Jorge Cardoso (1,2), John A. Miller (3), Casey Bowman (3), Christian Haas (2), Amit P.Sheth (4), Tom W. Miller (5)(1) CISU...
The importance of servicesManual Semi-automatic Fully Automated2013 Genessiz: Center for Large-Scale Service System Resear...
The importance of networks2013 Genessiz: Center for Large-Scale Service System Research 3World Wide Web Social NetworksLin...
Networks andVulnerability• Protecting just 4 nodesmade a system lessvulnerable• Left– all communicationsservers are couple...
…definitions…“A service network is defined as a graph structurecomposed of service systems which are nodesconnected by one...
Service Network Modeling_Business services__Business services__Business services__Business services__Business services_ _B...
Basic Building BlocksService Description• Service description• Follows Linked Data principles• Simplicity for computation ...
2013 Genessiz: Center for Large-Scale Service System Research 8www.internet-of-services.comhttp://www.linked-usdl.org/Link...
Service DescriptionModeling2013 Genessiz: Center for Large-Scale Service System Research 9http://aws.amazon.com/ec2/
:pricing_EC2_Small_EU_Windows_ReservedInstance_Light_1yr a price:PricePlan ;dcterms:description "Price plan for a Small EC...
The relationship problem…• Relations provided by RDFS,FOAF, SIOC, SKOS,…– rdfs:subClassOf,owl:EquivalentClass– owl:sameAs,...
Genessiz: Center for Large-Scale Service System Research2013 12
2013 Genessiz: Center for Large-Scale Service System Research 13Service Network AnalysisCentrality: 23
ACMECustomer RelationshipManagementACMEBusiness IntelligenceHerokuAmazonElastic BlockStoreBIMEService ProvidersService Cre...
Service Value Networks(SVN)Cooperative Models (t)Evolution Models (t)Open SemanticService Relationship(OSSR)Unified Servic...
Service Network Optimization2013 Genessiz: Center for Large-Scale Service System Research 161
Service Network Optimization• Optimal construction has two phases– Maximal color-compliant construction (1) and cost minim...
Service Network Optimization• Optimal construction has two phases– Maximal color-compliant construction (1) and cost minim...
Evolutionary Analysis• Hypothesis– Highly connected services increase theirconnectivity faster than less connected ones– P...
OSSN Formal Modeling2012 Genessiz: Center for Large-Scale Service System Research 20
OSSN and Preferential Attachment• Use USDL value proposition as apreferential attachment.– usdl:valueproposition– Service ...
OSSN and Preferential Attachment• Objective– Forecast the evolution of a service network– The market share of each service...
OSSN and Preferential Attachment• The service marketshare is represented inthe figure at t = 3.• What will happen to thema...
OSSN and Preferential Attachment• The service marketshare is represented inthe figure at t = 3.• What will happen to thema...
Cooperative AnalysisSelf-organizing system• Explore the applicability of systemdynamics– Using mathematical expressions to...
Total ServicesKPI Gain perIndividualService-++Sk KPI =Resource Limit+Si KPI =# servicesSj KPI =# servicesSj KPI = Net gain...
OSSN and System Dynamics• If the two services Si and Sj overuse the shared service Sk,– It will become depleted and all th...
ServiceValue Networks• Previous three approaches considered structural aspects, SVN take considerparticipants’ behavior– F...
ServiceValue Networks• Mechanism Design perspective– How we can select a combination of servicesthat best satisfies the co...
ServiceValue Networks• Two step mechanism– Calculation of the allocation (1)– Calculation of the payments (2)• (1) Calcula...
ServiceValue Networks• Properties of the mechanism– Allocative efficient: it selects the bestcombination of atomic service...
Conclusions• Service Networks– Large scale, open, dynamic, and highly distributed• Service Network Modeling– Use Linked US...
2013 Genessiz: Center for Large-Scale Service System Research 33Thank you.Questions?
References3.Von Bertalanffy, L.: General System Theory:Foundations, Development, Applications.TheInternational Library of ...
References• [CPL+13] Cardoso, J.; Pedrinaci, C. and Leenheer, P. D Open Semantic Service Networks:Modeling and Analysis.In...
