IEEE Access (Jan 2021)
Classification and Mapping of Model Elements for Designing Runtime Reconfigurable Systems
Abstract
Embedded systems are ubiquitous and control many critical functions in society. A fairly new type of embedded system has emerged with the advent of partial reconfiguration, i.e. runtime reconfigurable systems. They are attracting interest in many different applications. Such a system is capable of reconfiguring itself at the hardware level and without the need to halt the application’s execution. While modeling and implementing these systems is far from a trivial task, there is currently a lack of systematic approaches to tackle this issue. In other words, there is no unanimously agreed upon modeling paradigm that can capture adaptive behaviors at the highest level of abstraction, especially when regarding the design entry, namely, the initial high-level application and platform models. Given this, our paper proposes two domain ontologies for application and virtual platform models used to derive a classification system and to provide a set of rules on how the different model elements are allowed to be composed together. The application behavior is captured through a formal model of computation which dictates the semantics of execution, concurrency, and synchronization. The main contribution of this paper is to combine suitable formal models of computation, a functional modeling language, and two domain ontologies to create a systematic design flow from an abstract executable application model into a virtual implementation model based on a runtime reconfigurable architecture (virtual platform model) using well-defined mapping rules. We demonstrate the applicability, generality, and potential of the proposed model element classification system and mapping rules by applying them to representative and complete examples: an encoder/decoder system and an avionics attitude estimation system. Both cases yield a virtual implementation model from an abstract application model.
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