Web Service Discovery Mechanisms Looking for a Needle in a Haystack?

1. Web Service Discovery Mechanisms Looking for a Needle in a Haystack? Evangelos Sakkopoulos joint work with J. Garofalakis, Y. Panagis, A. Tsakalidis University of Patras, CEID & RA Computer Techonology Institute

2. Overview of Talk • Introduction • Description of Players • Discovery Architectures • Data Models • Quality of Service • Conclusions Research Academic Computer Technology Institute

3. The name of the game • Web Service (WS):interoperable S/W components that can be used in application integration and component based application development • WS Discovery: requester + middle agent = find • Find the WS matching certain functional criteria Research Academic Computer Technology Institute

4. Reasons for discovery + common problems Why: • Need for complex WS invocation patterns • Need to chose between several descriptions Problems: • Heterogeneities in Technical, Pragmatical, Ontological Level Research Academic Computer Technology Institute

5. Description of Players [catalogues] • Centralized repositories of WS Descriptions • UDDI – emerging protocol, v. 3.0 • SOAP APIs • XML representation for the registry • WSDL interface definitions • APIs Defs of various tech. models • Three types of info available in UDDI • White pages (contact info) • Yellow pages (WS categorization) • Green pages (Technological INformation) Research Academic Computer Technology Institute

6. Description of Players [P2P systems] • Distributed, Load balanced repositories • Typical P2P overlay Chord [Stoica et. al. 2001], Pastry [Rowstrom et. Al. 2001], CAN [Ratnasamy et. al. 2001] • Several WS Discovery systems have chosen Chord as overlay • WS Descriptions hashed and distributed over Chord Ring • Speed-R [Sivashanmugam et. al. 2004], uses combination of Ontological mapping and P2P (nodes have different roles and are controlled by ontologies) Research Academic Computer Technology Institute

7. Discovery Architectures (1) • Manual • A human queries and decides • Automatic • Discovery by a requester agent • Centralized • UDDI registry: Centralized, authoritative repository of service descriptions • Decentralized • Distant ancestors of Whois++, rWhois systems • UDDI Federations • P2P systems Research Academic Computer Technology Institute

8. Discovery Achitectures(2) • Following the standards: • Info is added on white or yellow pages • Modify green pages (design by contract) • Ignoring the standards • Active UDDI (a new WS for mediator) • Grid Computing • Industrial Standards • J2EE, MS .NET, Java-based APIs Research Academic Computer Technology Institute

9. Discovery Achitectures (3) Research Academic Computer Technology Institute

10. Data Models - The IR viewpoint • UDDI keyword matching = Boolean IR Model • Sajjanhar et. al., 2003: • Service Descriptions are modelled as texts, texts as vectors, a term-document matrix A is built • LSI is applied to A • Ability to query by similarity Research Academic Computer Technology Institute

11. Data Models - The IR viewpoint (cont’d) • Schmidt and Parashar, 2004 • WS Descriptions = d-dimensional point • Hilbert curve: Points are mapped to 1-d and assigned unique IDs • IDs hashed and distributed in a Chord • XChord, Li et. al. • P2P discovery • Descriptions extracted, hashed and distributed across Chord Research Academic Computer Technology Institute

12. Data Models- The Semantics Viewpoint • Desideratum: retrieve WS with similar functionality • Semantic WS descriptions with DAML-S OWL-S • Paolucci et. al., ISWC 2002 • An ontology for each WS (Service Profile) • Service Profile: Functional Attr. , Functional Descr. • Ontology  Subsumption and Semantic Matching • Matchmaker implemented as UDDI add-on • Sivashanmugam et. al., ISWC 2003 • Matching engine implemented with semantic additions to WSDL descriptions Research Academic Computer Technology Institute

13. Data Models- The Semantics Viewpoint (2) • Moreau et. al. 2002, • Agents are described as WS • Matching: structural validations of queries against XML service descriptions • Hu, NODe 2002, • Domain Ontologies and Operation Ontologies • Binding Ontology performs matching • Overhage, 2002 • Blue pages, a new UDDI section with semantic descriptions Research Academic Computer Technology Institute

14. Data Models – A taxonomy Research Academic Computer Technology Institute

15. Quality of Service Concerns • Quality of Web Service (QoWS): a rather neglected issue • First attempt to define: Ran, 2003 • QoWS parameters: • Computational Behavior: Latency, Accuracy, Throughput, Availability • Business Behavior: Invocation Cost, Company Reliability • Metadata Constraints: Location, Company Preference etc. Research Academic Computer Technology Institute

16. Discovery with QoWS • Ouzzani and Bouguettaya, IEEE Internet Computing, March 2004. • QoWS parameters are categorized as negative and positive. • QoS distance, measures advertised vs provided QoWS • Execution plan, an ordered execution sequence of WSs. • Selection performed of an optimum execution plan that maximizes provided QoWS Research Academic Computer Technology Institute

17. Conclusions • Surveyed work emphasizes binding and matching. • UDDI and P2P systems, the main players • Data models: classical IR to Ontologies • More emphasis to QoWS provisioning • Discovery not only for WS, web-based S/W components, too. Research Academic Computer Technology Institute

18. Thank you Inquiries: sakkopul@cti.gr