Scheduling Techniques for Operating Systems for Medical and IoT Devices: A Review

Software and Hardware synthesis are the major subtasks in the implementation of hardware/software systems. Increasing trend is to build SoCs/NoC/Embedded System for Implantable Medical Devices (IMD) and Internet of Things (IoT) devices, which includes multiple Microprocessors and Signal Processors, allowing designing complex hardware and software systems, yet flexible with respect to the delivered performance and executed application. An important technique, which affect the macroscopic system implementation characteristics is the scheduling of hardware operations, program instructions and software processes. This paper presents a survey of the various scheduling strategies in process scheduling. Process Scheduling has to take into account the real-time constraints. Processes are characterized by their timing constraints, periodicity, precedence and data dependency, pre-emptivity, priority etc. The affect of these characteristics on scheduling decisions has been described in this paper

Analyzing the effect of gain time on soft task scheduling policies in real-time systems

In hard real-time systems, gain time is defined as the difference between the Worst Case Execution Time (WCET) of a hard task and its actual processor consumption at runtime. This paper presents the results of an empirical study about how the presence of a significant amount of gain time in a hard real-time system questions the advantages of using the most representative scheduling algorithms or policies for aperiodic or soft tasks in fixed-priority preemptive systems. The work presented here refines and complements many other studies in this research area in which such policies have been introduced and compared. This work has been performed by using the authors' testing framework for soft scheduling policies, which produces actual, synthetic, randomly generated applications, executes them in an instrumented Real-Time Operating System (RTOS), and finally processes this information to obtain several statistical outcomes. The results show that, in general, the presence of a significant amount of gain time reduces the performance benefit of the scheduling policies under study when compared to serving the soft tasks in background, which is considered the theoretical worst case. In some cases, this performance benefit is so small that the use of a specific scheduling policy for soft tasks is questionable. © 2012 IEEE.This work is partially funded by research projects PROMETEO/2008/051, CSD2007-022, and TIN2008-04446.Búrdalo Rapa, LA.; Terrasa Barrena, AM.; Espinosa Minguet, AR.; García Fornes, AM. (2012). Analyzing the effect of gain time on soft task scheduling policies in real-time systems. IEEE Transactions on Software Engineering. 38(6):1305-1318. https://doi.org/10.1109/TSE.2011.95S1305131838

An efficient aperiodic task server for energy harvesting embedded systems

International audienceThe energy existing in our environment can be converted into electricity to supply a wireless device such as sensor node. In this paper, we will address a problem of scheduling for a device that executes a mixed set of real-time tasks, composed of aperiodic and hard deadline periodic tasks. High responsiveness of the aperiodic tasks and timeliness of the periodic tasks can be performed through an aperiodic task server that takes into account both time and energy limitations. This paper describes an extension of the well known TBS (Total Bandwidth Server) which is energy harvesting aware. The performance of the new aperiodic server, called TB-H, is evaluated and compared to background approaches through simulation experiments

Generalizing List Scheduling for Stochastic Soft Real-time Parallel Applications

Advanced architecture processors provide features such as caches and branch prediction that result in improved, but variable, execution time of software. Hard real-time systems require tasks to complete within timing constraints. Consequently, hard real-time systems are typically designed conservatively through the use of tasks? worst-case execution times (WCET) in order to compute deterministic schedules that guarantee task?s execution within giving time constraints. This use of pessimistic execution time assumptions provides real-time guarantees at the cost of decreased performance and resource utilization. In soft real-time systems, however, meeting deadlines is not an absolute requirement (i.e., missing a few deadlines does not severely degrade system performance or cause catastrophic failure). In such systems, a guaranteed minimum probability of completing by the deadline is sufficient. Therefore, there is considerable latitude in such systems for improving resource utilization and performance as compared with hard real-time systems, through the use of more realistic execution time assumptions. Given probability distribution functions (PDFs) representing tasks? execution time requirements, and tasks? communication and precedence requirements, represented as a directed acyclic graph (DAG), this dissertation proposes and investigates algorithms for constructing non-preemptive stochastic schedules. New PDF manipulation operators developed in this dissertation are used to compute tasks? start and completion time PDFs during schedule construction. PDFs of the schedules? completion times are also computed and used to systematically trade the probability of meeting end-to-end deadlines for schedule length and jitter in task completion times. Because of the NP-hard nature of the non-preemptive DAG scheduling problem, the new stochastic scheduling algorithms extend traditional heuristic list scheduling and genetic list scheduling algorithms for DAGs by using PDFs instead of fixed time values for task execution requirements. The stochastic scheduling algorithms also account for delays caused by communication contention, typically ignored in prior DAG scheduling research. Extensive experimental results are used to demonstrate the efficacy of the new algorithms in constructing stochastic schedules. Results also show that through the use of the techniques developed in this dissertation, the probability of meeting deadlines can be usefully traded for performance and jitter in soft real-time systems