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Open Service Network Analysis

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Understanding how services operate as part of large scale global networks, the related risks and gains of different network structures and their dynamics is becoming increasingly critical for society. Our vision and research agenda focuses on the particularly challenging task of building, analyzing, and reasoning about global service networks. This paper explains how Service Network Analysis (SNA) can be used to study and optimize the provisioning of complex services modeled as Open Semantic Service Networks (OSSN), a computer-understandable digital structure which represents connected and dependent services.

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Open Service Network Analysis

  1. 1. Jorge Cardoso (1,2), John A. Miller (3), Casey Bowman (3), Christian Haas (2), Amit P.Sheth (4), Tom W. Miller (5)(1) CISUC/Dept. Informatics Engineering, University of Coimbra, Portugal(2) Karlsruhe Service Research Institute, Karlsruhe Institute of Technology, Germany(3) Dept. of Computer Science, University of Georgia, USA(4) Kno.e.sis Center, Wright State University, USA(5) Dept. of Economics, Finance and Quantitative Analysis, Kennesaw State University, USA// 01 May 2013 //First Int. IFIP Working Conf. on Value-Driven Social Semantics & Collective Intelligence (VaSCo)Paris, FranceOpen Service Network AnalysisDepartamento de Engenharia InformáticaFCTUC FACULDADE DE CIÊNCIAS E TECNOLOGIA da UNIVERSIDADE DE COIMBRA
  2. 2. The importance of servicesManual Semi-automatic Fully Automated2013 Genessiz: Center for Large-Scale Service System Research 2ServiceeconomiesSelf-servicesConsulting IT Services Cloud servicesSoftware
  3. 3. The importance of networks2013 Genessiz: Center for Large-Scale Service System Research 3World Wide Web Social NetworksLinked Data…energy grids, water systems, wireless mobile networks...Financial/Political Networks Food chain NetworksRailway Network
  4. 4. Networks andVulnerability• Protecting just 4 nodesmade a system lessvulnerable• Left– all communicationsservers are coupled to thepower grid• Right– Four are decoupled– Lower vulnerability• Circles represent a power grid• Diamonds a communicationsnetwork• Colors show the probability that anode fails after 14 servers fail2012 Genessiz: Center for Large-Scale Service System Research 4Source: C.M. Schneider et al/arxiv.org 2011; Map: Geoatlas/graphi-ogre, adapted by T. Dubéhttp://www.sciencenews.org/view/feature/id/343939/description/When_Networks_Network
  5. 5. …definitions…“A service network is defined as a graph structurecomposed of service systems which are nodesconnected by one or more specific types ofservice relationship, the edges.”2013 Genessiz: Center for Large-Scale Service System Research 5”A service system is afunctional unit with aboundary through whichinteractions occur withthe environment, and,especially, with otherservice systems.”!
  6. 6. Service Network Modeling_Business services__Business services__Business services__Business services__Business services_ _Business services__Business services__Business services__Business services__Business services__Business services_ _Business services__Business services__Business services__Business services__Business services__Business services__Business services__Business services__Business services__Business services__Business services__Business services__Business services__Business services__Business services__Business services_2013 Genessiz: Center for Large-Scale Service System Research 6
  7. 7. Basic Building BlocksService Description• Service description• Follows Linked Data principles• Simplicity for computation andmodeling• Reuse existing vocabularies• Means for publishing andinterlinking distributed data• [CPL+13][CM12][CPL+12][CBM+10]Service RelationshipOpen Semantic ServiceRelationship (OSSR)• Relationship description• Interconnects services• Multi-layer• Follows Linked Data principles• Reuse existing vocabularies• Means for interlinking servicedescriptions/systems2013 Genessiz: Center for Large-Scale Service System Research 7
  8. 8. 2013 Genessiz: Center for Large-Scale Service System Research 8www.internet-of-services.comhttp://www.linked-usdl.org/Linked USDL:CoreLinked USDL:PricingLinked USDL:SECLinked USDL:SLA
  9. 9. Service DescriptionModeling2013 Genessiz: Center for Large-Scale Service System Research 9http://aws.amazon.com/ec2/
