Dr. Rajkumar Buyya

1. WW Grid The Gridbus Middleware:Enabling Market-based Grid Computing for e-Science and e-Business Applications Grid Computing and Distributed Systems (GRIDS) Lab. Dept. of Computer Science and Software EngineeringThe University of Melbourne, Australiagridbus.org/~raj/tut/gridbus.zip Dr. Rajkumar Buyya

2. (1) Water (2) Electricity (3) Gas (4) Telephone 4 Essential Utilities (in Home)

3. (5) IT services as the fifth utility (water, electricity, gas, telephone, IT) e-Science eBusiness eGovernment eHealth Multilingual eEducation …

4. GRIDS Lab @ Melbourne R & D Education • The youngest and one of the largest research labs in the CSSE Dept: • 3 PostDocs • 3 Research Programmers • 10 RHD (7 PhD) students • ~5 honours/masters projects • Funding • National and International organizations • Australian Research Council • Many industries (Sun, StorageTek, Microsoft, IBM) • University-wide collaboration: • Faculties of Science, Engineering, and Medicine • Many national and international collaborations. • Academics and Industries • Software: • Our Grid middleware technologies are widely in academic and industrial users. • Publication: • My research team produces 20% of our Dept’s research output. + Community Services

5. Books at Glance: Co-authored/edited

6. Presentation Outline • Part 1: Introduction to Grid Computing and Applications • Technology Evolution and Application Drivers • Grid Challenges, Approaches, and Architecture • Part 2: Grid Economy and Service Oriented Computing • Challenges • Service-Oriented Grid Architecture (SOGA) • Realisation of SOGA • Part 3: Global Grids and Gridbus Technologies • Grid Market Directory, GridBank, VPM, Grid Service Broker, G-Monitor • Part 4: Performance Evaluation on the World-Wide Grid • Compute Grid Application • eScience Application – Belle Analysis Data Grid • Part 5: Closing Remarks • Analogy to Electric Power Grid • Summary and Conclusion

7. Evolution: Humans  eHumans (eHugging, eSmell, eFood!), Science  eScience, Business  eBusiness

8. Computing and Communication Technologies Evolution * HTC * P2P * PDAs Minicomputers * * PCs * Workstations * Mainframes * Grids COMPUTING * Computing Utility * PC Clusters * Crays * MPPs * WS Clusters * XEROX PARC worm * eScience * eBusiness * IETF * W3C * TCP/IP Communication * Ethernet * HTML * Mosaic * Web Services * Email * Sputnik * SocialNet * Internet Era * WWW Era * XML * ARPANET 2010 1960 1970 1975 1980 1985 1990 1995 2000

9. 2100 2100 2100 2100 2100 2100 2100 2100 2100 Computing Evolving towards: Global/Grid Computing SERV ICES + PERFORMANCE Administrative Barriers • Individual • Group • Department • Campus • State • National • Globe • Inter Planet • Universe Personal Device SMPs or SuperComputers Global Grid Inter Planet Grid Local Cluster Enterprise Cluster/Grid

10. Leading to Grid (computing) Paradigm:Cyberinfrastructure for sharing resources • Inspired by Power Grid! • * A service-oriented/utility computing paradigm that enables seamless sharing of geographically distributed, autonomous resources. • * This was the original aim of building Internet although it ended up in giving birth to email!

11. What is Grid ?(there are several definitions) • A type of parallel and distributed system that enables the sharing, selection, & aggregationof geographically distributed “autonomous” resources: • Computers– PCs, workstations, clusters, supercomputers, laptops, notebooks, mobile devices, PDA, etc; • Software– e.g., ASPs renting expensive special purpose applications on demand; • Catalogued data and databases– e.g. transparent access to human genome database; • Special devices/instruments – e.g., radio telescope – SETI@Home searching for life in galaxy. • People/collaborators. depending on their availability, capability, cost, and user QoS requirements. Widearea

12. database A Bird Eye View of World-Wide Grid Environment Grid Information Service Grid Resource Broker Application R2 R3 R4 R5 RN Grid Resource Broker R6 R1 Resource Broker Grid Information Service

