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Workflow Resource Allocation through Auctions

Workflow Resource Allocation through Auctions. Universitat de Girona. Albert Plà , Beatriz López, Javier Murillo. eXiT. Line up. Introduction WMS The Auction Experimentation & Results Conclusions. Introduction Workflow Management System Workflow Resource Allocation: The Auction

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Workflow Resource Allocation through Auctions

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  1. Workflow Resource Allocation through Auctions Universitat de Girona AILOG 2011 - Barcelona Universitat de Girona Albert Plà, Beatriz López, Javier Murillo eXiT

  2. Line up Introduction WMS TheAuction Experimentation & Results Conclusions • Introduction • Workflow Management System • Workflow Resource Allocation: The Auction • Workflow Agents: The Auctioneers • Resource Agents: The Bidders • Experimentation and Results • Conclusions and Future Work AILOG 2011 - Barcelona Universitat de Girona

  3. Introduction Introduction WMS TheAuction Experimentation & Results Conclusions AILOG 2011 - Barcelona Universitat de Girona

  4. Introduction Introduction WMS TheAuction Experimentation & Results Conclusions OrganizationInteractions Schedules & Deadlines DecentralizedProductionChain Business Processes CostReduction Resources Resources AILOG 2011 - Barcelona Universitat de Girona

  5. Introduction Introduction WMS TheAuction Experimentation & Results Conclusions • Decentralization of the production processes. • Distribute production plants • Service outsourcing • Third party elements • Some tasks can not be Scheduled (e.g. faults) • Unknown service providers schedule • Customer oriented production methodologies • Lean Manufacturing • Avoid unnecessary work • Interaction between customer & provider • Production under demand • Production flexibility • Resource allocation in real time AILOG 2011 - Barcelona Universitat de Girona

  6. Introduction Introduction WMS TheAuction Experimentation & Results Conclusions Dynamism Decentralization Third Party Oustourcing Contingency Robustness Customer Orientation Providers Privacy Process Planing: + Uncertainity + Complexity AILOG 2011 - Barcelona Universitat de Girona

  7. Introduction Introduction WMS TheAuction Experimentation & Results Conclusions Dynamism Decentralization Third Party Oustourcing Contingency Robustness Customer Orientation Providers Privacy Process Planing: + Uncertainity + Complexity AILOG 2011 - Barcelona Universitat de Girona

  8. Introduction Introduction WMS TheAuction Experimentation & Results Conclusions Unknown # of online workflows AILOG 2011 - Barcelona Universitat de Girona Dynamism Decentralization Third Party Oustourcing Contingency Robustness Customer Orientation Providers Privacy Process Planing: + Uncertainity + Complexity

  9. Example: Introduction WMS TheAuction Experimentation & Results Conclusions Internal technicians FaultReparation Outsource technicians ? … Company 1 Comp. 2 Comp. n Hospital devicemaintenanceservice AILOG 2011 - Barcelona Universitat de Girona

  10. Ourproposal: Introduction WMS TheAuction Experimentation & Results Conclusions • Resource allocation using: • Workflow Management System (WMS) • Multi-Ageng Systems (MAS) technolgoy • Auctions AILOG 2011 - Barcelona Universitat de Girona

  11. Ourproposal: Introduction Background? WMS TheAuction Experimentation & Results Conclusions Workflow Management System Auction Organization ResourceProviders AILOG 2011 - Barcelona Universitat de Girona

  12. Workflow Management System Introduction WMS TheAuction Experimentation & Results Conclusions AILOG 2011 - Barcelona Universitat de Girona

  13. Workflow Management System Introduction WMS TheAuction Experimentation & Results Conclusions Type: Technician A ResourcesCapacity: 2 Currentlyusedresources: 1 Pla A. et al. Petri Net BasedAgentsforCoordinatingResources. Rome 2011 • Workflows modeled using Resource-aware Petri Nets (RAPN) • Resource requirements included in the model AILOG 2011 - Barcelona Universitat de Girona

  14. Workflow Management System Introduction WMS TheAuction Experimentation & Results Conclusions WF Agent A ResourceAgent 1 WF Agent B ResourceAgent 2 … ResourceAgent n-1 ResourceAgent n WF Agent C WF Agent D Pla A. et al. Petri Net BasedAgentsforCoordinatingResources. Rome 2011 • Monitoring using agents [1] • 1 Workflow agent for each workflow typology • 1 Resource agent for each resource AILOG 2011 - Barcelona Universitat de Girona

