WSN-SES/MB: System Entity Structure and Model Base Framework for Large-Scale Wireless Sensor Networks

Large-scale wireless sensor networks are characterized by stringent energy and computation restrictions. It is exceedingly difficult to change a sensor network’s environment configurations, such as the number of sensor nodes, after deployment of the nodes. Although several simulators are able to variously construct simulation models for sensor networks before their deployment, the configurations should be modified with extra human effort as the simulators cannot freely generate diverse models. In this paper, we propose a novel framework, called a system entity structure and model base for large-scale wireless sensor networks (WSN-SES/MB), which is based on discrete event system specification formalism. Our proposed framework synthesizes the structure and models for sensor networks through our modeling construction process. The proposed framework achieves time and cost savings in constructing discrete event simulation-based models. In addition, the framework increases the diversity of simulation models by the process’s pruning algorithm. The simulation results validate that the proposed framework provides up to 8% time savings and up to 23% cost savings as compared to the manual extra effort.

Ontological Approach to Holistic Healthcare Systems Simulation

This article aims at developing a new ontology for healthcare systems (HS) simulation. The ontology includes various classes that represent major components of HS simulation and their relationships as an integrated whole. It is formally expressed using system entity structure language with links to basic models developed in various formalisms and stored in a model base repository. Entities are mapped into web ontology language (OWL) classes and can be visualized in Protégée and queried with SPARQL. Classes are built based on agreed-upon concepts in HS simulation domain and serve to document and formalize knowledge while providing notable benefits such as common representation of healthcare models from different simulation platforms, model reuse, querying simulation models, and browsing. The paper also presents an illustrative case study to showcase the use of the ontology while capturing successfully within its scope an outbreak of cholera disease and its mitigation plan.