13. Type of Services Modern Grids Offer • Computational Services – CPU cycles • NASA IPG, WWG, TeraGrid, SETI@Home • Data Services • Data replication, management, secure access--LHC Grid/Napster • Application Services • Access to remote software/libraries and license management—NetSolve • Information Services • Extraction and presentation of data with meaning • Knowledge Services • The way knowledge is acquired and managed using meta data & semantics. • Utility Computing Services Utility Grid Knowledge Grid Information Grid ASP Grid Data Grid Computational Grid

14. Prominent Grid Drivers: Emerging e-Science and e-Business Apps • Next generation experiments, simulations, sensors, satellites, even people and businesses are creating a flood of data. • e-Science refers to the large scale science that will increasingly be carried out through distributed global collaborations enabled by the Internet. ~PBytes/sec High Energy Physics Brain Activity Analysis Newswire & data mining: Natural language engineering Digital Biology Life Sciences Astronomy Quantum Chemistry Finance: Portfolio analysis Internet & Ecommerce

15. Analysis Results Analysis Results 1. Online Medical Instrumentation and Neuroscience DV transfer Osaka Univ. • Virtual Laboratory • for medicine and brain science • Knowledge sharing • MEG sharing? • Data Sharing Data Generation Osaka Univ. Hospital Data Analysis Life-electronics laboratory, AIST Cybermedia Center • Provision of MEG • Provision of expertise in • the analysis of brain function

16. Traditional Model Grid Based Model 2. Enterprise Computing Applications Service Virtualization Layer & Load Balancing Email server Web server Database server Apps server Upgrade to a new server to handle more users Horizontal integration of Email, Web, Data, and Apps servers

17. Global Grids and Challenges

18. 2100 2100 2100 2100 2100 2100 2100 2100 Distributed instruments Distributed data E-Science / E-Business App Elements Peers sharing ideas and collaborative interpretation of data/results E-Scientist Distributed computation Remote Visualization Data & Compute Service

19. Grid Information Service Grid Resource Broker Application R2 R3 R4 R5 RN Grid Resource Broker R6 R1 Resource Broker Grid Information Service database Grids have Emerged as Cyber-infrastructure that scales from enterprise to global

20. 2100 2100 2100 2100 2100 2100 2100 2100 2100 Grid-based Utility Computing model need to scale from desktops to Global level SERV ICES + PERFORMANCE Administrative Barriers • Individual • Group • Department • Campus • State • National • Globe • Inter Planet • Universe Personal Device SMPs or SuperComputers Global Grid Inter Planet Grid Local Cluster Enterprise Cluster/Grid

21. Grids need to offer a wide variety of services • Computational Services – CPU cycles • SETI@Home, NASA IPG, TeraGrid, I-Grid,… • Data Services • Data replication, management, secure access--LHC Grid/Napster • Application Services • Access to remote software/libraries and license management—NetSolve • Information Services • Extraction and presentation of data with meaning • Knowledge Services • The way knowledge is acquired and managed—data mining. • Utility Computing Services • Towards a market-based Grid computing: Leasing and delivering Grid services as ICT utilities. Utility Grid Knowledge Grid Information Grid ASP Grid Data Grid Computational Grid

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

23. GOC Grid Exchange Grid Operations Management Challenges –dynamic resources, policies, and self interested entities GSP GSP GSP5 GSP1 Grid Economy Technologies GSP4 GSP2 GSP3

24. 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 I-Grid Japan NAGERI Korea... N*Grid Singapore NGP USA Globus GridSec AccessGrid TeraGrid Cyberinfrasture and many more... Industry Initiatives IBM On Demand Computing HP Adaptive Computing Sun N1 Microsoft - .NET Oracle 10g Infosys – Enterprise Grid Satyam – Enterprise Grid StorageTek –Grid.. and many more Public Forums Global Grid Forum Australian Grid Forum Conferences: CCGrid Grid HPDC E-Science Some Grid Initiatives Worldwide 27 million 1.3 billion – 3 yrs 2? billion 120million – 5 yrs 450million – 5 yrs 486million – 5 yrs 1.3 billion (Rs) 1 billion – 5 yrs http://www.gridcomputing.com

25. NetSolve mix-and-match (service) Object-oriented Internet/partial-P2P Grid Computing Approaches Network enabled Solvers Economic-based Utility / Service-Oriented Computing Nimrod-G