  15. Workflow Management System Introduction WMS TheAuction Experimentation & Results Conclusions WorkflowAgent A ResourceType A ResourceAgent 1 ResourceAgent 2 Pla A. et al. Petri Net BasedAgentsforCoordinatingResources. Rome 2011 • A workflow agent monitors and manages all the instances of a workflow type • Call for auctions when they need resources AILOG 2011 - Barcelona Universitat de Girona

  16. Workflow Management System Introduction WMS TheAuction Experimentation & Results Conclusions ResoruceAgent A ResourceType A ResourceAgent 1 ResourceAgent 2 Pla A. et al. Petri Net BasedAgentsforCoordinatingResources. Rome 2011 • A workflow agent monitors and manages all the instances of a workflow type [1] • Call for auctions when they need resources AILOG 2011 - Barcelona Universitat de Girona

  17. Workflow Management System Introduction WMS TheAuction Experimentation & Results Conclusions • A workflow agent monitors and manages all the instances of a workflow type [1] • Call for auctions when they need resources ResoruceAgent A ResourceType A ResourceAgent 1 ResourceAgent 2 AILOG 2011 - Barcelona Universitat de Girona

  18. Workflow Management System Introduction WMS TheAuction Experimentation & Results Conclusions ResoruceAgent A ResourceType A AUCTION! ResourceAgent 1 ResourceAgent 2 • A workflow agent monitors and manages all the instances of a workflow type [1] • Call for auctions when they need resources AILOG 2011 - Barcelona Universitat de Girona

  19. Workflowresourceallocation: TheAuction Introduction WMS TheAuction Experimentation & Results Conclusions AILOG 2011 - Barcelona Universitat de Girona

  20. Workflow Agent: TheAuctioneer Introduction WMS TheAuction Experimentation & Results Conclusions • Differentattributtestobefullfilled • Time Restritctions (Starting & Ending Time) • ResourceCategory (E.g.TehcnicianLicense) • Minimizecosts AILOG 2011 - Barcelona Universitat de Girona

  21. Workflow Agent: TheAuctioneer Introduction WMS TheAuction Experimentation & Results Conclusions • Reverse SealedAuction • First Price • PenaltyMechanisms: • Fraudulentbids • Delays • AgreementRepudiation • AttributePromotion: • Differentstrategies • WinningDeterminationProblem (WDP) AILOG 2011 - Barcelona Universitat de Girona

  22. AuctioneersStrategies Introduction WMS TheAuction Experimentation & Results Conclusions • Balanced Strategy: • WDP: Lowest Bid Price • Balanced market price • Providers equilibrium • Decrease costs for workflow agent • Suitable for internal & external providers • + Delays AILOG 2011 - Barcelona Universitat de Girona

  23. AuctioneersStrategies Introduction WMS TheAuction Experimentation & Results Conclusions • DelayPreventionStrategy • WDP: Takesintoaccounttaskending time • Shortensworkflowtimings • Reduces number of delays • Indicatedfordealingwithinternalproviders • Arisescost • Fasterproviders can increasetheirprices AILOG 2011 - Barcelona Universitat de Girona

  24. ResourceAgents: TheBidders Introduction WMS TheAuction Experimentation & Results Conclusions • Characterizedby: • Theircategories (1 or more) • List of scheduledtasks (private agenda) • Estimation of times neededtoperformtasksbasedonpastexperience (mean, stddeviation, etc) AILOG 2011 - Barcelona Universitat de Girona

  25. ResoruceAgents: Thebidders Introduction WMS TheAuction Experimentation & Results Conclusions • TheBid: • Agentsevaluatetheir agenda • Find gaps for new tasks • Entertoauctiosn • Chooseprice (Agentcharacter): • Arisethepricewhenwinning • Decreasewhenlosing • Reinforcementlearning • Evaluatebenefits of winningtheauction • They can cancel scheduledactivitysifthebenefit of realizing a new taskcompensatesthecancellationpenalty. • Riskybids AILOG 2011 - Barcelona Universitat de Girona

