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CDA for Grid and Cloud

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Double Auction-based Scheduling of Scientific Applications in Distributed Grid and Cloud Environments by R. Prodan, M. Wieczorek, H.M. Fard

Double Auction-based Scheduling of Scientific Applications in Distributed Grid and Cloud Environments by R. Prodan, M. Wieczorek, H.M. Fard

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  • 1. Double Auction-based Scheduling ofScientific Applications in Distributed Grid and Cloud Environments Francesc Lordan Gomis Metodologia de Recerca en la Informàtica 25/06/2012
  • 2. OutlineIntroductionAuction TheoryModel and strategiesResultsConclusions Double Auction-based Scheduling of Scientific applications in Distributed Grid and Cloud Environment 1
  • 3. IntroductionGrid and Cloud Computing allow user to execute applications on a third-party infrastructure by paying for the access to the remote resources Double Auction-based Scheduling of Scientific applications in Distributed Grid and Cloud Environment 2
  • 4. IntroductionUsers are represented by Schedulers that picks which resource a job will be runThe providers are represented by Resource Managers that try to maximize the incomes of the provider by optimizing the resource usage Resource Resource Manager Manager Scheduler Resource Resource Manager Manager Double Auction-based Scheduling of Scientific applications in Distributed Grid and Cloud Environment 3
  • 5. IntroductionWhen many users try to obtain the same resources, they compete for them.Since access to these resources is paid, it can be seen as a market governed by the supply-demand lawEconomy-based negotiation techniques are attractive from bussiness point of view Scheduler Resource Manager Scheduler Scheduler Market Resource ? Manager Scheduler Scheduler Resource Manager Scheduler Scheduler Resource Manager Scheduler Double Auction-based Scheduling of Scientific applications in Distributed Grid and Cloud Environment 4
  • 6. Auction TheoryAuctions are an economic mechanism used for allocating a set of resources among a group of bidders.Models: Single-sided auctions: the seller submits a resource and the bidders submit their offers to buy (bid) - English auction: buyers constantly increase their offers until the highest one wins - Dutch auction: the seller decreases the price of the resource until a buyer decides to pay the proposed price - Sealed auctions: buyers give their bids on an envelope First-price: the highest bid wins Vickrey second-price: the second highest bid wins Double Auction-based Scheduling of Scientific applications in Distributed Grid and Cloud Environment 5
  • 7. Auction TheoryAuctions are an economic mechanism used for allocating a set of resources among a group of bidders.Models: Double-sided auctions: all the participant submit their offers to sell (asks) and buy (bids) - Call Auctions: during a timeframe all the participants submit their offers and finally they try to match - Continuous Double Auction (CDA): offers are continously submitted until a match between the lowest ask and the highest bid is achieved or the auction times out. Combinatorial auctions: a single bid for multiple resource (NP-complete) Double Auction-based Scheduling of Scientific applications in Distributed Grid and Cloud Environment 6
  • 8. Model and strategiesDouble Auction-based Scheduling of Scientific applications in Distributed Grid and Cloud Environment 7
  • 9. Model and strategiesThe limitation on resources converts the schedulers into competitors with their own negotiation strategy.Any strategy is based on 4 factors Resource selection Resource valuation Auction participation Bidding Double Auction-based Scheduling of Scientific applications in Distributed Grid and Cloud Environment 8
  • 10. Model and strategiesResource SelectionBefore bidding, the scheduler decides for which resources it will participate in an auction.When a task is sumitted the scheduler looks for a pending auction. If there is no such auction the scheduler postpones the bidding until there is one.The selection is done with a lottery where probabilities take into account:Availability of the resourceExecution timeBudget cost Double Auction-based Scheduling of Scientific applications in Distributed Grid and Cloud Environment 9
  • 11. Model and strategiesResource ValuationUser Valuation 2 steps: - Update the value of the resource depending on the final price of its last auction and a smoothing factor α. - Increases the value depending on the number of lost auctions and a revaluation factor β.Provider Valuation Depending on the success ratio on the last auctions for the resource the price is increased or decreased by a resource revaluation factor γ Double Auction-based Scheduling of Scientific applications in Distributed Grid and Cloud Environment 10
