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PublicationTiming Analysis of Mixed Time/Event-Triggered Multi-Mode Systems(2009-12-01) Phan, Linh T.X.; Chakraborty, Samarjit; Lee, InsupMany embedded systems operate in multiple modes, where mode switches can be both time- as well as event-triggered. While timing and schedulability analysis of the system when it is operating in a single mode has been well studied, it is always difficult to piece together the results from different modes in order to deduce the timing properties of a multi-mode system. As a result, often certain restrictive assumptions are made, e.g., restricting the time instants at which mode changes might occur. The problem becomes more complex when both time- and event-triggered mode changes are allowed. Further, for complex systems that cannot be described by traditional periodic/sporadic event models (i.e., where event streams are more complex/bursty) modeling multiple modes is largely an open problem. In this paper we propose a model and associated analysis techniques to describe embedded systems that process multiple bursty/complex event/data streams and in which mode changes are both timeand event-triggered. Compared to previous studies, our model is very general and can capture a wide variety of real-life systems. Our analysis techniques can be used to determine different performance metrics, such as the maximum fill-levels of different buffers and the delays suffered by the streams being processed by the system. The main novelty in our analysis lies in how we piece together results from the different modes in order to obtain performance metrics for the full system. Towards this, we propose both – exact, but computationally expensive, as well as safe approximation techniques. The utility of our model and analysis has been illustrated using a detailed smart-phone case study. PublicationVideo Quality Driven Buffer Sizing via Frame Drops(2011-08-01) Gangadharan, Deepak; Phan, Linh T.X.; Chakraborty, Samarjit; Zimmermann, Roger; Lee, InsupWe study the impact of video frame drops in buffer constrained multiprocessor system-on-chip (MPSoC) platforms. Since on-chip buffer memory occupies a significant amount of silicon area, accurate buffer sizing has attracted a lot of research interest lately. However, all previous work studied this problem with the underlying assumption that no video frame drops can be tolerated. In reality, multimedia applications can often tolerate some frame drops without significantly deteriorating their output quality. Although system simulations can be used to perform video quality driven buffer sizing, they are time consuming. In this paper, we first demonstrate a dual-buffer management scheme to drop only the less significant frames. Based on this scheme, we then propose a formal framework to evaluate the buffer size vs. video quality trade-offs, which in turn will help a system designer to perform quality driven buffer sizing. In particular, we mathematically characterize the maximum numbers of frame drops for various buffer sizes and evaluate how they affect the worst-case PSNR value of the decoded video. We evaluate our proposed framework with an MPEG-2 decoder and compare the obtained results with that of a cycle-accurate simulator. Our evaluations show that for an acceptable quality of 30 dB, it is possible to reduce the buffer size by upto 28.6% which amounts to 25.88 megabits. PublicationModeling Buffers With Data Refresh Semantics in Automotive Architectures(2010-10-01) Phan, Linh T.X.; Schneider, Reinhard; Chakraborty, Samarjit; Lee, InsupAutomotive architectures consist of multiple electronic control units (ECUs) which run distributed control applications. Such ECUs are connected to sensors and actuators and communicate via shared buses. Resource arbitration at the ECUs and also in the communication medium, coupled with variabilities in execution requirements of tasks results in jitter in the signal/data streams existing in the system. As a result, buffers are required at the ECUs and bus controllers. However, these buffers often implement different semantics – FIFO queuing, which is the most straightforward buffering scheme, and data refreshing, where stale data is overwritten by freshly sampled data. Traditional timing and schedulability analysis that are used to compute, e.g., end-to-end delays, in such automotive architectures can only model FIFO buffering. As a result, they return pessimistic delay and resource estimates because in reality overwritten data items do not get processed by the system. In this paper we propose an analytical framework for accurately modeling such data refresh semantics. Our model exploits a novel feedback control mechanism and is purely functional in nature. As a result, it is scalable and does not involve any explicit state modeling. Using this model we can estimate various timing and performance metrics for automotive ECU networks consisting of buffers implementing different data handling semantics. We illustrate the utility of this model through three case studies from the automotive electronics domain.