  26. Experimentationand Results Introduction WMS TheAuction Experimentation & Results Conclusions AILOG 2011 - Barcelona Universitat de Girona

  27. Experimental Setup Introduction WMS TheAuction Experimentation & Results Conclusions • WorkflowSimulation • 200 t.u.simulations • Workflowprobabilityp = 0.2 • Evaluation: • Economiccost • Delaysproduced • Workload balance • Strategies: • BalancedStrategy (BS) • DelayPreventionStrategy (DPS) • Firstavailableresource of a sortedlist (FRQ) AILOG 2011 - Barcelona Universitat de Girona

  28. Experimental Setup Introduction WMS TheAuction Experimentation & Results Conclusions • Scenario 1: • 4 ResourceAgents • Eachresources can perform, at least, 3 differenttasks • Competitionbetweensomeresources • Workflow instances > resources • Scenario 2: • 4 ResourceAgents • Eachresource can performallthetasks • Highcompetitionbetweenallresources • Workflow instances >> resources AILOG 2011 - Barcelona Universitat de Girona

  29. Results Introduction WMS TheAuction Experimentation & Results Conclusions Scenario 1 Scenario 2 AILOG 2011 - Barcelona Universitat de Girona

  30. Results: Delays Introduction WMS TheAuction Experimentation & Results Conclusions Scenario 1 Scenario 2 AILOG 2011 - Barcelona Universitat de Girona

  31. Results: Costs Introduction WMS TheAuction Experimentation & Results Conclusions Workflow agentsbudged AILOG 2011 - Barcelona Universitat de Girona

  32. Results: Workload Balance Introduction WMS TheAuction Experimentation & Results Conclusions Balanced Strategy FIFO Resource Queue Scenario 2 AILOG 2011 - Barcelona Universitat de Girona

  33. Conclusions and FutureWork Introduction WMS TheAuction Experimentation & Results Conclusions AILOG 2011 - Barcelona Universitat de Girona

  34. Conclusions Introduction WMS TheAuction Experimentation & Results Conclusions • Howtoallocateinternal and foreignresourcesunderdemand in a decentralizedproductionprocess? • Workflow Management System • Business Process • Resources • MultiAgentSystems • Useful in distributedenvironments • Auctions • Minimizecosts • Reduce production times • Balance resourceoccupation AILOG 2011 - Barcelona Universitat de Girona

  35. Conclusions Introduction WMS TheAuction Experimentation & Results Conclusions • 2 Kind of agents: • ResourceAgents • Bidders • Workflow Agents • Auctioneers • Differentstrategies • Resourcecosts (BalancedStrategy) • Workflow timings (DelayPreventionStrategy) • Improve simple schedulesmethods AILOG 2011 - Barcelona Universitat de Girona

  36. Furtherwork Introduction WMS TheAuction Experimentation & Results Conclusions • Vickeryauctioningmechanism • Incentive compatibility • Fightcheatingagents • New auctioningstrategies • Multi-attribute • Improve MAS capabilities • Trust • Historical data AILOG 2011 - Barcelona Universitat de Girona

  37. Introduction WMS TheAuction Experimentation & Results Conclusions albert.pla@udg.edu AILOG 2011 - Barcelona Universitat de Girona

  38. Workflow Resource Allocation through Auctions Universitat de Girona AILOG 2011 - Barcelona Universitat de Girona Albert Plà, Beatriz López, Javier Murillo eXiT

  39. AILOG 2011 - Barcelona Universitat de Girona

  40. AILOG 2011 - Barcelona Universitat de Girona

  41. WMS Architecture AILOG 2011 - Barcelona Universitat de Girona

  42. Multiple Reactive Maintenance Intervention (MRMI) Assigning to in-house technicians Maintenance action generated in the system Ranking the action (assigning a level) Locating the source of the action Classifying the action Sequential Solution Technician 1 reparation Concurrent Solution Technician 2 reparation Technician 1 reparation Technician 2 reparation Device returned to the medical center Assigning to an external service provider Device Check Out Resoruces: TechnicianType A TechnicianType B AILOG 2011 - Barcelona Universitat de Girona

  43. T4 P4 T3 P1 P2 P3 T5 P5 T1 T2 AILOG 2011 - Barcelona Universitat de Girona

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