System-of-systems （SOS） engineering involves a com- plex process of refining high-level SoS requirements into more detailed systems requirements and assessing the extent to which the performances of to-be systems ma...System-of-systems （SOS） engineering involves a com- plex process of refining high-level SoS requirements into more detailed systems requirements and assessing the extent to which the performances of to-be systems may possibly satisfy SoS capa- bility objectives. The key issue is how to model such requirements to automate the process of analysis and assessment. This paper suggests a meta-model that defines both functional and non- functional features of SoS requirements for command and control, communication, computer, intelligence, surveillance reconnais- sance （C41SR） systems. A domain-specific modeling language is defined by extending unified modeling language （UML） con- structed of class and association with fuzzy theory in order to model the fuzzy concepts of performance requirements. An effi- ciency evaluation function is introduced, based on Bezier curves, to predict the effectiveness of systems. An algorithm is presented to transform domain models in fuzzy UML into a requirements ontology in description logic （DL） so that requirements verification can be automated with a popular DL reasoner such as Pellet.展开更多
基金supported by the National Natural Science Foundation of China(61273210)
文摘System-of-systems （SOS） engineering involves a com- plex process of refining high-level SoS requirements into more detailed systems requirements and assessing the extent to which the performances of to-be systems may possibly satisfy SoS capa- bility objectives. The key issue is how to model such requirements to automate the process of analysis and assessment. This paper suggests a meta-model that defines both functional and non- functional features of SoS requirements for command and control, communication, computer, intelligence, surveillance reconnais- sance （C41SR） systems. A domain-specific modeling language is defined by extending unified modeling language （UML） con- structed of class and association with fuzzy theory in order to model the fuzzy concepts of performance requirements. An effi- ciency evaluation function is introduced, based on Bezier curves, to predict the effectiveness of systems. An algorithm is presented to transform domain models in fuzzy UML into a requirements ontology in description logic （DL） so that requirements verification can be automated with a popular DL reasoner such as Pellet.
