Parameterized Dataflow Scenarios

Abstract

Abstract-A number of modeling approaches combining dataflow and finite-state machines (FSMs) have been proposed to capture applications that combine streaming data with finite control. FSM-based scenario-aware dataflow (FSM-SADF) is such an FSM/dataflow hybrid that occupies a sweet spot in the tradeoff between analyzability and expressiveness. However, the model suffers from compactness issues when the number of scenarios increases. This hampers its use in analysis of applications exposing high levels of data-dependent dynamics.In this article, we address this problem by combining parameterized dataflow with finite control of FSM-SADF. We refer to the generalization as FSM-based parameterized scenario-aware dataflow (FSM-πSADF). We introduce the formal semantics of the model, in terms of Max-plus algebra and in particular Maxplus automata. Thereafter, by leveraging the existing results of FSM-SADF, we propose a worst-case performance analysis framework for FSM-πSADF. We show that by using FSM-πSADF and its analysis framework, one can, unlike with FSM-SADF, compactly capture streaming applications exhibiting high levels of data-dependent dynamics in presence of finite control. Furthermore, we show that for practical models our analysis typically yields tighter bounds on worst-case performance indicators such as throughput and latency than the existing techniques based on conservative FSM-SADF modeling (if such modeling can be applied at all). We evaluate our approach on a realistic case-study from the multimedia domain.Index Terms-parameterized dataflow, finite-state machine, parameterized dataflow scenarios, synchronous dataflow, Maxplus algebra, worst-case performance.

A survey of main dataflow MoCCs for CPS design and verification

“…3) FSM-PSADF: The Finite State Machine-based -Parameterized Scenario-Aware Dataflow (FSM-PSADF, [35]) uses parameters to improve the compactness of FSM-SADF. The scenario and the parameter configuration in that scenario are both non-deterministically chosen at the end of an iteration.…”