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GRID ECONOMICS. Lecturer: Ph.D Pham Tran Vu Students: Tran Quang Khai - 00708196 Nguyen Thanh Hai - 00708191 Le Qui Dong - 00707165. Outline. Introduction. What is Grid economics? Grid economics vision. Players in Grid marketplace. Economic/business models. Grid practices:
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GRID ECONOMICS Lecturer: Ph.D Pham Tran Vu Students: Tran Quang Khai - 00708196 Nguyen Thanh Hai - 00708191 Le Qui Dong - 00707165
Outline • Introduction. • What is Grid economics? • Grid economics vision. • Players in Grid marketplace. • Economic/business models. • Grid practices: • Nimrod-G. • GridEcon. • Summarize and conclusion. • Q & A.
Introduction • Current using of Grid in enterprises: • In large enterprises: • Consolidating IT resources. • Improving the workflow within an enterprise. • In small and medium enterprises (SMEs): • Almost not consider. • Lack of economic principles in the current Grid middlewares. • Miss out many helpful Grid’s properties.
Introduction • Grid can supply: • Availability of on-demand resources. • When consumer requests unavailable resources. • Supplier can buy the resources on the Grid. • Easily access to resources. • Low cost ownership. • Resources that you can’t afford for possession. • Pay-for-use pricing model. • Only pay for the usage of resources.
Introduction • Grid can help SMEs: • Opportunities. • Independency. • Compete with large enterprises.
What is Grid economics? • Definition: • Applying economic principles to Grid computing. • Grid infrastructure to support commercial, economic Grids. • Service Level Agreements (SLAs). • Pricing and Capacity Planning. • Business models for the Grid.
What is Grid business? • Definition: • Business activities. • Through commercialized IT services. • Based on Grid computing. • Grid business model: • Defines a framework for creating new value chains.
Some Grid-economics Projects • European Grid Projects • GridEcon, http://www.gridecon.eu • BEinGRID, http://www.beingrid.eu/ • Gridbus,http://www.gridbus.org/ • American Grid Project • TeraGrid , http://www.teragrid.org/ • GT4, http://www.globus.org/ • Asian Grid Project • K*Grid, http://www.gridcenter.or.kr/ (South Korea) • NAREGI, http://www.naregi.org/index_e.html (Japan) • CNGrid http://www.cngrid.org/ (China) • Australian Grid Project • GridBus, http://www.gridbus.org/
Example • Amazon EC2: • Allows the user to create virtual machines. • VM: • Initiate, run and monitor applications. • Price (Feb 2007): • $0.10 per instance-hour. • $0.20 per GB of transferred data. • $0.15 per GB-Month of Amazon S3 Storage. • 1.7Ghz Xeon CPU. 160GB local disk. • 1.75GB RAM. 250Mb/s network bandwidth.
Grid economics vision • Assume: • Grid needs a part called “Open market”: • Allows participants to: • Buy services. • Sell enhanced services at the same time.
Grid economics vision (cont.) • 3 existing technologies: • Service-oriented computing. • Virtualization of resources. • Network computing. • 1 missing: Economic-enhanced services • Economic risks and transaction opportunities. • Enlarge the access of existing Grid business. • Grid middleware Economic-aware or Market-aware
Grid economics architecture • Three layers: • Consumer. • Economic-enhanced service provider. • The basic resources provider.
Players in the Grid Marketplace • 2 key players: • Grid Service Providers (GSPs): producers. • Grid Resource Brokers (GRBs): consumers.
Players in the Grid Marketplace • The GSPs: • Make their resources Grid enabled by running software systems along with Grid Trading Services (GTS). • Interaction between GSPs and GRBs: • Through a Grid Market Directory (GMD). • For deciding service access price. • Economic models. • Interaction protocols.
Players in the Grid Marketplace • GRBs: • May invite bids from a number of GSPs. • Select those that offer: • Lowest service costs. • Meet their deadline and budget requirements. • GSPs: • May invite bids in an auction. • Offer services to the highest bidder as long as its objectives are met.