Combined scheduling of hard and soft real-time tasks in multiprocessor systems

Many complex real-time systems are composed of both hard and soft real-time tasks. Combined scheduling of hard and soft tasks in such systems should satisfy two important goals: (1) maximize the schedulability of soft real-time tasks with no or little impact on the schedulability of hard real-time tasks; (2) minimize the scheduling overhead. In this thesis, we develop two sets of algorithms for the problem, of which the first set allows sacrificing the schedulability of hard tasks and the second set does not. The first set of algorithms is based on a new concept, called task association , by which each soft task is associated with a hard task, whenever possible, in order to minimize the scheduling overhead. The second set has two algorithms, namely, background scheduling and emergency based scheduling. The background scheduling schedules soft tasks in the holes that are present in the schedule considering only the hard tasks. The emergency based scheduling always maintains two schedules (primary schedule and emergency schedule) and switches back and forth between them during the schedule construction process depending on the schedulability of a given hard task. To evaluate the schedulability of the proposed algorithms, extensive simulation studies were conducted and the results show that the proposed algorithms are superior to existing algorithms, in addition to some of them incurring lesser scheduling overhead

The jointly scheduling of hard periodic tasks with soft aperiodic events within the Real-Time Specification for Java (RTSJ)

The studied problem is the jointly scheduling of hard periodic tasks with soft aperiodic events, where the response times of soft tasks have to be as low as possible while the warranty to meet their deadlines has to be given to hard tasks. A lot of theoretical solutions have been proposed these past two decades but we are interested on the implementability of these solutions under the real-time specification for Java (RTSJ), without changing the scheduler. This led us to adapt the existing algorithms to operate at a user land level in the system, to propose some optimizations and counter measures in order to balance the lost of performances and finally to set up an approximate slack stealer algorithm specifically designed to take into account RTSJ restrictions. We propose new classes to extend the RTSJ API's to implement these mechanisms and some minor modification suggestions to existing ones as a feed back from our RTSJ experiences. We demonstrates the efficiency of the modified algorithms through extensive simulations and the implementability on available RTSJ compliant virtual machine by an overhead measure in real situation with the RTSJ JamaïcaVM from Aïcas. We also measure the overhead on LejosRT, an RTSJ compliant firmware for Lego Mindstorms NXT in development

Rate Monotonic vs. EDF: Judgment Day

Since the first results published in 1973 by Liu and Layland on the Rate Monotonic (RM) and Earliest Deadline First (EDF) algorithms, a lot of progress has been made in the schedulability analysis of periodic task sets. Unfortunately, many misconceptions still exist about the properties of these two scheduling methods, which usually tend to favor RMmore than EDF. Typical wrong statements often heard in technical conferences and even in research papers claim that RM is easier to analyze than EDF, it introduces less runtime overhead, it is more predictable in overload conditions, and causes less jitter in task execution. Since the above statements are either wrong, or not precise, it is time to clarify these issues in a systematic fashion, because the use of EDF allows a better exploitation of the available resources and significantly improves system’s performance. This paper comparesRMagainstEDFunder several aspects, using existing theoretical results, specific simulation experiments, or simple counterexamples to show that many common beliefs are either false or only restricted to specific situations

Schedulability-driven scratchpad memory swapping for resource-constrained real-time embedded systems

In resource-constrained real-time embedded systems, scratchpad memory (SPM) is utilized in place of cache to increase performance and enforce consistent behavior of both hard and soft real-time tasks via software-controlled SPM management techniques (SPMMTs). Real-time systems depend on time critical (hard) tasks to complete execution before their deadline times. Many real-time systems also depend on the execution of soft tasks that do not have to complete by hard deadlines. This thesis evaluates a new SPMMT that increases both worst-case task slack time (TST) and soft task processing capabilities, by combining two existing SPMMTs. The schedulability-driven ACETRB / WCETRB swapping (SDAWS) SPMMT of this thesis uses task schedulability characteristics to control the selection of either the average-case execution time reduction based (ACETRB) SPMMT or the worst-case execution time reduction based (WCETRB) SPMMT. While the literature contains examples of combined management techniques, until now there have been none that combine both WCETRB and ACETRB SPMMTs. The advantage of combining them is to achieve WCET reduction comparable to what can be achieved with the WCETRB SPMMT, while achieving significantly reduced ACET relative to the WCETRB SPMMT. Using a stripped-down RTOS and an SPMMT simulator implemented for this work, evaluated resource-constrained scenarios show a reduction in task slack time from the SDAWS SPMMT relative to the WCETRB SPMMT between 20% and 45%. However, the evaluated scenarios also conservatively show that SDAWS can reduce ACET relative to the WCETRB SPMMT by up to 60%