26. The Gridbus Project @ Melbourne:Enable Leasing of ICT Services on Demand Distributed Data WWG Gridbus World Wide Grid! On Demand Utility Computing

28. Presentation Outline • Part 1: Introduction to Grid Computing and Applications • Technology Evolution and Application Drivers • Grid Challenges, Approaches, and Architecture • Part 2: Grid Economy and Service Oriented Computing • Challenges • Service-Oriented Grid Architecture (SOGA) • Realisation of SOGA • Part 3: Global Grids and Gridbus Technologies • Grid Market Directory, GridBank, VPM, Grid Service Broker, G-Monitor • Part 4: Performance Evaluation on the World-Wide Grid • Compute Grid Application • eScience Application – Belle Analysis Data Grid • Part 5: Closing Remarks • Analogy to Electric Power Grid • Summary and Conclusion

29. Gridbus considers: “Incentive” as a Design Parameter for Grid Computing • Grids aim at exploiting synergies that result from cooperation of autonomous distributed entities. Synergies include: • Creation of Virtual Organisations/Enterprises • Resource sharing • Aggregation of resources on demand. • For this cooperation to be sustainable, participants needs to have (economic) incentive. • Therefore, “incentive” mechanisms should be considered as one of key design parameters of Grid computing.

30. Grid Economy: Methodology for Sustained Resourced Sharing and Managing Supply-and-Demand for Resources

31. Benefits of Computational Economy • It provides an effective paradigm for managing self interested and self-regulating entities (resource owners and consumers) • Helps in regulating supply-and-demand of resources. • Services can be priced in such a way that equilibrium is maintained. • User-centric / Utility driven • Scalable: • No need of central coordinator (during negotiation) • Resources(sellers) and also Users(buyers) can make their own decisions and try to maximize utility and profit. • Adaptable, • It allows to offer different QoS (quality of services) to different applications depending the value users place on them. • It offers incentive for resource owners for being part of the grid! • It offers incentive for resource consumers for being good citizens. • It improves the utilisation of resources.

32. It helps Users to Achieve their Goals • Grid Consumers • Execute jobs for solving varying problem size and complexity • Benefit by selecting and aggregating resources wisely • Tradeoff timeframe and cost • Strategy: minimise expenses • Grid Providers • Contribute (“idle”) resource for executing consumer jobs • Benefit by maximizing resource utilisation • Tradeoff local requirements & market opportunity • Strategy: maximise return on investment

33. New challenges of Grid Economy • Grid Service Providers (GSPs) • 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? • ….. • Grid Service Consumers (GSCs) • How do I decide expenses ? • How do I express QoS requirements ? • How do I trade between timeframe & cost ? • How do I map jobs to resources to meet my QoS needs? • ….. • They need mechanisms and technologies for value expression, value translation, and value enforcement.

34. GRACE: A Reference Grid Economy Services Architecture GRid Architecture for Computational Economy (GRACE)

35. Market-based Computing Systems Requirements • To enable users (GSPs and GSCs) to realise economic value, market-based systems need to provide mechanisms for: • Value Expression • a means to express their requirements, valuations, and objectives • Value Translation • scheduling policies to translate them to resource allocations • Value Enforcement • mechanisms to enforce the selection and allocation of differential services, and dynamic adaptation to changes in their availability at runtime • Market mechanisms, accounting and payment, Reservation of resources.

36. GRACE: A ReferenceService-Oriented Grid Architecture for Computational Economies 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 Grid Middleware Services Grid Consumer Grid Service Providers

37. Realising Market-based Grid: Minimal New Components • Grid Market Directory Services • Grid Trading Services – • for different economic models • Grid Metering Services • Grid Accounting and Payment Services • Grid Service Broker

38. CDB PDB Gridbus and Complementary Grid Technologies – realizing GRACE Grid Applications … Science Commerce Engineering Collaboratories Portals … ExcellGrid Gridscape Workflow X-Parameter Sweep Lang. MPI User-LevelMiddleware (Grid Tools) … Grid Brokers: Workflow Engine Gridbus Data Broker Nimrod-G Core Grid Middleware Grid MarketDirectory Grid Exchange & Federation Globus Unicore Grid Storage Economy GridBank … Alchemi NorduGrid XGrid GRIDSIM .NET JVM Condor PBS SGE Libra Tomcat Grid Economy Grid Fabric Software Mac Windows Linux AIX IRIX OSF1 Solaris Grid Fabric Hardware Worldwide Grid

