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

Statistic Rate Monotonic Scheduling

In this paper we present Statistical Rate Monotonic Scheduling (SRMS), a generalization of the classical RMS results of Liu and Layland that allows scheduling periodic tasks with highly variable execution times and statistical QoS requirements. Similar to RMS, SRMS has two components: a feasibility test and a scheduling algorithm. The feasibility test for SRMS ensures that using SRMS' scheduling algorithms, it is possible for a given periodic task set to share a given resource (e.g. a processor, communication medium, switching device, etc.) in such a way that such sharing does not result in the violation of any of the periodic tasks QoS constraints. The SRMS scheduling algorithm incorporates a number of unique features. First, it allows for fixed priority scheduling that keeps the tasks' value (or importance) independent of their periods. Second, it allows for job admission control, which allows the rejection of jobs that are not guaranteed to finish by their deadlines as soon as they are released, thus enabling the system to take necessary compensating actions. Also, admission control allows the preservation of resources since no time is spent on jobs that will miss their deadlines anyway. Third, SRMS integrates reservation-based and best-effort resource scheduling seamlessly. Reservation-based scheduling ensures the delivery of the minimal requested QoS; best-effort scheduling ensures that unused, reserved bandwidth is not wasted, but rather used to improve QoS further. Fourth, SRMS allows a system to deal gracefully with overload conditions by ensuring a fair deterioration in QoS across all tasks---as opposed to penalizing tasks with longer periods, for example. Finally, SRMS has the added advantage that its schedulability test is simple and its scheduling algorithm has a constant overhead in the sense that the complexity of the scheduler is not dependent on the number of the tasks in the system. We have evaluated SRMS against a number of alternative scheduling algorithms suggested in the literature (e.g. RMS and slack stealing), as well as refinements thereof, which we describe in this paper. Consistently throughout our experiments, SRMS provided the best performance. In addition, to evaluate the optimality of SRMS, we have compared it to an inefficient, yet optimal scheduler for task sets with harmonic periods.National Science Foundation (CCR-970668

Scalability in Real-Time Systems

The number and complexity of applications that run in real-time environments have posed demanding requirements on the part of the real-time system designer. It has now become important to accommodate the application complexity at early stages of the design cycle. Further, the stringent demands to guarantee task deadlines (particularly in a hard real-time environment, which is the assumed environment in this thesis) have motivated both practioners and researchers to look at ways to analyze systems prior to run-time. This thesis reports a new perspective to analyzing real-time systems that in addition to ascertaining the ability of a system to meet task deadlines also qualifies these guarantees. The guarantees are qualified by a measure (called the scaling factor) of the systems ability to continue to provide these guarantees under possible changes to the tasks. This measure is shown to have many applications in the design (task execution time estimation), development (portability and fault tolerance) and maintenance (scalability) of real-time systems. The measure is shown to bear relevance in both uniprocessor and distributed (more generally referred to as end-to-end) real-time systems. However, the derivation of this measure in end-to-end systems requires that we solve a fundamental (very important, yet unsolved) problem--the end-to-end schedulability problem. The thesis reports a solution to the end-to-end schedulability problem which is based on a solution to another fundamental problem relevant to single-component real-time systems (a uniprocessor system is a special instance of such a system). The problem of interest here is the schedulability of a set of tasks with arbitrary arrival times, that run on a single component. The thesis presents an optimal solution to this problem. One important consequence of this result (besides serving as a basis for the end-to-end schedulability problem) is its applicability to tbe classical approach to real-time scheduling, viz., static scheduling. The final contribution of the thesis comes as an application of the results to the area of real-time communication. More specifically, we report a heuristic approach to the problem of admission control in real-time traffic networks. The heuristic is based on the scaling factor measure

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

A Survey of Research into Mixed Criticality Systems

This survey covers research into mixed criticality systems that has been published since Vestal’s seminal paper in 2007, up until the end of 2016. The survey is organised along the lines of the major research areas within this topic. These include single processor analysis (including fixed priority and EDF scheduling, shared resources and static and synchronous scheduling), multiprocessor analysis, realistic models, and systems issues. The survey also explores the relationship between research into mixed criticality systems and other topics such as hard and soft time constraints, fault tolerant scheduling, hierarchical scheduling, cyber physical systems, probabilistic real-time systems, and industrial safety standards