Business Models Commodity Market Model Posted Price Model Bargaining Model Tendering/Contract-Net Model Auction Model Bid-based Proportional Resource Sharing Model Community/Coalition/Bartering Model
Business Models 1.Commodity Market Model Interaction between GSPs and users in a commodity market Grid.
Business Models • Pricing schemes in a Commodity Market Model can be based on: • Flat fee. • Usage Duration (Time). • Subscription. • Demand and Supply-based.
Business Models • Deployment: • The users compose their application using higher-level Grid programming languages. • The resource broker (working for the user) can carry out the following steps for executing applications: • The broker identifies service providers. • It identifies suitable resources and establishes their prices (by interacting with GMD and GTS). • It selects resources that meet its utility function and objectives (lower cost and meet deadline requirements). • It uses resource services for job processing and issues payments as agreed.
Business Models Posted price model and resource trading 2. Posted Price Model
Business Models • The posted price model: • Is similar to the commodity market model, except that it advertises special offers. • The activities that are: • Grid Service Providers (GSPs) post their special offers and associated conditions etc. in Grid Market Directory. • Broker looks at GMD to identify if any of these posted services are available and fits its requirements. • Broker enquires (GSP) for availability of posted services. • Other steps are similar to those pointed out in commodity market model.
Business Models Bargaining for lower access price in their bid for minimizing computational cost. 3. Bargaining Model
Business Models • In the bargaining model: • Both brokers and GSPs have their own objective functions. • They negotiate with each other as long as their objectives are met.
Business Models Tender/ContractNet model for resource trading. 4. Tender/Contract-Net Model
Business Models • In this model, a task to be solved is called the manager and resource that might be able to solve the task is called contractor. • From a manager’s perspective, the process is: • Consumer (Broker) announces its requirements (using deal template) and invites bids from GSPs. • Interested GSPs evaluate the announcement and respond by submitting their bids. • Broker evaluates and awards the contract to the most appropriate GSP(s). • The broker and GSP communicate privately and use the resource (R).
Business Models • From a contractor’s/GSP perspective, the process is: • Receive tender announcements/advertisements (say in GMD). • Evaluate service capability. • Respond with bid. • Deliver service if bid is accepted. • Report results and bill the broker/user as per the usage and agreed bid.
Business Models • Advantage: • If the selected GSP is unable to deliver a satisfactory service, the brokers can seek services of other GSPs. • This protocol has certain disadvantages. • A task might be awarded to a less capable GSP if a more capable GSP is busy at award time. • Another limitation is that the GRB manager has no obligation to inform potential contractors that an award has already been made.
Business Models 5. Auction Model
Business Models • The steps involved in the auction process are: • GSPs announce their services and invite bids. • Brokers offer their bids (and they can see what other consumers offer if they like - depending on open/closed). • Step (b) goes on until no one is willing to bid higher price or auctioneer stops if the minimum price line is not met. • GSP offers service to the one who wins. • Consumer uses the resource.
Business Models Market-based Proportional Resource Sharing. 6. Bid-based Proportional Resource Sharing Model
Business Models In this model, the percentage of resource share allocated to the user application is proportional to the bid value in comparison to other users’ bids.
Business Models • 7. Community/Coalition/Bartering/Share Holders Model. • A community of individuals shares each other’s resources to create a cooperative computing environment. Those who are contributing their resources to a common pool can get access to that pool. • This model works when those participating in the Grid have to be both service providers and consumers.
Grid Practice • Nimrod-G • Rajkumar Buyya, David Abramson and Jonathan Giddy. • Monash University, University of Queensland Australia.