  • 12. Model and strategiesAuction participationScheduler participates when there is at least one task waiting for that resource. Tasks are kept in a priority queue sorted by the bottom levelsResource Manager The time between two auctions of the same resource are created depend on the result for the last auctions. If it was won, it wait until the resource has been used and adds a delay If it was lost, the delay is incremented exponentially with a delaying factor δ Double Auction-based Scheduling of Scientific applications in Distributed Grid and Cloud Environment 11
  • 13. Model and strategiesBiddingZero Intelligence: participants submit their offers periodicallyScheduler tries to reduce the value of the resource by decreasing the distance between its valuation and the highest bidResource Manager tries to increase the value of the resource by reducing the distance between its valuation and the lowest ask Double Auction-based Scheduling of Scientific applications in Distributed Grid and Cloud Environment 12
  • 14. Model and strategiesModifications to the base strategy:Self-limitation Reduce the price by reducing the competence limit the number of auctions where the scheduler participates in based on: The average number of retries A resource limitation factor ζPricing Agressiveness Change the revaluation factor of a single scheduler Value of the resource are increased faster or slower Double Auction-based Scheduling of Scientific applications in Distributed Grid and Cloud Environment 13
  • 15. ResultsResource Valuation Double Auction-based Scheduling of Scientific applications in Distributed Grid and Cloud Environment 14
  • 16. ResultsResource Valuation Double Auction-based Scheduling of Scientific applications in Distributed Grid and Cloud Environment 15
  • 17. ResultsSelf-limitation Double Auction-based Scheduling of Scientific applications in Distributed Grid and Cloud Environment 16
  • 18. ResultsPricing aggressiveness Double Auction-based Scheduling of Scientific applications in Distributed Grid and Cloud Environment 1 17
  • 19. ConclusionsCreation of an open market of resources implemented as a CDA instanceIdentification the general behaviour pattersEvaluation of strategies: Self-limitation: - has marginal improvements on specific configuration - NOT RECOMENDED Concessive strategy: - very good for the common-drift case Aggressive-strategy: - reduces execution time with low impact on the budget on the single-user deviation case - higher budget and similar execution time on the common-drift case - RISKY Double Auction-based Scheduling of Scientific applications in Distributed Grid and Cloud Environment 18
  • 20. QuestionsDouble Auction-based Scheduling of Scientific applications in Distributed Grid and Cloud Environment 19
  • 21. Resource Selection availability Expected execution time and cost at any resource Expected execution time Resource value0 <= rsfmin <=rsfmax<=1 Resource selection ratio Double Auction-based Scheduling of Scientific applications in Distributed Grid and Cloud Environment
  • 22. Resource ValuationScheduler Smoothing factor Last final price Last valuation Linear Exponential Resource revaluation factor # lost auctions for the resourceResource Manager Average success ratio Resource revaluation factor Double Auction-based Scheduling of Scientific applications in Distributed Grid and Cloud Environment
  • 23. Auction ParticipationDelay factor # lost auctions for the resource Double Auction-based Scheduling of Scientific applications in Distributed Grid and Cloud Environment
  • 24. Self-limitation Resource limitation factor Average retry numberDouble Auction-based Scheduling of Scientific applications in Distributed Grid and Cloud Environment
  • 25. WorkflowsDouble Auction-based Scheduling of Scientific applications in Distributed Grid and Cloud Environment
  • 26. Pricing aggressivenessDouble Auction-based Scheduling of Scientific applications in Distributed Grid and Cloud Environment
  • 27. Pricing aggressivenessDouble Auction-based Scheduling of Scientific applications in Distributed Grid and Cloud Environment
  • 28. Pricing aggressivenessDouble Auction-based Scheduling of Scientific applications in Distributed Grid and Cloud Environment
  • 29. Pricing aggressivenessDouble Auction-based Scheduling of Scientific applications in Distributed Grid and Cloud Environment
  • 30. Pricing aggressivenessDouble Auction-based Scheduling of Scientific applications in Distributed Grid and Cloud Environment
  • 31. Pricing aggressivenessDouble Auction-based Scheduling of Scientific applications in Distributed Grid and Cloud Environment
  • 32. Pricing aggressivenessDouble Auction-based Scheduling of Scientific applications in Distributed Grid and Cloud Environment

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