Energy-aware Fault-tolerant Scheduling for Hard Real-time Systems

Over the past several decades, we have experienced tremendous growth of real-time systems in both scale and complexity. This progress is made possible largely due to advancements in semiconductor technology that have enabled the continuous scaling and massive integration of transistors on a single chip. In the meantime, however, the relentless transistor scaling and integration have dramatically increased the power consumption and degraded the system reliability substantially. Traditional real-time scheduling techniques with the sole emphasis on guaranteeing timing constraints have become insufficient. In this research, we studied the problem of how to develop advanced scheduling methods on hard real-time systems that are subject to multiple design constraints, in particular, timing, energy consumption, and reliability constraints. To this end, we first investigated the energy minimization problem with fault-tolerance requirements for dynamic-priority based hard real-time tasks on a single-core processor. Three scheduling algorithms have been developed to judiciously make tradeoffs between fault tolerance and energy reduction since both design objectives usually conflict with each other. We then shifted our research focus from single-core platforms to multi-core platforms as the latter are becoming mainstream. Specifically, we launched our research in fault-tolerant multi-core scheduling for fixed-priority tasks as fixed-priority scheduling is one of the most commonly used schemes in the industry today. For such systems, we developed several checkpointing-based partitioning strategies with the joint consideration of fault tolerance and energy minimization. At last, we exploited the implicit relations between real-time tasks in order to judiciously make partitioning decisions with the aim of improving system schedulability. According to the simulation results, our design strategies have been shown to be very promising for emerging systems and applications where timeliness, fault-tolerance, and energy reduction need to be simultaneously addressed

Distributed real-time fault tolerance in a virtualized separation kernel

Computers are increasingly being placed in scenarios where a computer error could result in the loss of human life or significant financial loss. Fault tolerant techniques must be employed to prevent an error from resulting in a fault causing such losses. Two types of errors that are common in real-time and embedded system are soft errors, i.e. data bit corruption, and timing errors, such as missed deadlines. Purely software based techniques to address these types of errors have the advantage of not requiring specialized hardware and are able to use more readily available commercial off-the-shelf hardware. Timing errors are addressed using Adaptive Mixed-Criticality, a scheduling technique where higher criticality tasks are given precedence over those of lower criticality when it is impossible to guarantee the schedulability of all tasks. While mixed-criticality scheduling has gained attention in recent years, most approaches assume a periodic task model and that the system has a single criticality level which dictates the available budget to all tasks. In practice these assumptions do not hold: different types of tasks are better served by different scheduling approaches and only a subset of high critical tasks might require additional capacity to meet deadlines. In the latter case, this occurs when a process has experienced a fault and requires additional capacity to perform the recovery. In this thesis, soft errors are addressed using a novel real-time fault tolerance method based on a virtualized separation kernel. Instead of executing redundant copies of an application on separate machines, the applications are consolidated onto one multi-core processor and use hardware virtualization extensions to partition the applications. This allows new recovery schemes to be explored. In addition, the maximum recovery time is sufficiently bounded to ensure recovery occurs in a timely manner without affecting the normal execution of the application. A virtualized separation kernel in combination with Adaptive Mixed-Criticality techniques creates a fault tolerant system that predictably detects and recovers from timing and soft errors

High Performance Real-Time Scheduling Framework for Multiprocessor Systems

Embedded systems, performing specific functions in modern devices, have become pervasive in today's technology landscape. As many of these systems are real-time systems, they necessitate operations with stringent time constraints. This is especially evident in sectors like automotive and aerospace. This thesis introduces a High Performance Real-time Scheduling (HPRTS) framework, which is designed to navigate the multifaceted challenges faced by multiprocessor real-time systems. To begin with, the research attempts to bridge the gap between system reliability and resource sharing in Mixed-Criticality Systems (MCS). In addressing this, a novel fault-tolerance solution is presented. Its main goal is to enhance fault management and reduce blocking time during fault tolerance. Following this, the thesis delves into task allocation in systems with shared resources. In this context, we introduce a distinct Resource Contention Model (RCM). Using this model as a foundation, our allocation strategy is formulated with the aim to reduce resource contention. Moreover, in light of the escalating system complexity where tasks are represented using Directed Acyclic Graph (DAG) models, the research unveils a new Response Time Analysis (RTA) for multi-DAG systems. This particular analysis has been tailored to provide a safe and more refined bound. Reflecting on the contributions made, the achievements of the thesis highlight the potency of the HPRTS framework in steering real-time embedded systems toward high performance