cloud, before licenses or support need to be purchased.Build the CloudMany large enterprises understand the economic benefits of cloud computing but want to ensure strict enforcement of secur ity policies. So they’re experimenting first with “private” clouds, with a longer-term option of migrating mature enterprise applications to a cloud that’s able to deliver the right service levels.Other companies may simply want to build private clouds to take advantage of the economics of resource pools and standardize their development and deployment processes.Be the CloudThis category includes both cloud computing service providers and cloud aggregators — companies that offer multiple types of cloud services.As enterprises and service providers gain experience with the cloud architecture model and confidence in the security and access-control technologies that are available, many will decide to deploy externally facing cloud services. The phenomenal growth rates of some of the public cloud offerings available today will no doubt accelerate the momentum. Amazon’s EC2 was introduced only two years ago and officially graduated from beta to general availability in October 2008.Cloud service providers can:Provide new routes to market for startups and Web 2.0 application developersOffer new value-added capabilities such as analyticsDerive a competitive edge through enterprise-level SLAsHelp enterprise customers develop their own cloudsIf you’re building large datacenters today, you should probably be thinking about whether you’re going to offer cloud services.(5)Public, Private, and Hybrid CloudsA company may choose to use a service provider’s cloud or build its own — but is it always all or nothing? Sun sees an opportunity to blend the advantages of the two primary options:Public clouds are run by third parties, and jobs from many different customers may be mixed together on the servers, storage systems, and other infrastructure within the cloud. End users don’t know who else’s job may be me running on the same server, network, or disk as their own jobs.Private clouds are a good option for companies dealing with data protection and service-level issues. Private clouds are on-demand infrastructure owned by a single customer who controls which applications run, and where. They own the server, network, and disk and can decide which users are allowed to use the infrastructure.But even those who feel compelled in the short term to build a private cloud will likely want to run applications both in privately owned infrastructure and in the public cloud space. This gives rise to the concept of a hybrid cloud.Hybrid clouds combine the public and private cloud models. You own parts and share other parts, though in a controlled way. Hybrid clouds offer the promise of on-demand, externally provisioned scale, but add the complexity of determining how to distribute applications across these different environments. While enterprises may be attracted to the promise of a hybrid cloud, this option, at least initially, will likely be reserved for simple stateless applications that require no complex databases or synchronization.3. Cloud Computing Defined(1)Cornerstone TechnologyWhile the basic technologies of cloud computing such as horizontally scaled, distributed compute nodes have been available for some time, virtualization —the abstraction of computer resources —is the cornerstone technology for all cloud architectures. With the ability to virtualize servers (behind a hypervisor-abstracted operating system), storage devices, desktops, and applications, a wide array of IT resources can now be allocated on demand.The dramatic growth in the ubiquitous availability of affordable high-bandwidth networking over the past several years is equally critical. What was available to only a small percentage of Internet users a decade ago is now offered to the majority of Internet users in North America, Europe, and Asia: high bandwidth, which allows massive compute and data resources to be accessed from the browser. Virtualized resources can truly be anywhere in the cloud — not just across gigabit datacenter LANs and WANs but also via broadband to remote programmers and end users.Additional enabling technologies for cloud computing can deliver IT capabilities on an absolutely unprecedented scale. Just a few examples:Sophisticated file systems such as ZFS can support virtually unlimited storage capacities, integration of the file system and volume management, snapshots and copy-on-write clones, on-line integrity checking, and repair.Patterns in architecture allow for accelerated development of superscale cloud architectures by providing repeatable solutions to common problems.New techniques for managing structured, unstructured, and semistructured data can provide radical improvements in data-intensive computing.Machine images can be instantly deployed, dramatically simplifying and accelerating resource allocation while increasing IT agility and responsiveness.(2)The Architectural Services Layers of Cloud ComputingWhile the first revolution of the Internet saw the three-tier (or n-tier) model emerge as a general architecture, the use of virtualization in clouds has created a new set of layers: applications, services, and infra structure. These layers don’t just encapsulateon-demand resources; they also define a new application development model. And within each layer of abstraction there are myriad business opportunities for defining services that can be offered on a pay-per-use basis.Software as a Service (SaaS)SaaS is at the highest layer and features a complete application offered as a service, on demand, via multitenancy — meaning a single instance of the software runs on the provider’s infrastructure and serves multiple client organizations.The most widely known example of SaaS is , but there are now many others, including the Google Apps offering of basic business services such as e-mail. Of course, ’s multitenant application has preceded the definition of cloud computing by a few years. On the other hand, like many other players in cloud computing, now operates at more than one cloud layer with its release of , a companion application development environment, or platform as a service. Platform as a Service (PaaS)The middle layer, or PaaS, is the encapsulation of a development environment abstraction and the packaging of a payload of services. The archetypal payload is a Xen image (part of Amazon Web Services) containing a basic Web stack (for example, a Linux distro, a Web server, and a programming environment such as Pearl or Ruby).PaaS offerings can provide for every phase of software development and testing, or they can be specialized around a particular area, such as content management.Commercial examples include Google App Engine, which serves applications on Google’s infrastructure. PaaS services such as these can provide a great deal of flexibility but may be constrained by the capabilities that are available through the provider.Infrastructure as a Service (IaaS)IaaS is at the lowest layer and is a means of delivering basic storage and compute capabilities as standardized services over the network. Servers, storage systems, switches, routers, and other systems are pooled (through virtualization technology, for example) to handle specific types of workloads —from batch processing toserver/storage augmentation during peak loads.The best-known commercial example is Amazon Web Services, whose EC2 and S3 services offer bare-bones compute and storage services (respectively). Another example is Joyent whose main product is a line of virtualized servers which provide a highly scalable on-demand infrastructure for running Web sites, including rich Web applications written in Ruby on Rails, PHP, Python, and Java.中文翻译云计算1.更高层次的云计算在很多情况下，云计算仅仅是互联网的一个隐喻，也就是网络上运算和数据资源日益增加的一个隐喻。

