Utility-Oriented Cloud & Grid Computing: A Vision, Hype, and Reality

1. Utility-Oriented Cloud & Grid Computing: A Vision, Hype, and Reality Grid Computing and Distributed Systems (GRIDS) LabDept. of Computer Science and Software EngineeringThe University of Melbourne, Australiawww.gridbus.orgwww.buyya.comwww.manjrasoft.com Dr. Rajkumar Buyya Gridbus Sponsors

2. The GRIDS Lab @ Melbourne R & D Education • Youngest and one of the rapidly growing research labs in our School/University: • Founded in 2002 • Houses 20+ researchers consisting of: • Research Fellows/PostDocs • Software Engineers • PhD candidates • Honours/Masters students • Funding • National and International organizations • Australian Research Council & DEST • Many industries (Sun, StorageTek, Microsoft, IBM, Microsoft) • University-wide collaboration: • Faculties of Science, Engineering, and Medicine • Many national and international collaborations. • Academics • Industries • Software: • Widely in academic and industrial users. • Publication: • My research team produces over 20% of our Dept’s research output. + Community Services: e.g., IEEE TC for Scalable Computing

3. Agenda • Introduction • Utility Networks and Grid Computing • Application Drivers and Various Types of Grid Services • Global Grids and Challenges • Security, resource management, pricing models, … • Service-Oriented Grid Architecture and Gridbus Solutions • Market-based Management, GMD, Grid Bank, Aneka • Grid Service Broker • Architecture, Design and Implementation • Performance Evaluation: Experiments in Creation and Deployment of Applications on Global Grids • A Case Study in High Energy Physics • Summary and Conclusion

4. 1969 – Leonard Kleinrock, ARPANET project “As of now, computer networks are still in their infancy, but as they grow up and become sophisticated, we will probably see the spread of ‘computer utilities’, which, like present electric and telephone utilities, will service individual homes and offices across the country” Computers Redefined 1984 – John Gage, Sun Microsystems “The network is the computer” 2008 – David Patterson, U. C. Berkeley “The data center is the computer. There are dramatic differences between of developing software for millions to use as a service versus distributing software for millions to run their PCs” 2008 – “Cloud is the computer” – Buyya! “Computer Utilities” Vision: Implications of the Internet

5. Computing Paradigms and Attributes: Realizing the ‘Computer Utilities’ Vision ? } • Web • Data Centres • Utility Computing • Service Computing • Grid Computing • P2P Computing • Market-Oriented Computing • Cloud Computing • … + • -Ubiquitous access • -Reliability • Scalability • Autonomic • Dynamic discovery • Composability • -QoS • -SLA • - … • Trillion $ business • Who will own it? Paradigms Attributes/Capabilities

6. * Since Grids have been around for sometime (early 2000), do we have a unified vision of what Grids can do? * And did we make sufficient advances to turn vision of “computer utilities” into a reality? - Let us take a look at views of “industrial” practitioners & “academics”

7. “Industrial” vision of Grid computing • IBM • On Demand Computing • Microsoft • .NET • Oracle • 10g • Sun • N1 – Sun Grid Engine • HP • Adaptive Enterprise • Amazon • Elastic Compute Cloud Services • Manjrasoft • Aneka for building enterprise Grids and Clouds.

8. Most academics view: Cyberinfrastructure for conducting collaborative (e-)Science

9. database How do Grids look like?A Bird Eye View of a Global Grid Grid Information Service Grid Resource Broker Application R2 R3 R4 R5 RN Grid Resource Broker R6 R1 Resource Broker Grid Information Service

10. database How do Grids look like?A Bird Eye View of a Global Grid Grid Information Service Grid Resource Broker Application R2 R3 R4 R5 RN Grid Resource Broker R6 R1 Resource Broker Grid Information Service

11. How Are Grids Used? Utility computing High-performance computing Collaborative design Financial modeling Collaborative data-sharing High-energy physics E-Business Life sciences Drug discovery Data center automation E-Science Natural language processing Business Intelligence (Data Mining)

12. Agenda • Introduction • Utility Networks and Grid Computing • Application Drivers and Various Types of Grid Services • Global Grids and Challenges • Security, resource management, pricing models, … • Service-Oriented Grid Architecture and Gridbus Solutions • Market-based Management, GMD, Grid Bank, Aneka • Grid Service Broker • Architecture, Design and Implementation • Performance Evaluation: Experiments in Creation and Deployment of Applications on Global Grids • A Case Study in High Energy Physics • Summary and Conclusion

