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- Response time analysis of multiframe mixed-criticality systems with arbitrary deadlinesPublication . Hussain, Ishfaq; Awan, Muhammad Ali; Souto, Pedro; Bletsas, Konstantinos; Akesson, Benny; Tovar, EduardoThe well-known model of Vestal aims to avoid excessive pessimism in the quantifcation of the processing requirements of mixed-criticality systems, while still guaranteeing the timeliness of higher-criticality functions. This can bring important savings in system costs, and indirectly help meet size, weight and power constraints. This efciency is promoted via the use of multiple worst-case execution time (WCET) estimates for the same task, with each such estimate characterized by a confdence associated with a diferent criticality level. However, even this approach can be very pessimistic when the WCET of successive instances of the same task can vary greatly according to a known pattern, as in MP3 and MPEG codecs or the processing of ADVB video streams. In this paper, we present a schedulability analysis for the new multiframe mixed-criticality model, which allows tasks to have multiple, periodically repeating, WCETs in the same mode of operation. Our work extends both the analysis techniques for Static Mixed-Criticality scheduling (SMC) and Adaptive Mixed-Criticality scheduling (AMC), on one hand, and the schedulability analysis for multiframe task systems on the other. A constrained-deadline model is initially targeted, and then extended to the more general, but also more complex, arbitrary-deadline scenario. The corresponding optimal priority assignment for our schedulability analysis is also identifed. Our proposed worst-case response time (WCRT) analysis for multiframe mixed-criticality systems is considerably less pessimistic than applying the static and adaptive mixed-criticality scheduling tests oblivious to the WCET variation patterns. Experimental evaluation with synthetic task sets demonstrates up to 20% and 31.4% higher scheduling success ratio (in absolute terms) for constrained-deadline analyses and arbitrary-deadline analyses, respectively, when compared to the best of their corresponding frame-oblivious tests.
- Response time analysis of multiframe mixed-criticality systemsPublication . Hussain, Ishfaq; Ali Awan, Muhammad; Souto, Pedro; Bletsas, Konstantinos; Åkesson, Benny; Tovar, EduardoThe well-known model of Vestal aims to avoid excessive pessimism in the quantification of the processing requirements of mixedcriticality systems, while still guaranteeing the timeliness of highercriticality functions. This can bring important savings in system costs, and indirectly help meet size, weight and power constraints. This efficiency is promoted via the use of multiple worst-case execution time (WCET) estimates for the same task, with each such estimate characterised by a confidence associated with a different criticality level. However, even this approach can be very pessimistic when the WCET of successive instances of the same task can vary greatly according to a known pattern, as in MP3 and MPEG codecs or the processing of ADVB video streams. In this paper, we present a schedulability analysis for the multiframe mixed-criticality model, which allows tasks to have multiple, periodically repeating, WCETs in the same mode of operation. Our work extends both the analysis techniques for Static Mixed-Cricality scheduling (SMC) and Adaptive Mixed-Criticality scheduling (AMC), on one hand, and the schedulability analysis for multiframe task systems on the other. Our proposed worst-case response time (WCRT) analysis for multiframe mixed-criticality systems is considerably less pessimistic than applying the SMC, AMC-rtb and AMC-max tests obliviously to the WCET variation patterns. Experimental evaluation with synthetic task sets demonstrates up to 63.8% higher scheduling success ratio (in absolute terms) compared to the best of the frame-oblivious tests
- Techniques and Analysis for Mixed-criticality Scheduling with Mode-dependent Server Execution BudgetsPublication . Ali Awan, Muhammad; Bletsas, Konstantinos; Souto, Pedro F.; Åkesson, Benny; Tovar, EduardoIn mixed-criticality systems, tasks of different criticality share system resources, mainly to reduce cost. Cost is further reduced by using adaptive mode-based scheduling arrangements, such as Vestal’s model, to improve resource efficiency, while guaranteeing schedulability of critical functionality. To simplify safety certification, servers are often used to provide temporal isolation between tasks. In its simplest form, a server is a periodically recurring time window, in which some tasks are scheduled. A server’s computational requirements may greatly vary in different modes, although state-of-the-art techniques and schedulability tests do not allow different budgets to be used by a server in different modes. This results in a single conservative execution budget for all modes, increasing system cost. The goal of this paper is to reduce the cost of mixed-criticality systems through three main contributions: (i) a scheduling arrangement for uniprocessor systems employing fixed-priority scheduling within periodic servers, whose budgets are dynamically adjusted at run-time in the event of a mode change, (ii) a new schedulability analysis for such systems, and (iii) heuristic algorithms for assigning budgets to servers in different modes and ordering the execution of the servers. Experiments with synthetic task sets demonstrate considerable improvements (up to 52.8%) in
- Memory Bandwidth Regulation for Multiframe Task SetsPublication . Ali Awan, Muhammad; Souto, Pedro; Bletsas, Konstantinos; Åkesson, Benny; Tovar, EduardoTiming analysis of safety-critical real-time embedded systems should be free of both optimistic and pessimistic aspects. The multiframe model was devised to eliminate the pessimism in the schedulability analysis of systems with tasks whose worst-case execution times vary from job to job, according to known patterns. However, this model is optimistic and unsafe for multicores with shared memory controllers, since it ignores memory contention, and existing approaches to stall analysis based on memory regulation are very pessimistic if straightforwardly applied. This paper remedies this by adapting existing stall analyses for memory-regulated systems of conventional Liu-and-Layland tasks to the multiframe model. Experimental evaluations with synthetic task sets (and different task and memory budget assignment heuristics) show up to 85% higher scheduling success ratio for our analysis, compared to the frameagnostic analysis, enabling higher platform utilisation without compromising safety. We also explore implementation aspects, such as how to speed up the analysis and how to trade off accuracy with tractability.