无人机辅助边缘计算的能量效率最大化算法设计

无人机辅助边缘计算的能量效率最大化算法设计1. 概述在当今信息时代，边缘计算技术作为一种新兴的计算模式，逐渐受到人们的关注和重视。

边缘计算通过将数据处理和存储功能移到网络边缘，以减少数据传输延迟和网络拥塞，提高系统的实时性和可靠性。

无人机技术的快速发展也为边缘计算提供了新的可能性，无人机辅助边缘计算成为了研究热点。

本文将探讨无人机辅助边缘计算的能量效率最大化算法设计，并共享个人观点和理解。

2. 无人机辅助边缘计算技术概述无人机辅助边缘计算是指利用无人机作为移动边缘计算节点，协助边缘服务器完成数据处理和传输任务。

无人机具有灵活的空间移动能力和较强的计算存储能力，可以在特定区域内为终端设备提供计算和存储服务。

边缘计算和无人机技术的结合，为诸如物联网、智能交通、环境监测等领域提供了新的解决方案。

3. 能量效率最大化算法设计原理在无人机辅助边缘计算中，能量效率最大化算法的设计是十分重要的。

能量效率指的是在满足通信质量和计算性能要求的前提下，尽可能降低能量消耗。

算法设计的核心是要在保证任务完成质量的前提下，通过合理的资源调度和优化策略，有效降低系统的能量消耗。

4. 能量效率最大化算法设计方法针对无人机辅助边缘计算的能量效率最大化，可以设计以下几种算法：4.1 遗传算法：遗传算法作为一种全局搜索和优化技术，可以应用于无人机路径规划和资源分配，以达到能量效率最大化的目的。

