Time-triggered Static Schedulable Dataflows for Multimedia Systems

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.