最新大连理工大学云算计技术及应用PPT课件.ppt

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1、大连理工大学云算计技术大连理工大学云算计技术及应用及应用基本情况申彦明B810助教：齐恒B812Office hour:Fri 3:30-4:30 PMCourse website:http:/ only.Created with Aspose.Slides for.NET 3.5 Client Profile 5.2.0.0.Copyright 2004-2011 Aspose Pty Ltd.Evaluation only.Created with Aspose.Slides for.NET 3.5 Client Profile 5.2.0.0.Copyright 2004-2011 As

2、pose Pty Ltd.What is Cloud Computing?1.Web-scale problems2.Large data centers3.Different models of computing4.Highly-interactive Web applicationsEvaluation only.Created with Aspose.Slides for.NET 3.5 Client Profile 5.2.0.0.Copyright 2004-2011 Aspose Pty Ltd.Evaluation only.Created with Aspose.Slides

3、 for.NET 3.5 Client Profile 5.2.0.0.Copyright 2004-2011 Aspose Pty Ltd.1.“Web-Scale”ProblemsCharacteristics:Definitely data-intensiveMay also be processing intensiveExamples:Crawling,indexing,searching,mining the WebData warehousesSensor networks“Post-genomics”life sciences researchOther scientific

4、data(physics,astronomy,etc.)Web 2.0 applications Evaluation only.Created with Aspose.Slides for.NET 3.5 Client Profile 5.2.0.0.Copyright 2004-2011 Aspose Pty Ltd.Evaluation only.Created with Aspose.Slides for.NET 3.5 Client Profile 5.2.0.0.Copyright 2004-2011 Aspose Pty Ltd.How much data?Google proc

5、esses 20 PB a day(2008)“all words ever spoken by human beings”5 EBCERNs LHC will generate 10-15 PB a year640K ought to be enough for anybody.Evaluation only.Created with Aspose.Slides for.NET 3.5 Client Profile 5.2.0.0.Copyright 2004-2011 Aspose Pty Ltd.Evaluation only.Created with Aspose.Slides for

6、.NET 3.5 Client Profile 5.2.0.0.Copyright 2004-2011 Aspose Pty Ltd.What to do with more data?Answering factoid questionsPattern matching on the WebWorks amazingly wellLearning relationsStart with seed instancesSearch for patterns on the WebUsing patterns to find more instancesEvaluation only.Created

7、 with Aspose.Slides for.NET 3.5 Client Profile 5.2.0.0.Copyright 2004-2011 Aspose Pty Ltd.Evaluation only.Created with Aspose.Slides for.NET 3.5 Client Profile 5.2.0.0.Copyright 2004-2011 Aspose Pty Ltd.How do I make money?Petabytes of valuable customer dataSitting idle in existing data warehousesOv

8、erflowing out of existing data warehousesSimply being thrown awaySource of data:OLTPUser behavior logsCall-center logsWeb crawls,public datasets Structured data(today)vs.unstructured data(tomorrow)How can an organization derive value from all this data?Evaluation only.Created with Aspose.Slides for.

9、NET 3.5 Client Profile 5.2.0.0.Copyright 2004-2011 Aspose Pty Ltd.Evaluation only.Created with Aspose.Slides for.NET 3.5 Client Profile 5.2.0.0.Copyright 2004-2011 Aspose Pty Ltd.2.Large Data CentersWeb-scale problems?Throw more machines at it!Centralization of resources in large data centersNecessa

10、ry ingredients:fiber,juice,and landWhat do Oregon,Iceland,and abandoned mines have in common?Important Issues:EfficiencyRedundancyUtilizationSecurityManagement overheadEvaluation only.Created with Aspose.Slides for.NET 3.5 Client Profile 5.2.0.0.Copyright 2004-2011 Aspose Pty Ltd.Evaluation only.Cre

11、ated with Aspose.Slides for.NET 3.5 Client Profile 5.2.0.0.Copyright 2004-2011 Aspose Pty Ltd.3.Different Computing ModelsUtility computingWhy buy machines when you can rent cycles?Examples:Amazons EC2Platform as a Service(PaaS)Give me nice API and take care of the implementationExample:Google App E

