Ontology-Based Service Selection via Subsumption Reasoning
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Solution Overview
Problem
In service-oriented architectures, selecting the appropriate Web service to fulfill a request is resource-intensive due to the need to invoke and compare multiple services, often requiring excessive data processing and consumption of computer and connection resources, especially when service specifications differ in detail.
Innovation Solution
A system utilizing an ontology-based structure that transforms service requests into sub-concepts, allowing for efficient selection of provider services without invoking them, by using a transformer unit and selection unit that apply subsumption reasoning to determine if the request sub-concept is a sub-concept of the provider service, thereby reducing resource consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the requester invokes all potentially suitable services to analyze results and select a service, then the service selection can be based on comprehensive results, but the consumption of computer resources and connection resources increases significantly
Solution Approach 1:
The system performs preliminary action by transforming the service request into a sub-concept before invocation. The transformer unit converts the service request specification into a sub-concept of the generic contract ontology, enabling subsequent subsumption checking without requiring full service invocation. This preliminary transformation allows the selection unit to identify suitable services based on conceptual subsumption rather than empirical result analysis.
Solution Approach 2:
The system creates a conceptual copy of the service request as a sub-concept within the ontology. Instead of invoking services to obtain results and then comparing them, the system copies the request into the ontology structure and uses subsumption reasoning to determine suitability. This conceptual copying replaces the resource-intensive process of actual service invocation and result analysis.
2Measurement precision
If the requester specifies more data for invoking services that potentially fulfill the service request, then the service invocation can be more precise, but the data processing requirements and resource consumption increase
Solution Approach 1:
The system extracts the essential matching criteria from the service request and represents them as a sub-concept in the ontology. The transformer unit extracts the request specification and converts it into a conceptual form that can be directly compared with service descriptions through subsumption checking. This extraction eliminates the need to specify and process extensive data for invocation, as the conceptual representation captures the essential matching requirements.
Solution Approach 2:
The system changes the representation parameters of the service request from concrete data specifications to conceptual sub-concepts. Instead of working with detailed data specifications that require extensive processing, the system transforms the request into an ontology-based conceptual form. This parameter change enables precise matching through subsumption reasoning while dramatically reducing data processing volume.
3Adaptability or versatility
If services are described using detailed specifications with different levels of description, then the service discovery can be more flexible, but the service selection process becomes more complex when specifications differ
Solution Approach 1:
The system implements universality by using a generic contract ontology that can accommodate service specifications at different levels of detail. The ontology structure serves multiple functions: it represents service descriptions, performs subsumption checking, and enables flexible matching regardless of specification detail level. This universal ontology approach simplifies the selection process by providing a unified framework that handles diverse specification granularities without requiring separate processing mechanisms.
Solution Approach 2:
The ontology acts as an intermediary between the service request and the service descriptions. Instead of directly comparing requests with detailed service specifications, the system uses the ontology as a mediating layer. The transformer unit converts the request into a sub-concept, and the selection unit uses subsumption checking against the ontology to identify suitable services. This intermediary approach simplifies the selection process while maintaining flexibility in handling different specification levels.
Data Source
AI summary
Example implementations relate to a system for selecting a provider service that fulfills a specification of a service request. The system includes a storage unit, a transformer unit, and a selection unit. The storage unit is configured to store a generic contract that is a concept of an ontology and a provider sub-concept that is a further concept of the ontology and a sub-concept of the generic contract. The provider sub-concept represents the provider service. The transformer unit is configured to transform the service request to a request sub-concept that is a concept of the ontology and a sub-concept of the generic contract. The selection unit is configured to select the provider service in case that the request sub-concept is a sub-concept of the provider sub-concept.