  10. 10. :pricing_EC2_Small_EU_Windows_ReservedInstance_Light_1yr a price:PricePlan ;dcterms:description "Price plan for a Small EC2 Reserved Instance in Europe with Windows, lightutilization and a one year contract duration."@en ;price:hasContractDuration[ a gr:QuantitativeValue ;gr:hasValueInteger "1" ;gr:hasUnitOfMeasurement "ANN" ] ;price:hasBillingCycle[ a gr:QuantitativeValue ;gr:hasValueInteger "1" ;gr:hasUnitOfMeasurement "MON" ] ;price:hasPriceComponent:priceComponent_Small_EU_Windows_ReservedInstance_Light_1yr_General_Upfront ,:priceComponent_Small_EU_Windows_ReservedInstance_Light_1yr_General_Hourly ,:priceComponent_Small_EU_Windows_ReservedInstance_Light_1yr_General_Upfront a price:PriceComponent;dcterms:title "General costs upfront"@en ;dcterms:description "One-time fee for general usage of the instance."@en ;price:isLinkedTo…price:hasPrice[ a gr:UnitPriceSpecification ;gr:hasCurrency "USD" ;gr:hasCurrencyValue "69" ;gr:hasUnitOfMeasurement "C62" ] .@prefix price: <http://www.linked-usdl.org/ns/usdl-pricing#>2013 Genessiz: Center for Large-Scale Service System Research 10
  11. 11. The relationship problem…• Relations provided by RDFS,FOAF, SIOC, SKOS,…– rdfs:subClassOf,owl:EquivalentClass– owl:sameAs, rdfs:seeAlso,foaf:knows, …• Limited and not suitable toconnect all the world’s services.• One approach– Connect services via multipletypes of connection layers– Capture the inherent richness andcharacteristics of services• This goes well beyond theconnection of services treatedsimply as unidimensional nodes2013 Genessiz: Center for Large-Scale Service System Research 11Cardoso, J. Modeling Service Relationships for Service Networks. In 4th International Conference on Exploring Service Science (IESS 1.3),pages 114-128, Springer, LNBIP, Porto, Portugal, 2013.
  12. 12. Genessiz: Center for Large-Scale Service System Research2013 12
  13. 13. 2013 Genessiz: Center for Large-Scale Service System Research 13Service Network AnalysisCentrality: 23
  14. 14. ACMECustomer RelationshipManagementACMEBusiness IntelligenceHerokuAmazonElastic BlockStoreBIMEService ProvidersService CreatorsService ConsumersService ProvidersService AggregatorsService MarketplaceMotivation Scenario
  15. 15. Service Value Networks(SVN)Cooperative Models (t)Evolution Models (t)Open SemanticService Relationship(OSSR)Unified ServiceDescription Language(*- USDL)Open Semantic Service Networks (OSSN)Service networksmodelsmodelsmodelsService systemOptimization (?)Service Network AnalysisApproaches1234
  16. 16. Service Network Optimization2013 Genessiz: Center for Large-Scale Service System Research 161
  17. 17. Service Network Optimization• Optimal construction has two phases– Maximal color-compliant construction (1) and cost minimization (2)• Phase 1:– Build a service network from three sets of nodes, atomic services (sources),composite services (intermediate nodes), and consumers (sinks).– Starting with the sources, all intermediate and consumer nodes are connectedby edges that are color compliant, e.g., if an intermediate node needs a blueinput and green input and there exist sources producing/outputting thesecolors, then this intermediate node is added to the graph.– This process continues through k stages, the maximum number of stages (i.e.,distance from source to sink) desired.2013 Genessiz: Center for Large-Scale Service System Research 17
  18. 18. Service Network Optimization• Optimal construction has two phases– Maximal color-compliant construction (1) and cost minimization (2)• Phase 2:– Once the graph has been created, it can be reduced to an optimal form– Objective function: the cost of the network, and decision variables representthe flow of material through the network.– The flow is constrained by the supply, production, or demand capacity of thenodes in the network.– A Linear Programming algorithm such as the Simplex algorithm, can be usedto find the optimal values for the decision variables.– These values determine the optimal amount of flow through the network andthe value of the objective function estimates the minimum cost.2013 Genessiz: Center for Large-Scale Service System Research 18
  19. 19. Evolutionary Analysis• Hypothesis– Highly connected services increase theirconnectivity faster than less connected ones– Preferential attachment (PA) phenomenon– Only local information• Preferential attribute– e.g. price, quality, or availability2012 Genessiz: Center for Large-Scale Service System Research 192
  20. 20. OSSN Formal Modeling2012 Genessiz: Center for Large-Scale Service System Research 20
  21. 21. OSSN and Preferential Attachment• Use USDL value proposition as apreferential attachment.– usdl:valueproposition– Service value is judged from the perspectiveof consumers as they compare servicesamong the alternatives.• Let us assume– price is the value proposition (local rule)2012 Genessiz: Center for Large-Scale Service System Research 21
  22. 22. OSSN and Preferential Attachment• Objective– Forecast the evolution of a service network– The market share of each service is:2012 Genessiz: Center for Large-Scale Service System Research 22
  23. 23. OSSN and Preferential Attachment• The service marketshare is represented inthe figure at t = 3.• What will happen to themarket if the conditionsare not changed*?• According to Bassmodel, the leadingservice will reaches afixedpoint market shareaccording to:2012 Genessiz: Center for Large-Scale Service System Research 23*the value propositions of remain the same
