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

k2U: A General Framework from k-Point Effective Schedulability Analysis to Utilization-Based Tests

To deal with a large variety of workloads in different application domains in real-time embedded systems, a number of expressive task models have been developed. For each individual task model, researchers tend to develop different types of techniques for deriving schedulability tests with different computation complexity and performance. In this paper, we present a general schedulability analysis framework, namely the k2U framework, that can be potentially applied to analyze a large set of real-time task models under any fixed-priority scheduling algorithm, on both uniprocessor and multiprocessor scheduling. The key to k2U is a k-point effective schedulability test, which can be viewed as a "blackbox" interface. For any task model, if a corresponding k-point effective schedulability test can be constructed, then a sufficient utilization-based test can be automatically derived. We show the generality of k2U by applying it to different task models, which results in new and improved tests compared to the state-of-the-art. Analogously, a similar concept by testing only k points with a different formulation has been studied by us in another framework, called k2Q, which provides quadratic bounds or utilization bounds based on a different formulation of schedulability test. With the quadratic and hyperbolic forms, k2Q and k2U frameworks can be used to provide many quantitive features to be measured, like the total utilization bounds, speed-up factors, etc., not only for uniprocessor scheduling but also for multiprocessor scheduling. These frameworks can be viewed as a "blackbox" interface for schedulability tests and response-time analysis

The design and implementation of a multimedia storage server tosupport video-on-demand applications

In this paper we present the design and implementation of a client/server based multimedia architecture for supporting video-on-demand applications. We describe in detail the software architecture of the implementation along with the adopted buffering mechanism. The proposed multithreaded architecture obtains, on one hand, a high degree of parallelism at the server side, allowing both the disk controller and the network card controller work in parallel. On the other hand; at the client side, it achieves the synchronized playback of the video stream at its precise rate, decoupling this process from the reception of data through the network. Additionally, we have derived, under an engineering perspective, some services that a real-time operating system should offer to satisfy the requirements found in video-on-demand applications.This research has been supported by the Regional Research Plan of the Autonomus Community of Madrid under an F.P.I. research grant.Publicad

On-line schedulability tests for adaptive reservations in fixed priority scheduling

Adaptive reservation is a real-time scheduling technique in which each application is associated a fraction of the computational resource (a reservation) that can be dynamically adapted to the varying requirements of the application by using appropriate feedback control algorithms. An adaptive reservation is typically implemented by using an aperiodic server (e.g. sporadic server) algorithm with fixed period and variable budget. When the feedback law demands an increase of the reservation budget, the system must run a schedulability test to check if there is enough spare bandwidth to accommodate such increase. The schedulability test must be very fast, as it may be performed at each budget update, i.e. potentially at each instance of a task; yet, it must be as efficient as possible, to maximize resource usage. In this paper, we tackle the problem of performing an efficient on-line schedulability test for adaptive resource reservations in fixed priority schedulers. In the literature, a number of algorithms have been proposed for on-line admission control in fixed priority systems. We describe four of these tests, with increasing complexity and performance. In addition, we propose a novel on-line test, called Spare-Pot al- gorithm, which has been specifically designed for the problem at hand, and which shows a good cost/performance ratio compared to the other tests

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

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

Investigation of single cart gantry crane system performance using scheduling algorithm

This paper investigates the implementation of two types of scheduling algorithm to obtain the best performances of the Single Cart Gantry Crane System (GCS). In this research, Deadline Monotonic Priority Assignment (DMPA) and Earliest Deadline First (EDF) scheduling algorithm are chosen to be implemented. The main ideas of this approach is to find the schedule that more compatible and provide more stable result for the system. The Cart performances will be analyzed in term of Settling Time (Ts) and Overshoot (OS). In this study, a simple PID controller that acts as a basic control structure is used. The application of TRUETIME kernel block also is implemented to be executed in a MATLAB environment. It has been demonstrated that implementation of these two algorithms will help this system to be more stabilized according to appropriate execution time

Platform-based Plug and Play of Automotive Safety Features - Challenges and Directions

Optional software-based features are increasingly becoming an important cost driver in automotive systems. These include features pertaining to active safety, infotainment, etc. Currently, these optional features are integrated into the vehicles at the factory during assembly. This severely restricts the flexibility of the customer to select and use features on-demand and therefore, the customer will either have to be satisfied with an available set of feature options or pre-order a car with the required features from the manufacturer resulting in considerable delay. In order to increase flexibility and reduce the delay, it is necessary to provide the option to configure the vehicle on-demand at the dealership or remotely. In this paper, we present our vision and challenges involved in developing a platform infrastructure that allows on-demand deployment of automotive safety features and ensures their correct execution