通过不断进化和适应环境，找到最优的计算与传输方案。

4.2 强化学习算法：强化学习算法是一种通过试错的方式来优化决策的算法。

在无人机辅助边缘计算中，可以通过强化学习来自动学习和调整无人机的行为策略，以使系统的能量效率达到最大化。

4.3 深度学习算法：深度学习算法可以用于数据的特征提取和建模，对于无人机传感器采集的数据进行分析和处理，从而优化系统的能量消耗和性能。

5. 个人观点和理解无人机辅助边缘计算的能量效率最大化算法设计，是一个涉及计算机科学、通信技术和航空航天领域的复杂问题。

HPMSCloudComputingSolution讲解

成功案例介绍
上海电信
成功案例介绍
云计算对上海电信的影响-业务模式
云计算将促使运营商的业务模式将从以通信服务为中心转变为以IT服务为中心
服务内容服务交付模式服务渠道
传统电信业务模式
以通信服务为主，如语音通信、数据通信等
以通信网络为中心进行服务交付，用户对通信服务的使用通过网络终端（如固定电话、手机、电脑等）实现
5 ©2010 HP Confidential
数说上海电信IDC云计算平台
上海电信IDC云平台项目从2010年4月立项，5月招标，3周完成一阶段系统搭建和原型发布，以配合上海电信市场部营销。8月底，云平台完成一阶段开发，投入试运行。11月底云平台一期正式上线。截止至11月底，上海电信已经签约渠道供应商10个，云主机334台全部售罄
实现应用系统的解耦，建立面向服务的技术架构（SOA），在服务器、存储、基础软件、应用等不同层面分别进行虚拟化，建立资源池，实现资源的充分共享
更多的通过平台化机制来统一解决IT 的安全保障问题（如容灾、高可用性、高可靠性等），从而能以更加经济的全面的实现IT安全
成功案例介绍
云计算对上海电信的影响-管理模式
成功案例介绍
云计算对上海电信的影响- IT技术架构
云计算将促使运营商的IT技术架构将从分散、独立、非标准的IT系统转变为集中、共享、标准的云服务
传统IT技术架构
云计算技术架构
部署模式
多数IT系统分散在各地，使用效率较低，难以进行集中有效管理
“一点提供、全网服务”，集中、统一、规范的提供云服务，从而实现规模经济效应，提升IT资源使用效率和管理专业化程度
客户案例 – 上海电信IDC云平台

saas模式之百度百科

saas模式SaaS是Software-as-a-service（软件在线服务）的简称，它是一种基于互联网提供软件服务的应用模式。

随着互联网技术的发展和应用软件的成熟，SaaS作为一种创新的软件应用模式逐渐兴起。

SaaS区别于传统的软件销售模式，使得企业无需购买软硬件、建设机房、招聘IT人员，只需支付极少的服务费用，即可以通过互联网享受到信息服务。

营。

是一种基于互联网提供软件服务的应用模式。

一种随着互联网技术的发展和应用软件的成熟，在21世纪开始兴起的完全创新的软件应用模式，是软件科技发展的最新趋势。

目录编辑本段1、SaaS概念SaaS提供商为企业搭建信息化所需要的所有网络基础设施及软件、硬件运作平台，并负责所有前期的实施、后期的维护等一系列服务，企业无需购买软硬件、建设机房、招聘IT人员，即可通过互联网使用信息系统。

就像打开自来水龙头就能用水一样，企业根据实际需要，向SaaS提供商租赁软件服务。

SaaS 是一种软件布局模型，其应用专为网络交付而设计，便于用户通过互联网托管、部署及接入。

SaaS 应用软件的价格通常为“全包”费用，囊括了通常的应用软件许可证费、软件维护费以及技术支持费，将其统一为每个用户的月度租用费。

对于广大中小型企业来说，SaaS是采用先进技术实施信息化的最好途径。

但SaaS绝不仅仅适用于中小型企业，所有规模的企业都可以从SaaS中获利。

2008 年前，IDC 将SaaS 分为两大组成类别：托管应用管理 (hosted AM) －以前称作应用服务提供 (ASP)，以及“按需定制软件”，即 SaaS 的同义词。