  24. 24. OSSN and Preferential Attachment• The service marketshare is represented inthe figure at t = 3.• What will happen to themarket if the conditionsare not changed*?• According to Bassmodel, the leadingservice will reaches afixedpoint market shareaccording to:2012 Genessiz: Center for Large-Scale Service System Research 24*the value propositions of remain the same
  25. 25. Cooperative AnalysisSelf-organizing system• Explore the applicability of systemdynamics– Using mathematical expressions to model therelationships of SN– Instead of looking at causes and their effects inisolation (e.g. PA)• The next figure– Service systems Si, Sj , Sk,– Links illustrating internal and externalrelationships2012 Genessiz: Center for Large-Scale Service System Research 253
  26. 26. Total ServicesKPI Gain perIndividualService-++Sk KPI =Resource Limit+Si KPI =# servicesSj KPI =# servicesSj KPI = Net gains++++Si KPI = Net gains+++--+Service system SiServicesystem SkService system Sja)SN and System DynamicsOSSROSSR OSSROSSR Causal links connect KPIsfrom different services’ andwithin services.(’Tragedy of the Commons’archetype )USDLUSDLUSDL• Positive Feedback (+)Reinforcement and amplification• Negative Feedback (-)Counteracts perturbations andstabilizes
  27. 27. OSSN and System Dynamics• If the two services Si and Sj overuse the shared service Sk,– It will become depleted and all the providers will experiencediminishing benefits• Services Si and Sj– To increase net gains, both providers increase the availability ofservice instances– As the number of instances increases, the margin decreases andthere is the need to increase even more the number of instancesavailable– As the number of instances increases, the stress on the availability ofservice Sk is so strong that the service collapses or cannot respondanymore as needed– At that point, service Si and Sj can no longer fully operate and the netgain is dramatically reduced for all the parties involved as shown inthe following figure2012 Genessiz: Center for Large-Scale Service System Research 27TimeSi
  28. 28. ServiceValue Networks• Previous three approaches considered structural aspects, SVN take considerparticipants’ behavior– For example, depending on the market mechanism of a service marketplace, providersmight report their service characteristics (such as price) untruthfully to increase sales• Consumers request services– Certain functionalities– Have preferences (e.g. an acceptable price range, availability thresholds, etc.)2013 Genessiz: Center for Large-Scale Service System Research 28SVNs componentsAttributes: availability,throughput, latency,and price.4
  29. 29. ServiceValue Networks• Mechanism Design perspective– How we can select a combination of servicesthat best satisfies the consumer requirements?• Complex service auction– Maximize the welfare of the SVN– Sum of consumer and provider utilities.• Provider utility = revenue - costs of service• Consumer utility = valuation - price• Valuation = distance between request and offer2013 Genessiz: Center for Large-Scale Service System Research 29
  30. 30. ServiceValue Networks• Two step mechanism– Calculation of the allocation (1)– Calculation of the payments (2)• (1) Calculation of the allocation– Computes the various combinations of atomic services to the desired aggregatedservice.– Select the aggregated service with the highest (positive) difference betweenconsumer valuation minus the costs of the atomic services.• (2) Calculation of the payments:– Implement a Vickrey-Clarke-Groves (VCG) payment scheme to determine theactual payments to the providers– VCG motivate providers to report the attributes of their services truthfully– Rewards providers according to their relative importance (added value) to the SVN,which means they can receive an additional discount on their service provisioningprice.2013 Genessiz: Center for Large-Scale Service System Research 30
  31. 31. ServiceValue Networks• Properties of the mechanism– Allocative efficient: it selects the bestcombination of atomic services given theconsumer preferences.– Strategy-proof: the dominant strategy forservice providers is to submit their serviceattributes truthfully to the marketplace2013 Genessiz: Center for Large-Scale Service System Research 31
  32. 32. Conclusions• Service Networks– Large scale, open, dynamic, and highly distributed• Service Network Modeling– Use Linked USDL for open service modeling– Use the Open Semantic Service Relationship (OSSR) model– Results in Open Semantic Service Networks (OSSN)• Service Network Analysis– Allocation optimization– Evolutionary analysis– Cooperative analysis– Value analysis2013 Genessiz: Center for Large-Scale Service System Research 32
  33. 33. 2013 Genessiz: Center for Large-Scale Service System Research 33Thank you.Questions?