- Schedulability analysis for CAN bus messages of periodically-varying sizePublication . Hussain, Ishfaq; Souto, Pedro; Bletsas, Konstantinos; Awan, Muhammad Ali; Tovar, EduardoConventional CAN bus schedulability analysis assumes that all messages with a given identifier have the same worst-case length. In this paper we extend that analysis to a more general model in which messages with a given identifier may have different lengths, that vary according to a known periodic pattern.That is, for some positive integer S, we assume that the length of message instances n and n + S with the same id is the same. By leveraging such patterns, where present, our new analysis allows for a more efficient use of CAN bus bandwidth than the application of conventional analysis, which can be pessimistic. This may be interesting when a given node sends the values of multiple signals with different periods. In such a scenario, the conventional CAN schedulability analysis would require either the use of different ids for different signals (assuming there are enough of them), which leads to a higher bandwidth overhead because of the reduplication of message headers, or using only one id, but pessimistically always assuming the maximum possible length of the message, for safety reasons.
- Cache-aware Schedulability Analysis of PREM Compliant TasksPublication . Rashid, Syed Aftab; Awan, Muhammad Ali; Souto, Pedro; Bletsas, Konstantinos; Tovar, EduardoThe Predictable Execution Model (PREM) is useful for mitigating inter-core interference due to shared resources such as the main memory. However, it is cache-agnostic, which makes schedulabulity analysis pessimistic, via overestimation of prefetches and write-backs. In response, we present cache-aware schedulability analysis for PREM tasks on fixed-task-priority partitioned multicores, that bounds the number of cache prefetches and write-backs. Our approach identifies memory blocks loaded in the execution of a previous scheduling interval of each task, that remain in the cache until its next scheduling interval. Doing so, greatly reduces the estimated prefetches and write backs. In experimental evaluations, our analysis improves the schedulability of PREM tasks by up to 55 percentage points.
- Non-Preemptive Scheduling of Periodic Mixed-Criticality Real-Time SystemsPublication . Singh, Jasdeep; Santinelli, Luca; Reghenzani, Federico; Bletsas, Konstantinos; Guo, ZhishanIn this work we develop an offline analysis of periodic mixed-criticality real-time systems. We develop a graph-based exploratory method to non-preemptively schedule multiple criticality tasks. The exploration process obtains a schedule for each periodic instance of the tasks. The schedule adjusts for criticality mode changes to maximize the resource usage by allowing lower criticality executions. At the same time, it ensures that the schedulability of other higher criticality jobs is never compromised. We also quantify the probabilities associated to a criticality mode change by using task probabilistic Worst Case Execution Times. A method to reduce the offline complexity is also proposed.
- Mixed Criticality Scheduling of Probabilistic Real-Time SystemsPublication . Singh, Jasdeep; Santinelli, Luca; Reghenzani, Federico; Bletsas, Konstantinos; Doose, David; Guo, ZhishanIn 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.
- Response time analysis of memory-bandwidth- regulated multiframe mixed-criticality systemsPublication . Hussain, Ishfaq; Awan, Muhammad Ali; Souto, Pedro; Bletsas, Konstantinos; Tovar, EduardoThe multiframe mixed-criticality task model eliminates the pessimism in many systems where the worst-case execution times (WCETs) of successive jobs vary greatly by design, in a known pattern. Existing feasibility analysis techniques for multiframe mixed-criticality tasks are shared-resource-oblivious, hence un-safe for commercial-o -the-shelf (COTS) multicore platforms with a memory controller shared among all cores. Conversely, the feasibility analyses that account for the interference on shared resource(s) in COTS platforms do not leverage theWCET variation in multiframe tasks. This paper extends the state-of-the-art by presenting analysis that incorporates the memory access stall in memory-bandwidth-regulated multiframe mixed-criticality multicore systems. An exhaustive enumeration approach is proposed for this analysis to further enhance the schedulability success ratio. The running time of the exhaustive analysis is improved by proposing a pruning mechanism that eliminates the combinations of interfering job sequences that subsume others. Experimental evaluation, using synthetic task sets, demonstrates up to 72% improvement in terms of schedulability success ratio, compared to frame-agnostic analysis.