12、ngineSoftware as a Service(SaaS)Just run it for me!Example:Gmail“Why do it yourself if you can pay someone to do it for you?”Evaluation only.Created with Aspose.Slides for.NET 3.5 Client Profile 5.2.0.0.Copyright 2004-2011 Aspose Pty Ltd.Evaluation only.Created with Aspose.Slides for.NET 3.5 Client

13、Profile 5.2.0.0.Copyright 2004-2011 Aspose Pty Ltd.4.Web ApplicationsWhat is the nature of future software applications?From the desktop to the browserSaaS=Web-based applicationsExamples:Google Maps,FacebookHow do we deliver highly-interactive Web-based applications?AJAX(asynchronous JavaScript and

14、XML)A hack on top of a mistake built on sand,all held together by duct tape and chewing gum?Evaluation only.Created with Aspose.Slides for.NET 3.5 Client Profile 5.2.0.0.Copyright 2004-2011 Aspose Pty Ltd.Evaluation only.Created with Aspose.Slides for.NET 3.5 Client Profile 5.2.0.0.Copyright 2004-20

15、11 Aspose Pty Ltd.Some Cloud DefinitionsIan Foster et al defined cloud computing as a large-scale distributed computing paradigm,that is driven by economics of scale,in which a pool of abstracted virtualized,dynamically-scalable,managed computing power,storage,platforms,and services are delivered on

16、 demand to external customers over the internet(云计算是一种商业计算模型。它将计算任务分布在大量计算机构成的资源池上，使各种应用系统能够根据需要获取计算力、存储空间和各种软件服务。)IBM experts consider clouds that can:Host a variety of different workloads,including batch-style backend interactive,user-facing applicationsAllow workloads to be deployed and scaled-ou

17、t quickly through the rapid provisioning of virtual machines or physical machinesSupport redundant,self-recovering,highly scalable programming models that allow workloads to recover from HW/SW failuresMonitor resource use in real time to rebalance allocations on demand Evaluation only.Created with A

18、spose.Slides for.NET 3.5 Client Profile 5.2.0.0.Copyright 2004-2011 Aspose Pty Ltd.Evaluation only.Created with Aspose.Slides for.NET 3.5 Client Profile 5.2.0.0.Copyright 2004-2011 Aspose Pty Ltd.Internet Cloud Goals Sharing of peak-load capacity among a large pool of users,improving overall resourc

19、e utilizationSeparation of infrastructure maintenance duties from domain-specific application developmentMajor cloud applications include upgraded web services,distributed data storage,raw supercomputing,and access to specialized Grid,P2P,data-mining,and content networking servicesEvaluation only.Cr

20、eated with Aspose.Slides for.NET 3.5 Client Profile 5.2.0.0.Copyright 2004-2011 Aspose Pty Ltd.Evaluation only.Created with Aspose.Slides for.NET 3.5 Client Profile 5.2.0.0.Copyright 2004-2011 Aspose Pty Ltd.Three Aspects in Hardware that are New in Cloud ComputingThe illusion of infinite computing

21、resources available on demand,thereby eliminating the need for cloud users to plan far ahead for provisioningThe elimination of an up-front commitment by cloud users,thereby allowing companies to start small and increase hardware resources when neededThe ability to pay computing resources on a short

22、-term basis as needed(e.g.,processors by the hour and storage by the day)and release them after done and thereby rewarding resource conservationEvaluation only.Created with Aspose.Slides for.NET 3.5 Client Profile 5.2.0.0.Copyright 2004-2011 Aspose Pty Ltd.Evaluation only.Created with Aspose.Slides

23、for.NET 3.5 Client Profile 5.2.0.0.Copyright 2004-2011 Aspose Pty Ltd.Some Innovative Cloud Services and Application OpportunitiesSmart and pervasive cloud applications for individuals,homes,communities,companies,and governments,etc.Coordinated Calendar,Itinerary,job management,events,and consumer r

24、ecord management(CRM)servicesCoordinated word processing,on-line presentations,web-based desktops,sharing on-line documents,datasets,photos,video,and databases,etcDeploy conventional cluster,grid,P2P,social networking applications in cloud environments,more cost-effectivelyEarthbound Applications th

25、at Demand Elasticity and Parallelism rather data movement CostsEvaluation only.Created with Aspose.Slides for.NET 3.5 Client Profile 5.2.0.0.Copyright 2004-2011 Aspose Pty Ltd.Evaluation only.Created with Aspose.Slides for.NET 3.5 Client Profile 5.2.0.0.Copyright 2004-2011 Aspose Pty Ltd.Operations