13. Computational Economy Security Data locality Resource Allocation & Scheduling Uniform Access System Management Resource Discovery Application Construction Network Management Grid Challenges

14. Australia Nimrod-G Gridbus DISCWorld GrangeNet. APACGrid ARC eResearch Brazil OurGrid, EasyGrid LNCC-Grid + many others China ChinaGrid – Education CNGrid - application Europe UK eScience EU Grids.. and many more... India Garuda Japan NAREGI Korea... N*Grid Singapore NGP USA Globus TeraGrid Cyberinfrasture AutoMate and many more... Industry Initiatives IBM On Demand Computing HP Adaptive Computing Sun N1 Microsoft - .NET Oracle 10g Amzon – Elastic Compute Cloud Infosys – Enterprise Grid Satyam – Business Grid Manjrasoft – enterprise Clouds and Grids and many more Public Forums Open Grid Forum Conferences: CCGrid Grid HPDC E-Science Some Grid Initiatives Worldwide 1.3 billion – 3 yrs 27 million 2? billion 120million – 5 yrs 450million – 5 yrs 486million – 5 yrs 1.3 billion (Rs) 1 billion – 5 yrs http://www.gridcomputing.com

15. Open-Source Grid Middleware Projects OurGrid Slide by Hiro

16. Driving Theme:Community vs. Utility Grids

17. The Gridbus Project @ Melbourne:Enable Leasing of ICT Services on Demand WWG Gridbus Pushes Grid computing into mainstream computing

19. Agenda • Introduction • Utility Networks and Grid Computing • Application Drivers and Various Types of Grid Services • Global Grids and Challenges • Security, resource management, pricing models, … • Service-Oriented Grid Architecture and Gridbus Solutions • Market-based Management, GMD, Grid Bank, Aneka • Grid Service Broker • Architecture, Design and Implementation • Performance Evaluation: Experiments in Creation and Deployment of Applications on Global Grids • A Case Study in High Energy Physics • Summary and Conclusion

20. What do Grid players want & require? • Grid Service Consumers (GSCs): - minimize expenses, meet QoS • How do I express QoS requirements ? • How do I trade between timeframe & cost ? • How do I discover services and map jobs to meet my QoS needs? • How do I manage Grid dynamics and get my work done? • … • Grid Service Providers (GSPs):– maximise ROI • How do I decide service pricing models ? • How do I specify them ? • How do I translate them into resource allocations ? • How do I enforce them ? • How do I advertise & attract consumers ? • How do I do accounting and handle payments? • … • They need mechanisms, tools and technologies that help them in value expression, value translation, and value enforcement.

21. Service-Oriented Grid Architecture Data Catalogue Grid Bank Information Service Grid Market Services Sign-on HealthMonitor Info ? Grid Node N … Grid Explorer … Secure ProgrammingEnvironments Job Control Agent Grid Node1 Applications Schedule Advisor QoS Pricing Algorithms Trade Server Trading Trade Manager Accounting Resource Reservation Misc. services … Deployment Agent JobExec Resource Allocation Storage Grid Resource Broker … R1 R2 Rm Core Middleware Services Grid Service Consumer Grid Service Providers

22. CDB PDB Market-Oriented Grid Software: A union of Gridbus and other technologies … Grid Applications Science Commerce Engineering Collaboratories Grid Portals … APIs/Tools: ExcellGrid Workflow APIs Task, Parametric, and Components Programming MPI User-LevelMiddleware Grid Workflow Engine Grid Scheduling: Gridbus Resource Broker Grid MarketDirectory Grid Exchange & Federation Globus Unicore … Grid Storage Economy GridBank Core Grid Middleware Aneka Cloud (WS-based access + SLA NorduGrid XGrid Grid Economy JVM Condor PBS SGE Libra Tomcat .NET Grid Fabric Software Mac Windows Linux AIX IRIX OSF1 Solaris Grid Fabric Hardware Worldwide Grid

