<p>Systems controlled by embedded computers become indispensable in our lives and can be found in avionics, automotive industry, home appliances, medicine, telecommunication industry, mecatronics, space industry, etc. Fast, accurate and flexible performance estimation tools giving feedback to the designer in every design phase are a vital part of a design process capable to produce high quality designs of such embedded systems.</p><p>In the past decade, the limitations of models considering fixed task execution times have been acknowledged for large application classes within soft real-time systems. A more realistic model considers the tasks having varying execution times with given probability distributions. No restriction has been imposed in this thesis on the particular type of these functions. Considering such a model, with specified task execution time probability distribution functions, an important performance indicator of the system is the expected deadline miss ratio of tasks or task graphs.</p><p>This thesis proposes two approaches for obtaining this indicator in an analytic way. The first is an exact one while the second approach provides an approximate solution trading accuracy for analysis speed. While the first approach can efficiently be applied to monoprocessor systems, it can handle only very small multi-processor applications because of complexity reasons. The second approach, however, can successfully handle realistic multiprocessor applications. Experiments show the efficiency of the proposed techniques.</p> / Report code: LiU-Tek-Lic-2002:58.

Systems controlled by embedded computers become indispensable in our lives and can be found in avionics, automotive industry, home appliances, medicine, telecommunication industry, mecatronics, space industry, etc. Fast, accurate and flexible performance estimation tools giving feedback to the designer in every design phase are a vital part of a design process capable to produce high quality designs of such embedded systems. In the past decade, the limitations of models considering fixed task execution times have been acknowledged for large application classes within soft real-time systems. A more realistic model considers the tasks having varying execution times with given probability distributions. No restriction has been imposed in this thesis on the particular type of these functions. Considering such a model, with specified task execution time probability distribution functions, an important performance indicator of the system is the expected deadline miss ratio of tasks or task graphs. This thesis proposes two approaches for obtaining this indicator in an analytic way. The first is an exact one while the second approach provides an approximate solution trading accuracy for analysis speed. While the first approach can efficiently be applied to monoprocessor systems, it can handle only very small multi-processor applications because of complexity reasons. The second approach, however, can successfully handle realistic multiprocessor applications. Experiments show the efficiency of the proposed techniques. / <p>Report code: LiU-Tek-Lic-2002:58.</p>

Embedded systems have become indispensable in our life: household appliances, cars, airplanes, power plant control systems, medical equipment, telecommunication systems, space technology, they all contain digital computing systems with dedicated functionality. Most of them, if not all, are real-time systems, i.e. their responses to stimuli have timeliness constraints. The timeliness requirement has to be met despite some unpredictable, stochastic behaviour of the system. In this thesis, we address two causes of such stochastic behaviour: the application and platform-dependent stochastic task execution times, and the platform-dependent occurrence of transient faults on network links in networks-on-chip. We present three approaches to the analysis of the deadline miss ratio of applications with stochastic task execution times. Each of the three approaches fits best to a different context. The first approach is an exact one and is efficiently applicable to monoprocessor systems. The second approach is an approximate one, which allows for designer-controlled trade-off between analysis accuracy and analysis speed. It is efficiently applicable to multiprocessor systems. The third approach is less accurate but sufficiently fast in order to be placed inside optimisation loops. Based on the last approach, we propose a heuristic for task mapping and priority assignment for deadline miss ratio minimisation. Our contribution is manifold in the area of buffer and time constrained communication along unreliable on-chip links. First, we introduce the concept of communication supports, an intelligent combination between spatially and temporally redundant communication. We provide a method for constructing a sufficiently varied pool of alternative communication supports for each message. Second, we propose a heuristic for exploring the space of communication support candidates such that the task response times are minimised. The resulting time slack can be exploited by means of voltage and/or frequency scaling for communication energy reduction. Third, we introduce an algorithm for the worst-case analysis of the buffer space demand of applications implemented on networks-on-chip. Last, we propose an algorithm for communication mapping and packet timing for buffer space demand minimisation. All our contributions are supported by sets of experimental results obtained from both synthetic and real-world applications of industrial size.