Matchmaking Framework for Mathematical Web Services

Third IEEE International Conference on E-Science and Grid Computing (E-Science 2007)

Naylor³

et al. 2007

Self Cite

Service description and discovery offer complementary challenges, but in both cases, the problem is finding the right trade-off between accuracy and generality that will result in a positive service identification. Discovery systems have historically tended to focus on domain-specific techniques using single sources of knowledge to help classify queries against services, making both maintenance and extension difficult. The primary contribution of this paper is the presentation of a generic brokerage framework based on the use of plug-in components, that are themselves web services. The framework has been developed in the context of the KNOOGLE project, where the focus has been on demonstrating support for (i) the discovery of Grid services for the GridSAM job submission system and (ii) integration with the Taverna workflow enactment system. However, the broker itself is domain independent and it is the multiple user-specified matchmaker plug-ins that act as sources of domain-specific knowledge. The broker collects the results of the matchmakers' comparison of the query and service and then applies a user-specified selection policy to determine the final choice of service. Thus a range of comprehensive packaging of brokerage functionality becomes possible through the use of supplied and user-defined matchers and supplied or user-defined selection policies.Third IEEE International Conference on e-Science and Grid Computing 0-7695-3064-8/07 $25.00

Section: Broker Requirementsmentioning

confidence: 99%

Section: Broker Requirementsmentioning

confidence: 99%

Matchmaking Support for Dynamic Workflow Composition

Chapman

Third IEEE International Conference on E-Science and Grid Computing (E-Science 2007)

Naylor³

et al. 2007

Self Cite

“…A lot of related work on semantic service matching has been done [7,8,9,10,11] however, this approach takes not only semantic service descriptions into account but also context information. Ontologies are used for classification of the services based on their properties.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy match score of semantic service match

2008 IEEE International Conference on Fuzzy Systems (IEEE World Congress on Computational Intelligence)

2008

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Automatic discovery of services is a crucial task for the e-Science and e-Business communities. Finding a suitable way to address this issue has become one of the key points to convert the Web into a distributed source of computation, as it enables the location of distributed services to perform a required functionality. To provide such an automatic location, the discovery process should be based on the semantic match between a declarative description of the service being sought and a description being offered. This problem requires not only an algorithm to match these descriptions, but also a language to declaratively express the capabilities of services. The proposed matchmaking approach is based on semantic descriptions for service attributes, descriptions and metadata. For the ranking of service matches a match score is calculated whereby the weight values are either given by the user or estimated using a fuzzy approach. An evaluation of both weight assignment approaches is conducted identifying in which scenario one works better than the other.

“…The problem of matchmaking for mathematical services was addressed in [2], where a semantic annotation was used to determine the applicability (or otherwise) of a service. We use OpenMath descriptions of pre-and post-conditions to provide these annotations.…”

mentioning

confidence: 99%

Performance evaluation of semantic registries: OWLJessKB and instanceStore

Rana

2008

SOCA

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Service discovery is a critical task in distributed computing architectures for finding a particular service instance. Semantic annotations of services help to enrich the service discovery process. Semantic registries are an important component for the discovery of services and they allow for semantic interoperability through ontology-based query formulation and dynamic mapping of terminologies between system domains. This paper evaluates two semantic registries-OWLJessKB implementation and instanceStore-to determine the suitability of these with regards to the query response time and the overall scalability for use in mathematical services. Mathematical ontologies from the MONET project are used to undertake comparison. The results demonstrate that the performance of registries may be compared across two axes: (1) time to initialize (i.e. time to load an initial ontology into memory); (2) time to query (i.e. time to reason with an ontology loaded into memory).