Giorgio C. Buttazzo

Integrating multimedia applications in hard real-time systems

This paper focuses on the problem of providing efficient run-time support to multimedia applications in a real-time system, where two types of tasks can coexist simultaneously: multimedia soft real-time tasks and hard real-time tasks. Hard tasks are guaranteed based on worst case execution times and minimum interarrival times, whereas multimedia and soft tasks are served based on mean parameters. The paper describes a server-based mechanism for scheduling soft and multimedia tasks without jeopardizing the a priori guarantee of hard real-time activities. The performance of the proposed method is compared with that of similar service mechanisms through extensive simulation experiments and several multimedia applications have been implemented on the HARTIK kernel.

Hard Real-Time Computing Systems

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Real Time Scheduling Theory: A Historical Perspective

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Measuring the Performance of Schedulability Tests

In this 25th year anniversary paper for the IEEE Real Time Systems Symposium, we review the key results in real-time scheduling theory and the historical events that led to the establishment of the current real-time computing infrastructure. We conclude this paper by looking at the challenges ahead of us.

Implications of classical scheduling results for real-time systems

The high computational complexity required for performing an exact schedulability analysis of fixed priority systems has led the research community to investigate new feasibility tests which are less complex than exact tests, but still provide a reasonable performance in terms of acceptance ratio. The performance of a test is typically evaluated by generating a huge number of synthetic task sets and then computing the fraction of those that pass the test with respect to the total number of feasible ones. The resulting ratio, however, depends on the metrics used for evaluating the performance and on the method for generating random task parameters. In particular, an important factor that affects the overall result of the simulation is the probability density function of the random variables used to generate the task set parameters. In this paper we discuss and compare three different metrics that can be used for evaluating the performance of schedulability tests. Then, we investigate how the random generation procedure can bias the simulation results of some specific scheduling algorithm. Finally, we present an efficient method for generating task sets with uniform distribution in a given space, and show how some intuitive solutions typically used for task set generation can bias the simulation results.

Scheduling Aperiodic Tasks in Dynamic Priority Systems

Knowledge of complexity, fundamental limits and performance bounds-well known for many scheduling problems-helps real time designers choose a good design and algorithm and avoid poor ones. The scheduling problem has so many dimensions that it has no accepted taxonomy. We divide scheduling theory between uniprocessor and multiprocessor results. In the uniprocessor section, we begin with independent tasks and then consider shared resources and overload. In the multiprocessor section, we divide the work between static and dynamic algorithms. >

An implicit prioritized access protocol for wireless sensor networks

In this paper we present five new on-line algorithms for servicing soft aperiodic requests in realtime systems, where a set of hard periodic tasks is scheduled using the Earliest Deadline First (EDF) algorithm. All the proposed solutions can achieve full processor utilization and enhance aperiodic responsiveness, still guaranteeing the execution of the periodic tasks. Operation of the algorithms, performance, schedulability analysis, and implementation complexity are discussed and compared with classical alternative solutions, such as background and polling service. Extensive simulations show that algorithms with contained run-time overhead present nearly optimal responsiveness.A valuable contribution of this work is to provide the real-time system designer with a wide range of practical solutions which allow to balance efficiency against implementation complexity.

Rate monotonic vs. EDF: judgment day

Recent advances in wireless technology have brought us closer to the vision of pervasive computing where sensors/actuators can be connected through a wireless network. Due to cost constraints and the dynamic nature of sensor networks, it is undesirable to assume the existence of base stations connected by a wired backbone. In this paper, we present a network architecture suitable for sensor networks along with a medium access control protocol based on earliest deadline first.

Elastic scheduling for flexible workload management

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 RM more 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 systems performance.This paper compares RM against EDF under 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 analysis of periodic fixed priority systems

An increasing number of real-time applications related to multimedia and adaptive control systems require greater flexibility than classical real-time theory usually permits. We present a novel scheduling framework in which tasks are treated as springs with given elastic coefficients to better conform to the actual load conditions. Under this model, periodic tasks can intentionally change their execution rate to provide different quality of service and the other tasks can automatically adapt their periods to keep the system underloaded. The proposed model can also be used to handle overload conditions in a more flexible way and to provide a simple and efficient mechanism for controlling a systems performance as a function of the current load.