从 2009 年起，托管应用管理已作为 IDC 应用外包计划的一部分，而按需定制软件以及 SaaS 被视为相同的交付模式对待。

目前，SaaS已成为软件产业的一个重要力量。

只要SaaS的品质和可信度能继续得到证实，它的魅力就不会消退。

编辑本段2、SaaS起源SaaS起源于60年代的Mainframe、80年代的C/S、从ASP模式演变而来的SaaS 。

云计算的概念

云计算的影响云计算有可能颠覆软件产业，应用和许可被随时购买和生效，应用在网络上而不是本机上运行。这种转变将数据中心放在网络的核心位置，而所有的应用所需要的计算能力、存储、带宽、电力都由数据中心提供。云计算不仅影响商业模式，还影响开发、部署、运行、交付应用的方式。
云计算对服务提供商意味着什么快速部署缩小主机规模提高资源利用率提高管理效率降低运维成本基础设施可以放置在低土地和能源成本的地区提供商业连续性服务提高服务水平复杂的体系结构商业模式和理念的转变
Many for one
云计算云计算：广大用户依托互联网上某些节点强大的信息资源，包括存储资源、计算资源、软件资源、数据资源、管理资源，为我所用，强调需求驱动、用户主导、按需服务，即用即付，用完即散，不对用户集中控制，用户不关心服务者在什么地方。
one for many
区别
网格计算
云计算的意义 Co件软件
软件
传统方式：每人要安装软件
云方式：什么都不需要安装
云计算的意义 Cont. 提供全新的云安全理念，保护企业的用户终端信誉技术威胁发现管理技术终端安全管理技术
云计算的意义 Cont. 云计算为我们使用网络提供了几乎无限多的可能。简单的设备可以具有无限的计算能力简单的设备可以具有无限的存储能力可轻松实现不同设备间的数据和应用共享
云计算的概念（狭义）云计算是一种基于网络的资源的交付和使用模式，指通过网络获得应用所需的资源（硬件、平台、软件）。提供资源的网络被称为“云”。 “云”中的资源在使用者看来是可以无限扩展的，并且可以随时获取。这种特性经常被比喻向电厂购买电，用户不需要知道电是如何产生的，来自何方，但可以按需购买和使用。

区域高分辨率数值预报检验评估系统

区域高分辨率数值预报检验评估系统
陆天舒;孙鑫;陈昊明;李普曦;朱峰;霍庆;周佰铨;杨琳韵
【期刊名称】《气象科技进展》
【年(卷),期】2024(14)1
【摘要】近年来我国区域高分辨率数值预报业务发展迅速,目前传统检验方法已不能满足高分辨率模式降水检验评估需求。

区域高分辨率数值预报检验评估系统在吸收降水传统检验方法优势的同时,融入基于降水发展演变过程的检验评估方法,旨在建立一套适用于高时空分辨率观测资料的精细化降水检验评估系统,为促进区域模式改进和高分辨率数值预报产品的偏差理解提供了重要参考,也为理解区域数值预报的模拟能力及其偏差提供了新的视角。

【总页数】6页(P32-37)
【作者】陆天舒;孙鑫;陈昊明;李普曦;朱峰;霍庆;周佰铨;杨琳韵
【作者单位】中国气象科学研究院灾害天气国家重点实验室;内蒙古气象台;国家气象信息中心
【正文语种】中文
【中图分类】TP3
【相关文献】
1.高分辨率快速循环同化预报系统在内蒙古地区汛期预报性能检验和评估
2.乌鲁木齐区域数值预报业务系统降水预报检验与评估分析
3.2017年乌鲁木齐区域数值预
报业务系统预报\r性能检验和评估4.华南区域高分辨率数值模式前汛期预报初步评估5.乌鲁木齐区域高分辨率数值预报系统V2.0预报性能客观检验
因版权原因，仅展示原文概要，查看原文内容请购买。