23. Application Code Explore data 1 Visual Application Composer 10 Results+Cost Info 2 GridResource Broker Data Catalogue 5 4 Grid Info Service 12 6 3 ASP Catalogue Grid Market Directory 9 7 Job Results 8 Grid Service (GS) (Globus) Bill Aneka EC2 CPU orPE PE GTS 11 GridbusGridBank Resource Allocation PE GSP (Accounting Service) GSP (e.g., IBM) GSP (e.g., Amazon) GSP (e.g., Microsoft) On Demand Assembly of Services in Market-Oriented Grid Environments

24. On Demand Assembly of Services in Market-Oriented Grid Environments

25. Cloud Services • Infrastructure as a Services (IaaS) • CPU, Storage: Amazon.com et. al • Platform as a Services (PaaS) • Google App Engine, Microsoft Azure, andManjrasoft Aneka • Software as a Service (SaaS) • SalesForce.Com Enterprise/Private Clouds Clouds Public/Internet Clouds

26. Software as a Service (SaaS) e.g., ..SalesForce.com Platform as a Service (PaaS) e.g., ..Aneka Infrastructure as a Service (IaaS) e.g., Amazon, Nirvanix Layered view of services within a Cloud stack

27. Aneka A Software Platform for Building and Managing “Enterprise” Grids and Clouds

28. Aneka: A 3rd Gen enterprise Grid Technology  Cloud model

29. .NET based service-oriented platform for grid / cloud computing Development and Run Time Environment Includes Development and Management Tools Suitable for Development of Enterprise Grid / Cloud Applications Grid / Cloud enabling legacy applications Ideal for Corporate Developers, Software, SaaS, Hosting Vendors and Application / System Integrators ANEKA – Product Overview (Alpha) ANEKA Product Architecture

30. Enterprise/Private Harness LAN connected resources Application Development, Testing, Execution Teaching and Learning Sensitive applications Public Hosted by a 3rd party service provider owning a large Data Center (1000s of servers) Offers subscription-based services to their shared infrastructure on “pay-as go” model.to many users from different organisations. Amazon.com, Microsoft Azure Aneka SDK + Execution Manger Aneka Deployment Models Enterprise/Private Clouds Aneka Public Clouds

31. Executor Executor Executor Executor Scheduler ClientAgent ClientAgent Programming / Deployment Model FIRST PRODUCT Aneka: components public DumbTask: ITask { … public void Execute() { …… } } Aneka enterprise Cloud for(int i=0; i<n; i++) { … DumbTask task = newDumbTask(); app.SubmitExecution(task); } work units internet work units Aneka Worker Service Aneka Manager internet Aneka Users

32. How does it solve the problem? An Illustratioin • Divide the problem in to multiple small tasks and distribute them run in parallel on multiple computers within a Cloud. Executor Application Manager Manager / Executor GThreads/Tasks

33. User scenario: GoFront(unit of China Southern Railway Group) Aneka Maya Renderer Use private Aneka Cloud Case 2: Aneka Enterprise Cloud Time (in hrs) Case 1: Single Server Using Maya Graphical Mode Directly Single Server Aneka Cloud Aneka utilizes idle desktops (30) to decrease task time from days to hours 4 cores server Application: Locomotive design CAD rendering Raw Locomotive Design Files (Using AutoDesk Maya) GoFront Private Aneka Cloud LAN network (Running Maya Batch Mode on demand)

34. Aneka: How can get it? • Available to Download: • Software: www.manjrasoft.com • Manual: Setting up Cloud using your LAN-network computers • Teaching material • parallel and distributed computing and programming, • List of possible assignments for students • Possible Projects for Final year students.. • Price – highly affordable  • = Fee you charge to 1 student (each year) and all students/teachers in entire college/university can use it! • Applications • Other Departments (Physics, Chemistry, Biology, Finance, Engineering) can use it for their applications.

