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AHM2006, RSSM: A Rough Sets based Service Matchmaking Algorithm Bin Yu and Maozhen Li School of Engineering and Design.

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Presentation on theme: "AHM2006, RSSM: A Rough Sets based Service Matchmaking Algorithm Bin Yu and Maozhen Li School of Engineering and Design."— Presentation transcript:

1 AHM2006, RSSM: A Rough Sets based Service Matchmaking Algorithm Bin Yu and Maozhen Li School of Engineering and Design Brunel University Uxbridge, West London

2, Nottingham2 Outline l Service Oriented Architecture –Service Oriented Grids l Web/Grid Service Discovery Methods l RSSM: Service Matchmaking with Rough Sets –Problems RSSM tries to solve –How it works –Preliminary results achieved

3, Nottingham3 Service Oriented Architecture (SOA) l SOA is emerging as the mainstream architecture for developing next generation interoperable Grid systems –Facilitated by OGSA, a standard architecture for developing service oriented Grid systems –Enabled by Web services technologies such as WSDL, SOAP, WSRF, WS-N and many others. –Engineered with technologies such as Apache Axis, GT4, WSRF.NET l SOA define standard interfaces and protocols that allow developers to encapsulate resources (computers, data, storage, software, instruments) as services l Benefits of SOA –Makes future heterogeneous Grid systems interoperable using open standard technologies –Facilitates service discovery for use by a wider user community

4, Nottingham4 Service Oriented Grids l What is a service? –A service is a software component that >Has a rich describable interface (e.g. WSDL) >Can be advertised, discovered, composed, located via computer programs not by human beings >Has operations on underlying resources l Another Grid definition in the context of SOA –A Grid is a large scale distributed system that couples a bunch of services utilising various resources on the Internet

5, Nottingham5 Service Discovery l UDDI –An industrial standard for Web services registration and discovery –Major Limitation: Only supports keyword match l Service discovery with Semantic Web technologies –UDDI-M, OWL-S, UDDI/OWL-S, WSMO >Using metadata to annotate service entities (properties), and using ontologies to describe the relationships between metadata >Relationships of service properties include exact, plugin, subsume, nomatch.

6, Nottingham6 Introducing RSSM l Service Matchmaking with Rough Sets –Rough sets is a mathematic tool that can be used to find knowledge from incomplete data sets l Problems RSSM tries to solve –Be able to deal with uncertainty of service properties when matching service advertisements with service requests –This issue has never been explored before l Why this issue exists? –Because of the scale of Grid, service providers may advertise services independently >using independent properties to describe services –and same to service requesters

7, Nottingham7 How RSSM Works Irrelevant Property Reduction Dependent Property Reduction Advertised Domain Services Domain Ontology Service Matching and Ranking A Service Query Matched Services 1 2 34 5 6 7 8 9 10

8, Nottingham8 Irrelevant Service Property Reduction

9, Nottingham9 Dependent Service Property Reduction l By dynamically reducing irrelevant and dependent properties in terms of a service request, RSSM can deal with uncertain properties in service discovery.

10, Nottingham10 Service Matchmaking and Ranking l Properties of service advertisements and service requests are matched based on their relationships from 100% to 60% l Properties without values (uncertain properties) have a match degree of 50% l Calculating a match degree using

11, Nottingham11 RSSM Implementation l Java l mySQL as a service repository l It now provides interfaces to upload and parse OWL-S files for service registration automatically using OWL-S API l It also provide an interface to register services in a UDDI in the service repository

12, Nottingham12 RSSM Effectiveness l We compared RSSM with UDDI, and OWL-S Classical Matchmaking Method Proposed by M. Paolucci et al (at ISWC 2002) –Used a Pentium IIII 2.6G with 512M RAM running Red Hat Fedora Linux 3 –Used jUUDI and mySQL to build a UDDI registry –Extended Pizza Ontology > –Used Protégé OWL API to Parse OWL Documents –Used RACER as an inference engine l Results

13, Nottingham13 RSSM Overhead Overhead in retrieving service records Overhead in matching service records

14, Nottingham14 Concluding Remarks l Service discovery is of paramount importance for a wider uptake of the Grid l The preliminary results of RSSM are encouraging –But reducing dependent service properties is computationally intensive, which needs some optimisation work

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