39. Application Code Explore data 1 Data Visual Application Composer 10 Results+Cost Info 2 GridResource Broker Data Catalogue 5 4 Grid Info Service Data Replicator (GDMP) 12 6 3 ASP Catalogue Grid Market Directory 9 7 Job Results 8 Grid Service (GS) (Globus) Bill Alchemi GS CPU orPE PE GTS 11 GridbusGridBank Cluster Scheduler PE GSP (Accounting Service) GSP (e.g., IBM) GSP (e.g., VPAC) GSP (e.g., UofM) On Demand Assembly of Services: Interaction Between Grid Components Data Source (Instruments/distributed sources) Cluster Scheduler PE Grid Service Provider (GSP)(e.g., CERN)

42. Alchemi: .NET-based Enterprise Grid Platform & Web Services Alchemi Manager Web Services Internet Alchemi Users Internet • SETI@Home like Model • General Purpose • Dedicated/Non-dedicate workers • Role-based Security • .NET and Web Services • C# Implementation • GridThread and Job Model Programming • Easy to setup and use • Widely in use! Alchemi Worker Agents

43. Some Users of Alchemi Tier Technologies, USA Large scale document processing using Alchemi framework Satyam Computers Applied Research Laboratory, India Micro-array data processing using Alchemi framework CSIRO, Australia Natural Resource Modeling The University of Sao Paulo, Brazil The Alchemi Executor as a Windows Service stochastix GmbH, Germany Asynchronous Excel Tasks using ManagedXLL and Alchemi .Net Grid Computing framework. The Friedrich Miescher Institute (FMI) for Biomedical Research, Switzerland Patterns of transcription factors in mammalian genes Many users in Universities: See next for an example.

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46. Globus Technologies Usage • Security (GSI - Globus Security Infrastructure) - single sign-on and authentication based on RSA public key cryptography technology. • You need have Grid ID, public key, and private key (assigned by trusted CA) • Authorization to use: You need have your Grid ID mapped to a physical (login) account on every Grid nodes that you want to use. • Authentication: User proxy (trigger by grid-proxy-init) and Grid node gatekeeper authenticate each other by exchanging messages. (If you can decrypt the message that I sent by encrypting using your public key, then you are who you are claiming to be.) • Information (MDS - Metacomputing Directory Service) – LDAP-server based uniform access to resource structure/state information. • GIIS – Grid Index Information Service (one for your Grid!/organisation) • GRIS – Grid Resource Information Service (one for each node). • Communications (grid-ftp) - multi-method communication and QoS management. • Process/Job Management (GRAM - Globus Resource Allocation Manager) - Low-level (uniform) API for various local schedulers. • Remote file access(GASS - Global Access to Secondary Storage). • Reservation of Resources in Advance (GARA).

47. Globus Components (in One Slide) MDS client API calls to locate resources Client-side APIs MDS: Grid Index Info Server Site boundary MDS client API calls to get resource info GRAM client API calls to request resource allocation and process creation. MDS: Grid Resource Info Server Query current status of resource GRAM client API state change callbacks Globus Security Infrastructure Local Resource Manager Allocate & create processes Request Job Manager Create Gatekeeper Process Parse Monitor & control Process RSL Library Process

48. Presentation Outline • Part 1: Introduction to Grid Computing and Applications • Technology Evolution and Application Drivers • Grid Challenges, Approaches, and Architecture • Part 2: Grid Economy and Service Oriented Computing • Challenges • Service-Oriented Grid Architecture (SOGA) • Realisation of SOGA • Part 3: Global Grids and Gridbus Technologies • Grid Market Directory, GridBank, VPM, Grid Service Broker, G-Monitor • Part 4: Performance Evaluation on the World-Wide Grid • Compute Grid Application • eScience Application – Belle Analysis Data Grid • Part 5: Closing Remarks • Analogy to Electric Power Grid • Summary and Conclusion

50. The Grid Market Directory Grid Vision: To enable the creation of Virtual Enterprise (VE), Virtual Oranisation (VO), or Grid MarketPlace (GMP).