35. On Demand Assembly of Services in Market-Oriented Grid Environments

36. Agenda • Introduction • Utility Networks and Grid Computing • Application Drivers and Various Types of Grid Services • Global Grids and Challenges • Security, resource management, pricing models, … • Service-Oriented Grid Architecture and Gridbus Solutions • Market-based Management, GMD, Grid Bank, Aneka • Grid Service Broker • Architecture, Design and Implementation • Performance Evaluation: Experiments in Creation and Deployment of Applications on Global Grids • A Case Study in High Energy Physics • Summary and Conclusion

37. Grid Service Broker (GSB) • A resource broker for scheduling task farming data Grid applications with static or dynamic parameter sweeps on global Grids. • It uses computational economy paradigm for optimal selection of computational and data services depending on their quality, cost, and availability, and users’ QoS requirements (deadline, budget, & T/C optimisation) • Key Features • A single window to manage & control experiment • Programmable Task Farming Engine • Resource Discovery and Resource Trading • Optimal Data Source Discovery • Scheduling & Predications • Generic Dispatcher & Grid Agents • Transportation of data & sharing of results • Accounting

38. workload Gridbus User Console/Portal/Application Interface App, T, $, Optimization Preference Gridbus Broker Gridbus Farming Engine Schedule Advisor Trading Manager RecordKeeper Grid Dispatcher Grid Explorer TM TS $ GE GIS, NWS Core Middleware Grid Info Server RM & TS G $ Data Catalog Data Node C $ U G Globus enabled node. L A Amazon EC2/S3 Cloud.

39. Home Node/Portal Gridbus Broker batch() -PBS -Condor -SGE -Aneka -XGrid fork() Data Catalog Globus Aneka Amazon EC2 SSH Job manager fork() AMI batch() fork() batch() -PBS -Condor -SGE -XGrid -PBS -Condor -SGE Gridbus agent Gridbus agent Gridbus Broker: Separating “applications” from “different” remote service access enablers and schedulers Application Development Interface Single-sign on security Alogorithm1 SchedulingInterfaces AlogorithmN Plugin Actuators Data Store Access Technology SRB Grid FTP

40. Gridbus Services for eScience applications • Application Development Environment: • XML-based language for composition of task farming (legacy) applications as parameter sweep applications. • Task Farming APIs for new applications. • Web APIs (e.g., Portlets) for Grid portal development. • Threads-based Programming Interface • Workflow interface and Gridbus-enabled workflow engine. • … Grid Superscalar – in cooperation with BSC/UPC • Resource Allocation and Scheduling • Dynamic discovery of optional computational and data nodes that meet user QoS requirements. • Hide Low-Level Grid Middleware interfaces • Globus (v2, v4), SRB, Aneka, Unicore, and ssh-based access to local/remote resources managed by XGrid, PBS, Condor, SGE.

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43. Agenda • Introduction • Utility Networks and Grid Computing • Application Drivers and Various Types of Grid Services • Global Grids and Challenges • Security, resource management, pricing models, … • Service-Oriented Grid Architecture and Gridbus Solutions • Market-based Management, GMD, Grid Bank, Aneka • Grid Service Broker • Architecture, Design and Implementation • Performance Evaluation: Experiments in Creation and Deployment of Applications on Global Grids • A Case Study in High Energy Physics • Summary and Conclusion

44. Case Study: High Energy Physics and Data Grid • The Belle Experiment • KEK B-Factory, Japan • Investigating fundamental violation of symmetry in nature (Charge Parity) which may help explain “why do we have more antimatter in the universe OR imbalance of matter and antimatter in the universe?”. • Collaboration 1000 people, 50 institutes • 100’s TB data currently

45. Case Study: Event Simulation and Analysis B0->D*+D*-Ks • Simulation and Analysis Package - Belle Analysis Software Framework (BASF) • Experiment in 2 parts – Generation of Simulated Data and Analysis of the distributed data Analyzed 100 data files (30MB each) that were distributed among the five nodes within Australian Belle DataGrid platform.

46. Australian Belle Data Grid Testbed VPACMelbourne

47. Belle Data Grid (GSP CPU Service Price: G$/sec) G$4 NA G$4 G$6 VPACMelbourne G$2 Datanode

48. Belle Data Grid (Bandwidth Price: G$/MB) 32 33 36 G$4 31 30 34 NA 38 31 G$4 G$6 VPACMelbourne G$2 Datanode

49. Deploying Application Scenario • A data grid scenario with 100 jobs and each accessing remote data of ~30MB • Deadline: 3hrs. • Budget: G$ 60K • Scheduling Optimisation Scenario: • Minimise Time • Minimise Cost • Results:

50. fleagle.ph.unimelb.edu.au belle.anu.edu.au belle.physics.usyd.edu.au brecca-2.vpac.org 80 70 60 50 Number of jobs completed 40 30 20 10 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 Time (in mins.) Time Minimization in Data Grids