Abstract
Model complexity is a major concern affecting the design, analysis and runtime management of computing systems. One way of dealing with model complexity is to compromise on the fidelity of a model’s representation of entities and issues that the model is supposed to represent. This chapter describes a resource-driven modelling approach whereby the fidelity of a model can be managed rationally in order to control model complexity. This approach includes two concrete and related methods targeting two aspects of the problem. Dynamic resource graphs highlight the dependencies between system resources and describe a system’s progression as resource and dependency evolution steps. This forms a theoretical foundation for the tracking of parameters that can be regarded as resources, e.g. power consumption, time, computation units, etc. With this resource-oriented view of a system, a hierarchical modelling method emphasizing cross-layer cuts is established. This method facilitates parameter-proportional modelling to achieve optimal fidelity vs complexity trade-offs in models. Simulation and state space analysis application use cases help to validate the approach.
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This work is supported by EPSRC grant EP/K034448/1.
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Rafiev, A. et al. (2017). Resource-Driven Modelling for Managing Model Fidelity. In: Molnos, A., Fabre, C. (eds) Model-Implementation Fidelity in Cyber Physical System Design. Springer, Cham. https://doi.org/10.1007/978-3-319-47307-9_2
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DOI: https://doi.org/10.1007/978-3-319-47307-9_2
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