System-Level Modeling of Dynamic Applications with Scenario-Aware Dataflow Graphs

This paper presents a comprehensive modeling framework for managing the complexities inherent in modeling dynamic and intelligent embedded and cyber-physical systems (CPSs). Leveraging the scenario-aware dataflow (SADF) model of computation (MoC), our framework effectively captures CPS dynamism through controlled scenario representations. We establish denotational-style semantics within the Formal System Design (ForSyDe) framework and operational-style semantics tailored for practical industrial implementation. Integration of SADF MoC into ForSyDe-SystemC exploits modern C++ language features, offering type- and size-safety, model introspection, parallel simulation, and foreign model integration. The contributed SADF extension possesses the capability to seamlessly interconnect with other MoCs, thereby facilitating heterogeneous system modeling. Demonstrational examples, including an encoder/decoder system and an MPEG-۴ decoder algorithm for the simple profile, attest to the framework's correctness and practicality. We also introduce a tool flow for automated synthetic benchmark generation, essential for assessing the scalability and performance of ForSyDe-SystemC SADF models in diverse conditions. The extended modeling framework, examples, and supporting tools are available as public domain code.

Keywords:

Modeling Abstractions , Scenario-Aware Dataflow , Embedded Systems , Cyber-Physical Systems , Formal System Design , Streaming Applications