Mixed-Criticality with Integer Multiple WCETs and Dropping Relations: New Scheduling Challenges

Scheduling Mixed-Criticality (MC) workload is a challenging problem in real-time computing. Earliest Deadline First Virtual Deadline (EDF-VD) is one of the most famous scheduling algorithm with optimal speedup bound properties. However, when EDF-VD is used to schedule task sets using a model with additional or relaxed constraints, its scheduling properties change. Inspired by an application of MC to the scheduling of fault tolerant tasks, in this article, we propose two models for multiple criticality levels: the first is a specialization of the MC model, and the second is a generalization of it. We then show, via formal proofs and numerical simulations, that the former considerably improves the speedup bound of EDF-VD. Finally, we provide the proofs related to the optimality of the two models, identifying the need of new scheduling algorithms

chronovise: Measurement-Based Probabilistic Timing Analysis framework

A MBPTA framework for probabilistic real-time analyses</p

Work-in-Progress: Why statistical power matters for probabilistic real-time

The probabilistic approaches for real-time systems are based on the estimation of the probabilistic-WCET distribution. Such estimation is naturally subject to errors, caused by both systematic and estimation uncertainties. To solve this problem, statistical tests are applied on the resulting distribution to check whether such errors affect or not the output validity. In this paper, we show that the reliability of these tests depends on the statistical power that must be estimated in order to select the proper sample size. This a priori analysis is required to obtain a reliable result of the probabilistic-WCET

Statistical power estimation in Extreme Value Theory

These files contain the code (three executables in total) and the results carried out by that code. It provides the statistical power analysis and its sensitivity for Kolmogorov-Smirnov (KS), Anderson-Darling (AD) and the Modified Anderson-Darling (MAD) tests for Extreme Value (EV) distributions. The power is estimated via a Monte Carlo approach with 10^9 samples, under "case 0" conditions. The tests were performed varying the reference distribution, the sampling distribution, the sample size and the critical value. The sensitivity analysis was performed on the shape parameter of EV distribution

A Probabilistic Approach to Energy-Constrained Mixed-Criticality Systems

In battery-powered embedded systems, the energy budget management is a critical aspect. For systems using unreliable power sources, e.g. solar panels, the continuous system operation is a challenging requirement. In such scenarios, effective management policies must rely on accurate energy estimations. In this paper we propose a measurement-based probabilistic approach to address the worst-case energy consumption (WCEC) estimation, coupled with a job admission algorithm for energy-constrained task scheduling. The overall goal is to demonstrate how the proposed approach can introduce benefits also in mission-critical systems, where unsafe energy budget estimations cannot be tolerated

Mixed Criticality Scheduling of Probabilistic Real-Time Systems

In this paper we approach the problem of Mixed Criticality (MC) for probabilistic real-time systems where tasks execution times are described with probabilistic distributions. In our analysis, the task enters high criticality mode if its response time exceeds a certain threshold, which is a slight deviation from a more classical approach in MC. We do this to obtain an application oriented MC system in which criticality mode changes depend on actual scheduled execution. This is in contrast to classical approaches which use task execution time to make criticality mode decisions, because execution time is not affected by scheduling while the response time is. We use a graph-based approach to seek for an optimal MC schedule by exploring every possible MC schedule the task set can have. The schedule we obtain minimizes the probability of the system entering high criticality mode. In turn, this aims at maximizing the resource efficiency by the means of scheduling without compromising the execution of the high criticality tasks and minimizing the loss of lower criticality functionality. The proposed approach is applied to test cases for validation purposes

Variation of milk components in the Italian Brown cattle

The aim of this study was to evaluate the variations of protein, casein, saturated (SFA), unsaturated (UFA), monounsaturated (MUFA), polyunsaturated (PUFA) fatty acids contents and cheese yield in the milk of two groups of Italian Brown cows conventionally reared in indoor period of housing or consuming pasture during the summer months in 2008 and 2013. Milk components were obtained from samples collected during the national routine (conventionally reared) and 'extraordinary' (pasture period) milk recording scheme in herds located near Sondrio (Lombardia, Italy). Milk samples were processed with the MilkoScanTM FT6000 for the identification of milk casein, SFA, UFA, MUFA and PUFA composition. The groups were analysed separately per year and the environmental factors affecting milk protein, casein, and fatty acids contents (pasture/indoor, parity, data of sampling, days in milk, days from collection to analysis) were included in the MIXED procedure of SAS 9.3. A total of 778 milk samples were available, including 234 records from indoor and 544 observations from pasture feeding. Pasture intake affected the content of casein (%) and the proportion of fat in milk (g/100 g), enhancing milk casein levels (from 2.90 to 3) and reducing the concentration of milk SFA in milk from grazing cows (from 2.29 to 1.92). Additionally, the cheese yield was calculated as 'kg of cheese per 100 kg of milk' and resulted to be 10.4 and 12 in 2008 from milk of cows reared indoor and with pasture based diet, respectively. The dairy industry should take advantage of the milk production during grazing periods from which high quality products may be obtained