1. AHM2006, NottinghamMaozhen.Li@brunel.ac.uk1 RSSM: A Rough Sets based Service Matchmaking Algorithm Bin Yu and Maozhen Li School of Engineering and Design Brunel University Uxbridge, West London

2. Maozhen.Li@brunel.ac.ukAHM2006, 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. Maozhen.Li@brunel.ac.ukAHM2006, 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. Maozhen.Li@brunel.ac.ukAHM2006, 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. Maozhen.Li@brunel.ac.ukAHM2006, 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. Maozhen.Li@brunel.ac.ukAHM2006, 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. Maozhen.Li@brunel.ac.ukAHM2006, 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. Maozhen.Li@brunel.ac.ukAHM2006, Nottingham8 Irrelevant Service Property Reduction

9. Maozhen.Li@brunel.ac.ukAHM2006, 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. Maozhen.Li@brunel.ac.ukAHM2006, 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. Maozhen.Li@brunel.ac.ukAHM2006, 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. Maozhen.Li@brunel.ac.ukAHM2006, 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 >http://www.co-ode.org/ontologies/pizza/pizza_20041007.owl –Used Protégé OWL API to Parse OWL Documents –Used RACER as an inference engine l Results

13. Maozhen.Li@brunel.ac.ukAHM2006, Nottingham13 RSSM Overhead Overhead in retrieving service records Overhead in matching service records

14. Maozhen.Li@brunel.ac.ukAHM2006, 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