A Case for Economy Grid Architecture for Service Oriented Grid Computing

1. A Case for Economy Grid Architecture for Service Oriented Grid Computing Authors: Rajkumar Buyya, David Abramson & Jonathan Giddy Presenter: Diego Lopez Agnostic: Djuradj Babic

2. Outline • Introduction • Grid Economy and Resource Management Issues • Economy Models and Related Work • GRACE • Resource Trading and Scheduling Experimentation • Conclusion and Future Work

3. 1. Introduction “ We expect that an economy driven approach to resource management and scheduling will make a great impact on the eventual success and widespread adoption of the Grid in day-to-day computational activities.” Researcher Giddy Dr. Buyya Prof. Abramson Source: Buyya, R http://www.buyya.com

4. 1. Introduction • Grid environment is complex ($$$) • Different access cost models • Dynamically varying loads and availability conditions • Use of economic models in the Grid to encourage participation and wide-scale adoption • Proposal of computational economy framework that leverage existing Grid sites

5. View of Economic Grid Source: Buyya, R A Case for Economy Grid Architecture for Service Oriented Grid Computing (Pg. 2)

6. 2. Grid Economy and Resource Management Issues • Establish policies that promote Grid resource sharing • 2 key players in Grid economy • Resource providers (GSP) • Resource consumers (GRB) • Consumers interact with brokers to express their budget and deadline requirements from the Grid

7. Proposal of GRACE • Grid Architecture for Computational Economy • Leverage of existing infrastructures: • Globus/Legion • Condor/G • Provide an infrastructure that allows for: • Info/Market directory for publicizing entities • Model for determining value of resources • Resource pricing schemes • Accounting, Billing and Payment mechanisms

8. 3. Economy Models and Related Work Possible economic models for resource trading and pricing strategies • Commodity Market • Posted Price • Bargaining • Tendering/Contract-Net • Auction • Bid-based Proportional Resource Sharing • Community/Coalition/Bartering

9. Examples of Computational Economy Systems

10. 4. GRACE • Use of well-adopted Grid technologies, Globus/Condor • Development of middleware services for resource trading using different economic models • Development of advanced user-centric Grid resource brokers

11. 4.1 Grid Resource Broker (GRB) • Mediator between user and grid resources • *Nimrod – parametric modeling language • Use of Nimrod/G broker (superscheduler) • Job Control Agent • Schedule Advisor • Grid Explorer • Trade Manager • Deployment Agent http://ipdps.cc.gatech.edu/2000/papers/Abramson.pdf

12. RM: Local Resource Manager, TS: Trade Server Nimrod/G Broker Nimrod/G Client Nimrod/G Client Nimrod/G Client Nimrod/G Engine Schedule Advisor Trading Manager Grid Store Grid Dispatcher Grid Explorer Grid Middleware Globus, Legion, Condor, etc. TM TS GE GIS Grid Information Server(s) RM & TS RM & TS RM & TS G C L G Condor enabled node. Legion enabled node. Globus enabled node. L Src: http://www.buyya.com/ecogrid/

13. 4.2 Economy Grid Middleware in Globus Context • Trade Server (TS) – maximize the resource utility and profit for its owner • Pricing Policies – define prices for resources based on economic models previously mentioned • Resource Accounting and charging – tracking resource usage for billing and auditing purposes

14. 4.3 Grid Open Trading Protocols and Deal Template • Establish rules and format for exchanging commands between a GRACE client (Trade Manager) and Trade Server • Deal Template (DT) contains • CPU time • Storage requirements • Initial offer • This trading overhead can be reduced if prices are announced via GIS

15. 4.4 Pricing, Accounting, and Payment Mechanisms • N-ways to determine resource pricing • Fixed price model (no QoS like today’s www) • Usage timing (peak, off-peak) • Bulk purchase • Demand and supply • Loyalty of customers (i.e. frequent flyer miles) • Calendar based

16. 4.4 Pricing, Accounting, and Payment Mechanisms • Service items to be charged • CPU time • Memory • Storage used • Software and Libraries accessed (ASP) • Access to these services can be charged • Individually • Combination (costing matrix)

17. 4.4 Pricing, Accounting, and Payment Mechanisms • Prepaid – purchase credits from GSP or Grid Bank • Use and pay later (like electricity) • Pay as you go (wireless calling cards) • Grants based • *Billing services handled by 3rd party: • NetCheque • Paypal *not incorporated into GRACE described in this paper

18. 4.5 System Prototype & Demo Experiences • Prototype of the Nimrod/G resource brokering demo held during HPDC 2000 • Parameter study experiment performed over Grid resources located in both Australia and the US • Ability to change deadline and budget to trade-off cost vs. timeframe to illustrate Grid marketplace dynamics

19. 5. Resource Trading and Scheduling Experimentation • Experiment to test operation of Grid Trade Server across 5 systems (165 jobs) • Use of Posted Price Market Model for the Nimrod/G brokering • Runs during peak time vs. off-peak time • Access price expressed in Grid units per CPU second (G$) • Resource/service price provided by GRACE framework

20. Economy Grid Results • Cost-Optimization algorithm successfully • Minimized artificial access cost per resource • Completed within one-hour deadline • Initial calibration phase ensures completion within budget/time constraints • Scheduler excluded usage of resources during peak time • Scheduler predictions met deadline using least-expensive resources available

21. 6. Conclusion and Future Work • GRACE leverages existing middleware systems (Condor/Legion/Globus) • Nimrod/G can discover best resource providers based on user’s requirements • Nimrod/G does not support dynamic prices once initial scheduling is proposed • Nimrod/G Portal available …