26、in Cloud ComputingUsers interact with the cloud to request serviceProvisioning tool carves out the systems from the cloud configuration or reconfiguration,or deprovision The servers can be either real or virtual machinesSupporting resources include distributed storage system,datacenters,security dev

27、ices,etc.Evaluation only.Created with Aspose.Slides for.NET 3.5 Client Profile 5.2.0.0.Copyright 2004-2011 Aspose Pty Ltd.Evaluation only.Created with Aspose.Slides for.NET 3.5 Client Profile 5.2.0.0.Copyright 2004-2011 Aspose Pty Ltd.Cloud Computing InstancesGoogleAmazonMicrosoft AzureIBM Blue Clou

28、dEvaluation only.Created with Aspose.Slides for.NET 3.5 Client Profile 5.2.0.0.Copyright 2004-2011 Aspose Pty Ltd.Evaluation only.Created with Aspose.Slides for.NET 3.5 Client Profile 5.2.0.0.Copyright 2004-2011 Aspose Pty Ltd.Google Cloud InfrastructureSchedulerChubbyGFS masterNodeNodeNodeUserAppli

29、cationSchedulerslaveGFSchunkserverLinuxNodeMapReduceJobBigTableServerGoogle Cloud InfrastructureEvaluation only.Created with Aspose.Slides for.NET 3.5 Client Profile 5.2.0.0.Copyright 2004-2011 Aspose Pty Ltd.Evaluation only.Created with Aspose.Slides for.NET 3.5 Client Profile 5.2.0.0.Copyright 200

30、4-2011 Aspose Pty Ltd.S3EBSEC2EBSEC2EBSEC2EBSEC2SimpleDBSQSUserDeveloperAmazon Elastic Computing CloudSQS:Simple Queue ServiceEC2:Running Instance of Virtual MachinesEBS:Elastic Block Service,Providing the Block Interface,Storing Virtual Machine ImagesS3:Simple Storage Service,SOAP,Object InterfaceS

31、impleDB:Simplified DatabaseEvaluation only.Created with Aspose.Slides for.NET 3.5 Client Profile 5.2.0.0.Copyright 2004-2011 Aspose Pty Ltd.Evaluation only.Created with Aspose.Slides for.NET 3.5 Client Profile 5.2.0.0.Copyright 2004-2011 Aspose Pty Ltd.Azure Services PlatformMicrosoft Azure Platform

32、Evaluation only.Created with Aspose.Slides for.NET 3.5 Client Profile 5.2.0.0.Copyright 2004-2011 Aspose Pty Ltd.Evaluation only.Created with Aspose.Slides for.NET 3.5 Client Profile 5.2.0.0.Copyright 2004-2011 Aspose Pty Ltd.DeveloperMonitoringApplicationServerProvisioningManagerUserOpen Source Lin

33、ux with XenTivoli Monitoring AgentIBM Blue CloudEvaluation only.Created with Aspose.Slides for.NET 3.5 Client Profile 5.2.0.0.Copyright 2004-2011 Aspose Pty Ltd.Evaluation only.Created with Aspose.Slides for.NET 3.5 Client Profile 5.2.0.0.Copyright 2004-2011 Aspose Pty Ltd.Cost Considerations:Power,

34、Cooling,Physical Plant,and Operational CostsCosttechnology costscost of securityetc.Benefitsavailabilityopportunityconsolidationetc.Evaluation only.Created with Aspose.Slides for.NET 3.5 Client Profile 5.2.0.0.Copyright 2004-2011 Aspose Pty Ltd.Evaluation only.Created with Aspose.Slides for.NET 3.5

35、Client Profile 5.2.0.0.Copyright 2004-2011 Aspose Pty Ltd.Cost Breakdown+Storage($/MByte/year)+Computing($/CPU Cycles)+Networking($/bit)Evaluation only.Created with Aspose.Slides for.NET 3.5 Client Profile 5.2.0.0.Copyright 2004-2011 Aspose Pty Ltd.Evaluation only.Created with Aspose.Slides for.NET