云计算技术在

云计算的业务接口为了方便用户业务由传统IT系统向云计算环境的迁移，云计算应对用户提供统一的业务接口。业务接口的统一不仅方便用户业务向云端的迁移，也会使用户业务在云与云之间的迁移更加容易。在云计算时代，SOA架构和以Web Service为特征的业务模式仍是业务发展的主要路线。
PART 03
数据管理技术云计算的特点是对海量的数据存储、读取后进行大量的分析，如何提高数据的更新速率以及进一步提高随机读速率是未来的数据管理技术必须解决的问题。云计算的数据管理技术最著名的是谷歌的BigTable数据管理技术，同时Hadoop开发团队正在开发类似BigTable的开源数据管理模块。
数据存储技术云计算系统需要同时满足大量用户的需求，并行地为大量用户提供服务。因此，云计算的数据存储技术必须具有分布式、高吞吐率和高传输率的特点。目前数据存储技术主要有Google的GFS（Google File System，非开源）以及HDFS（Hadoop Distributed File System，开源），目前这两种技术已经成为事实标准。
云计算技术关键技术
LOGO
云计算技术关键技术
LOGO
虚拟机技术虚拟机，即服务器虚拟化是云计算底层架构的重要基石。在服务器虚拟化中，虚拟化软件需要实现对硬件的抽象，资源的分配、调度和管理，虚拟机与宿主操作系统及多个虚拟机间的隔离等功能，目前典型的实现（基本成为事实标准）有Citrix Xen、VMware ESX Server 和Microsoft Hype-V等。
云计算技术关键技术
LOGO
分布式编程与计算为了使用户能更轻松的享受云计算带来的服务，让用户能利用该编程模型编写简单的程序来实现特定的目的，云计算上的编程模型必须十分简单。必须保证后台复杂的并行执行和任务调度向用户和编程人员透明。当前各IT厂商提出的“云”计划的编程工具均基于Map-Reduce的编程模型

HCIA-云计算-03-HCIA-Cloud-Computing-V4.0-课程表

PM
安装FusionCompute FusionCompute资源配置
AM 虚拟化特性介绍
PM 虚拟机创建及配置
AM应用场景1 应用场景2 NhomakorabeaPM
应用场景3 应用场景4
AM 云计算的发展趋势
PM 应用场景5
联系电话：
Email:
联系电话：
上课时间：09：00AM —12：00AM（上午、下午中间各休息一次，每次20分钟）
序号时间 1 星期一
2 星期二
3 星期三 4 星期四 5 星期五
班主任：副班主任：
拟制： xxx
华为HCIA-Cloud Computing V4.0培训
XXXX.XX.XX～XXXX.XX.XX
日期
课程
AM 云计算简介
PM 计算虚拟化简介
PM 安装FusionCompute
AM
云计算中的网络基础知识云计算中的存储基础知识
华为hciacloudcomputingv40培训xxxxxxxxxxxxxxxx序号时间日期课程am云计算简介1星期一pm计算虚拟化简介pm安装fusioncompute云计算中的网络基础知识am云计算中的存储基础知识2星期二安装fusioncomputepmfusioncompute资源配置am虚拟化特性介绍3星期三pm虚拟机创建及配置应用场景1am应用场景24星期四应用场景3pm应用场景4am云计算的发展趋势5星期五pm应用场景5班主任
14：00PM —17：00PM（上午、下午中间各休息一次，每次20分钟）
批准：xxx
ng V4.0培训
X.XX
教学方法
理论授课理论授课上机实习
教师
理论授课

HPC高性能计算常用软件(高校版)

4
MXNet
MXNet是一个深度学习库, 支持C++, Python, R, Scala, Julia, Matlab以及JavaScript等语言
计算机科学技术等
5
darknet
对于图片分类训练、验证
计算机科学技术等
6
opencv2/3
OpenCV是一个基于BSD许可（开源）发行的跨平台计算机视觉库，可以运行在Linux、Windows、Android和Mac OS操作系统上
计算机科学技术等
3
TensorFlow
TensorFlow是谷歌基于DistBelief进行研发的第二代人工智能学习系统，其命名来源于本身的运行原理。Tensor（张量）意味着N维数组，Flow（流）意味着基于数据流图的计算，TensorFlow为张量从流图的一端流动到另一端计算过程。
计算机科学技术等
力学、物理学等
15
IDL
IDL使用者可以迅速且方便地运用此软件将数据转换为图以是全色三维图像和模型。
数学、物理学等
化学、化学工程等
9
GROMACS
GROMACS是一个功能强大的分子动力学的模拟软件，其在模拟大量分子系统的牛顿运动方面具有极大的优势。GROMACS是用于研究生物分子体系的分子动力学程序包。
生物学等
10
NAMD
NAMD（NAnoscale Molecular Dynamics）是用于在大规模并行计算机上快速模拟大分子体系的并行分子动力学代码。
计算机科学技术等
7
OpenFOAM
一个完全由C++编写，在linux下运行，面向对象的计算流体力学（CFD）类库
力学、物理学等

