Abstract
With the rise in cloud computing architecture, the development of service-oriented simulation models has gradually become a prominent topic in the field of complex system simulation. In order to support the distributed sharing of the simulation models with large computational requirements and to select the optimal service model to construct complex system simulation applications, this paper proposes a service-oriented model encapsulation and selection method. This method encapsulates models into shared simulation services, supports the distributed scheduling of model services in the network, and designs a semantic search framework which can support users in searching models according to model correlation. An optimization selection algorithm based on quality of service (QoS) is proposed to support users in customizing the weights of QoS indices and obtaining the ordered candidate model set by weighted comparison. The experimental results showed that the parallel operation of service models can effectively improve the execution efficiency of complex system simulation applications, and the performance was increased by 19.76% compared with that of scatter distribution strategy. The QoS weighted model selection method based on semantic search can support the effective search and selection of simulation models in the cloud environment according to the user’s preferences.
Highlights
The continuous evolution of complex systems has had a tremendous impact on people’s daily life and social development
In order to support the composite modeling of complex system simulation applications, some experts have carried out research on simulation service description methods based on semantics and have proposed description ontologies of simulation model resources (e.g., Ontology web language [7] (OWL)-SS [17] and OWL-SM [18])
A service-oriented model encapsulation and selection method for complex system simulation was proposed in this paper
Summary
The continuous evolution of complex systems (e.g., social systems, ecosystems, and war systems) has had a tremendous impact on people’s daily life and social development. In order to solve the abovementioned problems in the existing studies, this paper proposes a service-oriented model encapsulation and selection method for complex system simulation based on cloud architecture. The novelty and contribution of this method includes that it designs a cloud-service-oriented reusable model development (C-RUM) specification to encapsulate the simulation model into a shareable simulation service in the cloud, and devises a cloud-based simulation model service framework, which solves the problem of network communication in the former RUM specification This method uses a knowledge graph [9] to describe the simulation model services and establishes a model semantic search framework in the constructed model description knowledge graph, which supports users in setting correlations between models to obtain the required model.
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