Nimrod-G • A resource management and scheduling system • Supports deadline and budget-constrained algorithms • Supports GUI tools and declarative programming language • Abilities: • Resource discovery • Mapping jobs to appropriate resources • Gathering results
Nimrod-G - Architecture A grid resource broker based on the GRACE framework Follows hourglass design model
Nimrod-G – Architecture (cont.) • Nimrod-G Clients, which can be: • Tools for creating parameter sweep applications. • Steering and control monitors. • Customized end user applications. • Nimrod-G Resource Broker: • A Task Farming Engine (TFE), • A Scheduler that performs resource discovery, trading, and scheduling. • A Dispatcher and Actuator. • Agents for managing the execution of jobs.
Cost Deadline
Nimrod-G - Scheduling Algorithms When the user submits a parameter sweep application containing N tasks along with quality of service requirements, the broker performs the following activities: Resource Discovery: Identifying resources and their properties and then selecting resources capable of executing user jobs. Resource Trading: Negotiating and establishing service access cost using a suitable economic model. Scheduling: Select resources that fit user requirements using scheduling heuristic/algorithm and map jobs to them. Deploy jobs on resources [Dispatcher]. Monitor and Steer computations Perform load profiling for future usage When the job execution is finished, gather results back to the user home machine [Dispatcher]. Record all resource usage details for payment processing purpose. Perform rescheduling: Repeat steps 3-8 until all jobs are processed and the experiment is within the deadline and budget limit. Perform cleanup and post-processing, if required.
Nimrod-G - Deadline and budget constrained scheduling • 3 adaptive algorithms: • Cost Optimization, within time and budget constraints • Time Optimization, within time and budget constraints • Conservative Time Optimization, within time and budget constraints.
Nimrod-G - Time Optimization scheduling algorithm • For each resource: • Calculate the next completion time for an assigned job. • Taking into account previously assigned jobs and job consumption rate. • Sort resources by next completion time. • Assign one job to the first resource: • The cost per job is less than or equal to the remaining budget per job. • Repeat until all jobs are assigned.
Nimrod-G - Cost Optimization scheduling algorithm • Sort resources by increasing cost. • For each resource in order: • Assign as many jobs as possible to the resource, without exceeding the deadline.
Nimrod-G - Conservative Time Optimization algorithm • Split resources : Cost per job is less than or equal to the budget per job. • For the cheaper resources: • Assign jobs in inverse proportion to the job completion time. • E.g: a resource with completion time = 5 gets twice as many jobs as a resource with completion time = 10. • For the dearer resources, repeat until all jobs are assigned.
Nimrod-G - Software Availability Website: http://www.csse.monash.edu.au/~davida/nimrod/
GridEcon • A European Union funded project on Grid Economics and Business Models. • Goals: • Identify missing technology and software. • The design of the required economic enhancements to Grid technology • The implementation of a subset of these service enhancements • The simulation of the workings of the enhancements. • Perform economic and business modeling • Show how hardware, software, and information services can be bought and sold on the Grid. • Investigate potential ecosystems and explore current and future business models. • Website:http://www.gridecon.eu
Summarize and conclusion • Grid economics: • Help to manage and use resources in the way that both provider and consumer get benefit. • Have potential using in enterprises, especially SMEs: • Reduce cost. • Improve competition ability. • Some issues: • The resources in the Grid are geographically distributed and owned by multiple organizations with different usage and cost policies. • The management of resources in such a large and distributed environment is a complex task. • Lack of regulations/rules
References • Papers: • GridEcon – The Economic-Enhanced Next-Generation Internet (Jörn Altmann, Costas Courcoubetis, John Darlington, Jeremy Cohen). • Economic Models for Resource Management and Scheduling in Grid Computing (Rajkumar Buyya, David Abramson, Jonathan Giddy, and Heinz Stockinger). • Taxonomy of Grid Business Models (Jörn Altmann, Mihaela Ion, Ashraf Adel Bany Mohammed).
References (cont.) • Websites: • http://www.my-groups.de/altmann/?page_id=19 • http://www.gridecon.eu • http://www.gridbus.org • http://www.globus.org