36、3.5 Client Profile 5.2.0.0.Copyright 2004-2011 Aspose Pty Ltd.Research Challenges Service availabilityS3 outage:authentication service overload leading to unavailabilityAppEngine partial outageprogramming errorGmail:site unavailable Solutions:The management of a Cloud Computing service by a single c

37、ompany results in a single point of failure(SPF).In the Internet,a large ISP uses multiple network providers so that failure by a single company will not take them off the air.Similarly,we need multiple Cloud Computing providers to support each other to eliminate SPF.Evaluation only.Created with Asp

38、ose.Slides for.NET 3.5 Client Profile 5.2.0.0.Copyright 2004-2011 Aspose Pty Ltd.Evaluation only.Created with Aspose.Slides for.NET 3.5 Client Profile 5.2.0.0.Copyright 2004-2011 Aspose Pty Ltd.Research ChallengesData SecurityCurrent cloud offerings are essentially public rather than private network

39、s,exposing the system to more attacks such as DDoS attacks.Solutions:There are many well understood technologies such as encrypted storage,virtual local area networks,and network middle boxes.Evaluation only.Created with Aspose.Slides for.NET 3.5 Client Profile 5.2.0.0.Copyright 2004-2011 Aspose Pty

40、 Ltd.Evaluation only.Created with Aspose.Slides for.NET 3.5 Client Profile 5.2.0.0.Copyright 2004-2011 Aspose Pty Ltd.Research ChallengesData Transfer BottlenecksApplications continue to become more data-intensive.If we assume applications may be“pulled apart”across the boundaries of clouds,this may

41、 complicate data placement and transport.Both WAN bandwidth and intra-cloud networking technology are performance bottleneck.Industrial solutions:It is estimated that 2/3 of the cost of WAN bandwidth is consumed by high-end routers,whereas only 1/3 charged by fiber industry.We can lower the cost by

42、using simpler routers built from commodity components with centralized control,but research is heading towards using high-end distributed routers.Evaluation only.Created with Aspose.Slides for.NET 3.5 Client Profile 5.2.0.0.Copyright 2004-2011 Aspose Pty Ltd.Evaluation only.Created with Aspose.Slide

43、s for.NET 3.5 Client Profile 5.2.0.0.Copyright 2004-2011 Aspose Pty Ltd.Research ChallengesSoftware LicensingCurrent software licenses commonly restrict the computers on which the software can run.Users pay for the software and then pay an annual maintenance fee.Many cloud computing providers origin

44、ally relied on open source software in part because the licensing model for commercial software is not a good match to Utility Computing.Some ideas:We can encourage sales forces of software companies to sell products into Cloud Computing.Or they can implement pay-per-use model to the software to ada

45、pt to a cloud environment.Evaluation only.Created with Aspose.Slides for.NET 3.5 Client Profile 5.2.0.0.Copyright 2004-2011 Aspose Pty Ltd.Evaluation only.Created with Aspose.Slides for.NET 3.5 Client Profile 5.2.0.0.Copyright 2004-2011 Aspose Pty Ltd.Research ChallengesScalable storageDifferences b

46、etween common storage and cloud storageThe system is built from many inexpensive commodity components that often fail The system stores a modest number of large filesThe workloads primarily consist both large streaming reads and small random reads.The workloads many large,sequential writes that appe

47、nd data to files and once written,files are seldom modified again.The cloud storage(file)system needs to share many of the same goals as previous distributed file systems such as performance,scalability,reliability,and availability.In addition,its design needs to be driven by key observations of the

48、 specific workloads and technological environment,both current and anticipated,that reflect a marked departure from some earlier file system design assumptions.GFSFiles are divided into fixed-size chunks,Chunk size is one of the key design parameters.GFS chooses 64 MB,which is much larger than typic

49、al file system block sizes.The master stores three major types of metadata:the file and chunk namespaces,the mapping from files to chunks,and the locations of each chunks replicas.GFS supports the usual operations to create,delete,open,close,read,and write files.Evaluation only.Created with Aspose.S

50、lides for.NET 3.5 Client Profile 5.2.0.0.Copyright 2004-2011 Aspose Pty Ltd.Evaluation only.Created with Aspose.Slides for.NET 3.5 Client Profile 5.2.0.0.Copyright 2004-2011 Aspose Pty Ltd.Research ChallengesTransparent Programming ModelPrograms written for cloud implementation need to be automatica