  34. 34. References3.Von Bertalanffy, L.: General System Theory:Foundations, Development, Applications.TheInternational Library of Systems Theory and Philosophy. Braziller (2003)8.Yule, U.: A mathematical theory of evolution based on the conclusions of dr. j. c. willis. Phil.Trans.Roy. Soc. Lond. 213(2), 21–87 (1925)12. J. Gordijn, E.Yu, and B. van der Raadt, e-service design using i* and e3value modeling, IEEESoftware, vol. 23, pp. 26-33, 2006.13. H. Akkermans,Z. Baida, J. Gordijn, N. Pena, A. Altuna, and I. Laresgoiti,Value webs: Usingontologies to bundle real-world services," IEEE Intelligent Systems, vol. 19, no. 4, pp. 57--66, Jul.2004.14. O. Danylevych, D. Karastoyanova, and F. Leymann, Service networks modelling: An soa & bpmstandpoint, Journal of Universal Computer Science, vol. 16, no. 13, pp. 1668--1693, jul 2010.15.V. Allee, Reconfiguring the value network," Journal of Business Strategy, vol. 21, no. 4, pp. 1-6,2000.16. N.Weiner and A.Weisbecker,A business model framework for the design and evaluation ofbusiness models in the internet of services,in Proceedings of the Annual SRII Global Conference,Washington,DC, USA, 2011, pp. 21-33.17. R. C. Basole and W. B. Rouse, Complexity of service value networks: Conceptualization andempirical investigation, IBM Systems Journal, vol. 47, no. 1, pp. 53-70, 2008.2012 Genessiz: Center for Large-Scale Service System Research 34
  35. 35. References• [CPL+13] Cardoso, J.; Pedrinaci, C. and Leenheer, P. D Open Semantic Service Networks:Modeling and Analysis.In 4th International Conference on Exploring Service Science (IESS1.3), pages 141-154, Springer, LNBIP, Porto, Portugal, 2013.• [Car13] Cardoso, J. Modeling Service Relationships for Service Networks. In 4th InternationalConference on Exploring Service Science (IESS 1.3), pages 114-128, Springer, LNBIP, Porto,Portugal, 2013.• [CM12] Cardoso, J. and Miller, J. A Internet-Based Self-Services: from Analysis and Design toDeployment. In The 2012 IEEE International Conference on Services Economics (SE 2012),IEEE Computer Society, Hawaii, USA, 2012.• [CPL+12] Cardoso, J.; Pedrinaci, C.; Leidig,T.; Rupino, P. and Leenheer, P. D Open semanticservice networks.In The International Symposium on Services Science (ISSS 2012), pages 1-15,Leipzig, Germany, 2012.• [CBM+10] Cardoso, J.; Barros, A.; May, N. and Kylau, U.Towards a Unified Service DescriptionLanguage for the Internet of Services: Requirements and First Developments. In IEEEInternational Conference on Services Computing, IEEE Computer Society Press, Florida, USA,2010.2013 Genessiz: Center for Large-Scale Service System Research 35
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