Enhancing Service Selection by Semantic QoS

1. Enhancing Service Selection by Semantic QoS Henar Muñoz Frutos Telefónica I+D

2. Introduction Proposed Approach Implementation Conclusions and Future Directions

3. Context • Marketplace model: customers and providers interact for trading services • Introduction of Grid and Cloud technologies • New services included: infrastructureservices • Services: Storage, computing, infrastructure, software as a Service • Provided by Amazon, Google, HP… • Services encapsulate resources • Resources: machines, hard disk, applications, licenses • Key element: Service Selection based on QoS metrics • Due to the increase of functionally similar services • Due to the importance of non-functional properties: QoS metrics availability, performance, price, reliability, infrastructure properties • To find the best service to meet user requirements and assure QoS

4. Context • Important is to have a contract between the involved entities (customer-providers) • Need Service Level Agreement • terms for the provision of the service (service description), • Quality of service (QoS) level to be maintain, • Information about resources to be provided, • the liability to compensation if SLAs are not met. • SLA templates used for achieving an agreement between customers and provider specifying the terms under the provision of the service • SLA templates can be used as input for the service selection based on QoS metrics

5. Problemstatement • Main SLA specifications • WS-Agreement (OGF-GRAAP)-WSLA (IBM) • They covers the syntacticaspects in the description of SLA: • a schema for specifying an agreement and an agreement template, • no focus on vocabulary domain • WS-Agreement non-goals: Defining Specification of metrics associated with agreement parameters i.e., how and where these are measured • Specification assumes that other complimentary specifications will address these requirements • Current SLA specifications lack in interoperability: • Open marketplace: Providers and consumers are collaborating on a global scale competing for offering and consuming services • Different terminologies to describe the vocabulary domain (performance vs. response time) • Different language (performance vs. rendimiento)

6. Example • ANSYS request • CPUName: IntelCore Duo • CPU Speed: 2 GHz • Capacity: 400 MB • Price: 27 euros per day • DiskSpace: 250GB CUSTOMER Software engineering company • RAMMemory: 7.5 GB • ComputeUnit: 4 ECU • Storage: 850GB • Platform: 64 bit • Price: $0.4 per instance hour • MemoryPerTask: 7.5 GB • ClockCPUSpeed: 100 MHz / process • StorageCapability: 850GB • Cost: 5 euros/task/hour PROVIDERS Cloud and Grid providers AMAZON BSC

7. Objectives • Improve interoperability between service providers and clients • Providing semantic interoperability by the introduction of semantic annotations • Beyond syntax to semantics, mapping of data exchanged between the involved parties • Be backwards compatible • Compatible with current SLA specification e.g. WS-Agreement, WSLA • Compatible with current components (which do not understand the specification…) • If specification is used, then extra reasoning is feasible • If NOT then the process continues normal operation • A lightweight approach, so that, a easy way for providers to introduce these annotations. • Increase automation in the selection process to reduce human intervention

8. Introduction Proposed Approach Related Work Implementation Conclusions and Future Directions

9. Proposed Approach Specification for semantic Annotations (SA-SLA) - Backwards compatible - Lightweight approach Conceptual model - QoS ontology Implementation - Semantic Enhanced service Selection (SESS) • Selection algorithm • ranking services • taken from [Wang2006]

10. SA-SLA Introduction of semantic annotations in current SLA template files Based on SA-WSDL WS-Agreement + WSLA compatible Allow for annotating SLA description with pointers to semantic concepts Annotation of: SLA Parameters. Metrics RDF, OWL, WSML Semantic descriptions QoS metrics SLA terms modelReferences SchemaMappings SA-SLA Non-semantic descriptions SLA template Metric Parameter SLO

11. SA-SLA

12. ConceptualModel • Framework capturing the QoS provided by the suppliers and required by the customer to match between the two • Conceptual model in QoS which is shared by customers and providers and formalized as OWL • It can be extended by domain requirements (domain specific) • QoS ontology: specify SLA parameters and metrics for infrastructure services and their relationships • Based on [Wang2006], [Lee2003], [Tsesmetzis2006], [Ren2007] • QoS categorization: infrastructure, system, network, and security and cost

13. QoSontology

14. Conceptual Model • To solve the terminology problem (different terms for the same concept) • Simple Knowledge Organization System (SKOS) • Standard way to represent knowledge organization using RDF • SKOS is used for solving terminology problem <rdf:Description rdf:about="http:// brein.com/ontology/Upper/QoS#ResponseTime"> <skos:inScheme rdf:resource="http://eu-brein.com/thesaurus/QoSmetrics"/> <rdf:type rdf:resource="http://www.w3.org/2004/02/skos/core#Concept"/> <skos:prefLabel xml:lang="en">Response Time</skos:prefLabel> <skos:altLabel xml:lang="es">Tiempo de Respuesta</skos:altLabel> </rdf:Description>

15. Introduction Proposed Approach Implementation Conclusions and Future Directions

16. Architecture Comon conceptual model SA-SLA(WS-AgreementWSLA) SESS SESS SLAframework SLAframework Local domain knowledge Local domain knowledge

17. Architecture SA-SLA SA-SLA Customer Request Provides Offers Semantic Enhanced Service Selector TSLA Parser Local domain ontology SKOS representation TSLA Selector Ontology Manager SKOS Manager SLA template scores

18. Implementation • Ontologies • Common conceptual model: OWL • Local knowledge: OWL + RDF (SKOS) • Local knowledge repository • Query engine: Jena • Query language: SPARQL • Reasoner: Pellet • Semantic Enhanced Service Selector • Parse the SLA templates files (JAXB and XPATH) and • match providers offers with customers’ requirements (selection algorithm taken from [Wang2006]) • Interact with local domain repository for semantic support (create SLA instances, obtain local metrics)

19. Introduction Proposed Approach Implementation Conclusions

20. Conclusions • The increasing number of functionally similar services requires non-functional selecting process • Non-functional properties as QoS which are described as part of the SLA templates files • The introduction of semantic annotations in current SLA specifications allows solving the QoS metric definition problem • Using semantic technologies in a non-intrusive way addresses the issue of backwards compatibility and eases development of tools • Our proposal is based on existing specifications (WS-Agreement, SAWSDL)

21. References • [Wang2006] Wang, X, Vitvar, T., Kerrigan, M., and Toma, I.; A QoS-aware selection model for semantic Web Services. In 4th International Conference on Service Oriented Computing (ICSOC 2006), Chicago, USA, Dec. 2006. • [Lee2003] Lee, K, Jeon, J, Lee, W, Jeong, S., and Park, S., QoS for Web Services: Requirements and Possible Approaches, W3C Working Group Note 25, 2003. http://www.w3c.or.kr/kroffice/TR/2003/ws-qos/ • [Tsesmetzis2006] Tsesmetzis, D. T., Roussaki, I. G., Papaioannou, I. V., and Anagnostou, M. E. 2006. QoS awareness support in Web-Service semantics. AICT-ICIW. IEEE Computer Society, Washington, 128. • [Ren2007] Ren, K.; Jinjun Chen; Tao Chen; Junqiang Song; Nong Xiao; Grid-Based Semantic Web Service Discovery Model with QoS Constraints, Semantics, Knowledge and Grid, Third International Conference on 29-31 Oct. 2007 Page(s):479 – 482

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