Post on 29-Dec-2015
Web Service Discovery Mechanisms Looking for a Needle in a Haystack?
Evangelos Sakkopoulos
joint work withJ. Garofalakis, Y. Panagis, A. Tsakalidis University of Patras, CEID& RA Computer Techonology Institute
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Technology Institute2
Overview of Talk
Introduction Description of Players Discovery Architectures Data Models Quality of Service Conclusions
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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
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Technology Institute4
Reasons for discovery + common problems
Why: Need for complex WS invocation
patterns Need to chose between several
descriptionsProblems: Heterogeneities in Technical,
Pragmatical, Ontological Level
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Description of Players [catalogues]
Centralized repositories of WS Descriptions
UDDI – emerging protocol, v. 3.01. SOAP APIs 2. XML representation for the registry 3. WSDL interface definitions
4. 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)
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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)
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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
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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
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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
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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
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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
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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
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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.
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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
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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.