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SmartER Semantic Cloud Sevices

SmartER Semantic Cloud Sevices. Karuna P Joshi University of Maryland, Baltimore County Advisors: Dr . Tim Finin , Dr. Yelena Yesha. Agenda . Introduction and Motivation Service lifecycle Collaboration with IBM Collaboration with NIST. Cloud Computing : The present.

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SmartER Semantic Cloud Sevices

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  1. SmartER Semantic Cloud Sevices Karuna P Joshi University of Maryland, Baltimore County Advisors: Dr. Tim Finin, Dr. Yelena Yesha

  2. Agenda • Introduction and Motivation • Service lifecycle • Collaboration with IBM • Collaboration with NIST

  3. Cloud Computing : The present • New paradigm for IT services delivery • IaaS, PaaS, SaaS, …… , XaaS • Focus is on “virtualizing” resources • Great progress in dynamic provisioning at hardware resource level • Software/Service is still relatively statically provisioned • Gaps in current work • Lack of Cloud “service engineering” • Managing the entire lifecycle automatically

  4. Future Vision for Cloud • Virtualized Services on the Cloud • Service dynamically composed - On Demand composition • Service structure/components not pre-determined • Multiple provisioning. • Moving from totally manual to mostly automatic • needed if we truly want to leverage the cloud and service virtualization capabilities and efficiencies

  5. Key Open Research Issues • Current cloud research focused on • Improving cloud infrastructure – Virtual machines, Cloud OS etc. • Semantic description of services, and even some composition work • Limited research on how to use the cloud services efficiently • Most steps in service negotiation, acquisition, and consumption/monitoring still require significant human intervention • Difficult to manage service quality especially of composed services created by different providers

  6. Key Contributions of My Dissertation A semantically rich, policy-based framework can be used to automate the lifecycle of virtualized services on the cloud • Use semantic web languages/technologies • Proposed an integrated lifecycle of virtualized services on the Cloud • Negotiation for cloud service acquisition by constraint relaxation • Service quality framework

  7. Service Lifecycle Methodology • Our proposed methodology divides Service processes Lifecycle on the Cloud into Five Phases • Requirements, Discovery, Negotiation, Composition and Consumption • This Methodology is applicable on any cloud deployment. • We have developed high level ontologies for the five phases that enables automation. • available in OWL at http://ebiq.org/o/itse/1.0/itso.owl

  8. Service Requirements Service Discovery Service Negotiation Service Composition Service Consumption CONSUMER SERVICE CLOUD Phases of IT Services Lifecycle Service specified Provider(s) identified New Service needed Contract signed Service delivered

  9. Service Requirements Requirements for a service will include • Functional specifications (tasks to be automated) • Technical Policy specifications • Human Agent Policy • Security Policy • Data Quality Policy • Service Compliance Policy

  10. High Level Ontology for Requirements Phase

  11. Service Discovery • Services search/discovery engine used to search available services that match the specifications • Identify gaps that exist in services discovered • A central registry, similar to UDDI, will certify a service provided.

  12. High Level Ontology for Discovery Phase

  13. Service Negotiation • Discussion and agreement that the Service provider and consumer have regarding the Service. • Service Level Agreements (SLA) finalized between consumer and provider • Quality of Service (QoS) decided between primary provider and component providers.

  14. High Level Ontology for Negotiation Phase

  15. Service Composition Phase • One or more services provided by one or more providers are combined and delivered as a single Service • SLA and QoSfinalized in the negotiation phase used for determining service components and it’s orchestration or the sequence of execution of these components • We reuse OWL-S ontology

  16. High Level Ontology for Composition Phase • Class: Provider • Service list • Description • Class: Service Level Agreement • SLA Name • Description • SLA Metrics • Penalty • Class: • Specification • Name • Description • Class : Quality of Service (QOS) • QOS Name • Description • QOS Metrics • Penalty Class : Service Contract Part of composes Determines Refers to Class : Service Class : Dependent Service Sub-Contract part of part of Part of Class : OWL-S – Composite Process Class: Dependent Service Refers to

  17. Service Consumption Phase • Composed Service is consumed and monitored in this phase • Key measures like Service Performance and reliability are monitored using automated tools. • SLA, QoS determine performance of the service • Phase includes Service Delivery, Service payment • Customer Satisfaction is tracked in this phase

  18. High Level Ontology for Service Consumption Phase

  19. Collaboration with NIST • US government agency NIST working on standardizing cloud computing • Member of Reference architecture and Taxonomy groups • Prototype for NIST • Automation of Cloud Storage Service acquisition, consumption /monitoring. • Using Service lifecycle Ontologies developed by us. • Platform: using SPARQL, RDF, Web technologies – Perl, HTML. • NIST Cloud Computing workshop, Nov 2-4 2011.

  20. Some Policies/Constraints … • Cloud security – would like to mandate policies at the Cloud hardware level • Data security policies • US government compliance policies • User authentication policy : FIPS 140-2 is a standard used to accredit cryptographic modules. • Trusted Internet Connection mandated to optimize individual external connections. • Want to be interoperable across Cloud platforms

  21. Prototype Architecture Cloud user User Interface <rdf> Rfs description </rdf> Final SLA Service Translate to machine process able format Cloud Service Procurer module Discover service SLA negotiation Service URI Respond Cloud <rdf> SLA description </rdf> Cloud Provider 2 Cloud Provider 1 Cloud Provider 3 Joseki SPARQL endpoint Joseki SPARQL endpoint Joseki SPARQL endpoint Virtual Service Instance (Eucalyptus/Bluegrit) Virtual Service Instance (Eucalyptus/Bluegrit) Virtual Service Instance (Eucalyptus/Bluegrit)

  22. NIST prototype demo

  23. IBM collaboration : Future directions • Collaborating with Dr. Rindos and his team • Looking for cloud interfaces to validate Framework and Ontology

  24. Summary • For broader adoption of cloud computing, we need to automate cloud service processes • Developed an integrated methodology to acquire, consume and monitor services on the cloud. • Future work: working on more complex acquisition/negotiation policies from some international financial organizations, etc. • Ontologies in public domain. • Publications available at http://ebiq.org/j/93

  25. “Request for Service” Identify functional and technical specifications Determine domain, data type and it’s acceptable quality levels CONSUMER SERVICE CLOUD Detailed Processes: Service Life cycle Service Discovery Engine Service Certification List of service providers with advertised service, service levels and cost Service Level Agreement (SLA) between consumer and primary service provider Quality of Service (QoS) contracts between primary service providers and dependent services Dependant services Service composed Service Monitoring Service packaged, delivered – one time or periodically as needed Service consumed Service payment

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