Time-triggered static schedulable dataflows for multimedia systems

Abstract

Software-based reactive multimedia computation systems are pervasive today in desktops but also in mobile and ultra-portable devices. Most such systems offer a callback-based architecture to incorporate specific stream processing. The Synchronous Dataflow model (SDF) and its variants are appropriate for many continuous stream processing problems such as the ones involving video and audio. SDF allows for static scheduling of multi-rate processing graphs therefore enabling optimal run-time efficiency. But the SDF abstraction does not adapt well to real-time processing because it lacks the notion of time: executing non-trivial schedules of multi-rate dataflows in a time-triggered callback architecture, though possible through buffering, causes jitter, excessive latency and run-time inefficiencies. In this paper we formally describe a new Time-Triggered SDF (TTSDF) model with a static scheduling algorithm that produces periodic schedules than can be split among several callback activations, solving the above-mentioned problems. The model has the same expressiveness than SDF, in the sense that any graph computable by one model will also be computable by the other. Additionally, it enables parallelization and run time load balancing between callback activations.

Strictly periodic first: An optimal variant of LLF for scheduling tasks in a time‐critical cyber‐physical system

“…Therefore, if all tasks satisfy Equation ( 18), the task set is schedulable by SPF. This shows the sufficiency of condition (18).…”

“…Since 𝜏 i processor demand exceeds its period than, 𝜏 i should miss its deadline, which leads to a contradiction. This shows the necessity of condition (18). ▪ Example 7.…”

An Empirical Evaluation of a Programming Model for Context-Dependent Real-time Streaming Applications

“…It can provide several scenarios in parallel, whose composition is transparent for the programmer (i.e.they can be checked and validated independently from one another, as the composition does not change their execution). In [1], Arumi and Amatriam proposed Time Triggered Synchronous Data Flow (TTSDF) which associates Time-Triggered (TT) periodic schedule to the input nodes and output nodes of a Synchronous Data-flow (SDF) and derives a periodic schedule for all the actors in the SDF graph. This approach partially solves the problem of mixing real-time and high-performance computing, but it does not provide efficient mechanisms to cope with failure in real-time systems contrary to our model.…”