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06/15/2012 2:30 pm
06/15/2012 4:00 pm
Category:Ph.D. Dissertation Defense
Advisor:Dr. Xiaolin Hu
Simulation software, generally based on the process of imitating a real phenomenon with a set of mathematical formulas, is widely used in simulating wildfire spreading processes, weather conditions, electronic circuits, chemical reactions, and so on. Simulation software with real-time response has important industrial applications, especially where the penalty for improper operation is costly, such as nuclear power plants, airplanes, or chemical plants.
In the past, researchers and field experts had to obtain access to a machine that can host simulation software to do their experiments or research. Sometimes, the experiments may be impeded by the fact that one simulation may depend on another simulation that may be not immediately available. However, as the Service-Oriented Architecture (SOA) gains wide popularity, the way we used to compute is changing. New paradigms such as Software as a Service (SaaS) and cloud computing have paved the way, introducing us to a new computing environment via the Internet. Thus, it is desirable to expose simulation software as services on the Internet that can be easily accessed by researchers and field experts all over the world.
To spare researchers from the burden of learning different tools and languages, manually composing different services, designing the workflow, installing the runtime environment, and deploying the experiment, and to enable them to focus on their experiments and output results, we propose a specification for Simulation Software as a Service (SimSaaS) and Service-Oriented Simulation Experiment (SOSE). Based on the specification, we propose a service-oriented experiment framework that aims to automate some tedious steps mentioned above and to provide researchers with an easy-to-use interface to publish and share their simulation services and experiments, compose different simulation services in an efficient way, design their experiments, and automatically deploy and run the experiments. The framework includes three main components: publish and configure simulation services, compose simulation services, and design experiments with simulation services and non-simulation services. In addition, we propose a mechanism to improve the efficiency of the composability of different simulation services according to the researchers’ experiment purposes.
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