Accuracy improvement of dataflow analysis for cyclic stream processing applications scheduled by static priority preemptive schedulers

Stream processing applications executed on embedded multiprocessor systems regularly contain cyclic data dependencies due to the presence of feedback loops and bounded FIFO buffers. Dataflow modeling is suitable for the temporal analysis of such applications. However, the accuracy can be unsatisfactory as existing temporal analysis techniques ignore that cyclic data dependencies limit interference between tasks executed on shared processors.\ud \ud This paper presents a dataflow analysis approach that increases the analysis accuracy by taking into account that cyclic data dependencies limit interference between tasks. It is shown that the approach is applicable for single-rate stream processing applications that are executed on multiprocessor systems using static priority preemptive schedulers.\ud \ud The improvement of accuracy is demonstrated in a case study employing a WLAN 802.11p transceiver application that is executed on a multiprocessor system with shared processors

Temporal Analysis of Static Priority Preemptive Scheduled Cyclic Streaming Applications using CSDF Models

Real-time streaming applications with cyclic data dependencies that are executed on multiprocessor systems with processor sharing usually require a temporal analysis to give guarantees on their temporal behavior at design time. Current accurate analysis techniques for cyclic applications that are scheduled with Static Priority Preemptive (SPP) schedulers are however limited to the analysis of applications that can be expressed with Homogeneous Synchronous Dataflow (HSDF) models, i.e. in which all tasks operate at a single rate. Moreover, it is required that both input and output buffers synchronize atomically at the beginnings and finishes of task executions, which is difficult to realize on many existing hardware platforms.\ud \ud This paper presents a temporal analysis approach for cyclic real-time streaming applications executed on multiprocessor systems with processor sharing and SPP scheduling that can be expressed using Cyclo-Static Dataflow (CSDF) models. This allows to model tasks with multiple phases and changing rates and furthermore resolves the problematic restriction that buffer synchronization must occur atomically at the boundaries of task executions. For that purpose a joint interference characterization over multiple phases is introduced, which realizes a significant accuracy improvement compared to an isolated consideration of interference.\ud \ud Applicability, efficiency and accuracy of the presented approach are evaluated in a case study using a WLAN 802.11p transceiver application. Thereby different use-cases of CSDF modeling are discussed, including a CSDF model relaxing the requirement of atomic synchronization