基于云计算的遥感图像处理平台设计与开发

基于云计算的遥感图像处理平台设计与开发遥感图像处理平台是一种通过利用遥感技术获取的图像数据进行处理和分析的系统。

在过去的几十年中，遥感图像处理已经成为地理信息系统（GIS）和环境科学领域的重要工具。

随着云计算技术的快速发展，基于云计算的遥感图像处理平台已成为一个新的趋势。

云计算技术的出现为传统的遥感图像处理带来了革命性的变化。

传统的遥感图像处理需要昂贵而庞大的硬件设备和复杂的软件环境。

而基于云计算的遥感图像处理平台通过将处理任务分配给云端强大的计算资源，可以在几分钟内完成复杂的图像处理任务。

此外，云计算平台还可以根据用户的需求进行自动扩展和调整，以满足不同规模和复杂度的遥感图像处理需求。

基于云计算的遥感图像处理平台的设计与开发是一个复杂而全面的过程。

首先，需要建立稳定可靠的云计算环境，并确保有效地管理和维护云计算资源。

其次，需要使用先进的遥感图像处理算法和技术，以提供高质量的图像处理和分析结果。

同时，还需要考虑用户友好的图形界面和交互性，以便用户可以简单、直观地使用平台进行各种图像处理任务。

在设计和开发云计算的遥感图像处理平台时，最重要的是确保平台的可扩展性和可靠性。

平台应能够适应不同规模和复杂度的图像处理任务，并能够处理大规模的遥感图像数据。

此外，平台还应具备高可靠性，以确保在处理过程中不会丢失任何数据，并能够在任何时候恢复和继续处理任务。

为了满足任务的要求，云计算的遥感图像处理平台的设计与开发应遵循以下几个关键步骤：第一步是需求分析。

在这个阶段，需要与用户和利益相关者紧密合作，了解他们的需求和期望。

这将有助于确保开发出的平台符合用户的实际需求，能够提供他们所需要的功能和服务。

第二步是系统设计。

在设计平台时，需要考虑平台的整体架构和组件，以确保它能够有效地处理和分析遥感图像数据。

此外，还需要确定使用的算法和技术，以确保平台能够提供高质量的处理结果。

第三步是开发和测试。

在这个阶段，需要编写和调试平台的代码，并使用模拟数据和真实数据进行测试。

云雾边缘计算

云雾边缘计算一、引言随着物联网（IoT）和5G/6G通信技术的快速发展，数据量呈爆炸式增长，对数据处理和分析的需求也日益增强。

传统的云计算模式由于其数据传输延迟和带宽成本问题，已经无法满足一些低延迟和高带宽需求的应用场景。

为了解决这一问题，云雾边缘计算（Cloud-Fog Edge Computing）应运而生。

云雾边缘计算将数据处理和分析的任务从中心化的数据中心转移到了网络的边缘设备上，从而大大提高了数据处理的速度和效率。

二、云雾边缘计算概述云雾边缘计算是一种将云计算能力扩展到网络边缘的分布式计算模型。

它将数据处理和分析的任务从中心化的数据中心转移到了网络的边缘设备上，如终端设备、网关、路由器等。

这种计算模型利用了边缘设备的计算、存储和通信能力，实现了更快速、更高效的数据处理和分析。

同时，云雾边缘计算还具有低延迟、高带宽、低功耗等优势，能够满足各种低延迟和高带宽需求的应用场景。

三、云雾边缘计算架构云雾边缘计算的架构主要包括以下几个部分：1.终端设备：这些设备收集各种数据，包括传感器数据、视频数据等。

2.边缘节点：这些节点是网络的边缘设备，如网关、路由器等。

它们负责接收终端设备的数据，并进行初步的处理和分析。

3.雾计算节点：这些节点是比边缘节点更高级的计算节点，具有更强大的计算、存储和通信能力。

它们可以对经过初步处理的数据进行更深入的分析和处理。

4.云计算中心：这是整个架构的最高层，负责管理和调度整个架构的运行。

它还可以进行最高层次的数据处理和分析。

四、云雾边缘计算的优势与挑战云雾边缘计算的优势主要体现在以下几个方面：1.低延迟：由于数据处理和分析的任务在网络的边缘设备上进行，大大减少了数据传输的延迟，提高了应用的实时性能。

2.高带宽：边缘设备可以就近处理数据，避免了数据大量传输到中心化数据中心的带宽成本问题，提高了数据传输的效率。

3.降低中心化数据中心压力：通过将部分数据处理和分析的任务转移到网络的边缘设备上，可以减轻中心化数据中心的压力，使其更加专注于高层次的数据处理和分析任务。

全息网格云存储——下一代的天文学存储技术

全息网格云存储——下一代的天文学存储技术斯特凡诺;加略兹;张进京（译）【期刊名称】《中国信息界》【年(卷),期】2012(000)009【摘要】本文讨论了如何采用全息技术建立分布式的RAID系统（磁盘存储阵列），让不同地理位置的分布式天文数据“存储单元”组成一个一体的遥控设备。

为达到这一目的，需要建立一个平台（最好是开放源的），通过相应的软硬件（物理的或虚拟的），促进网页服务的认证加密和传递。

我认为“桉树”开放源平台是实现这一目标的最好平台。

一旦有了适宜的IaaS（基础设施即服务），就能建立所需的虚拟平台PaaS（平台即服务），然后才能按科研需求建立服务SaaS（软件即服务）。

任一一体服务都对应着特殊的仪器或天文台，通过与物理数据紧密相关的分布式次级元数据库提供。

从外部看，这些服务可以被看作是一个资源的组成部分，是分布式计算的结果。

终端用户只要用自己的个人许可证把相应的安全模式远程连接到设备中，就可以部分或全部使用这些技术了。

存储块＋服务构成的平台可以快速扩展，为某一仪器或任务提供分布式网络云计算服务。

建议每种云计算都采用专门的网格基础设施，这样能更好地完成一些重要任务，快速使用大量加密压缩的科学数据。

功效、可访问性、并行程度和冗余度都取决于分布式存储块和数据连网的数量：数量越多，IT系统的容量越大。

这类存储块是两种技术和两种不同计算模式即网格技术与云技术的汇合点。

提取、利用两种技术中的精华可以使效益最大化，缺点最小化，以最佳方式为将来的天文台和天文学任务开发建立基础设施。

在本文中，我首先介绍了我引用的技术：网格计算，云计算（即云存储），最先进的全息数据存储技术与设备，然后讨论了现代科学数据存储设施的若干主要问题，最后提出了一个利用存储块和基本需求服务技术的解决方案。

【总页数】4页(P75-78)【作者】斯特凡诺;加略兹;张进京（译）【作者单位】意大利国立天体物理研究院;意大利国立天体物理研究院;国家信息中心【正文语种】中文【中图分类】TP333【相关文献】1.下一代存储技术--全息存储 [J], 邓严林2.未来海量存储技术之全息存储技术 [J], 王雄3.从引擎到应用的云存储实战——百度云存储技术剖析 [J], 郭杏荣4.全球云存储技术领域顶级实战型专家——专访惠普公司云存储技术专家、首席架构师张楠 [J], 韩晓琳;5.云存储技术在广播电视中的应用框架构建 [J], 张志平因版权原因，仅展示原文概要，查看原文内容请购买。