This paper considers the scheduling of soft real-time sporadic task systems under global EDF on an iden-tical multiprocessor. Though Pfair scheduling is theoretically optimal for hard real-time task systems on multiprocessors, it can incur significant run-time overhead. Hence, other scheduling algorithms that are not optimal, including EDF, have continued to receive considerable attention. However, prior research on such algorithms has focussed mostly on hard real-time systems, where, to ensure that all deadlines are met, ap-proximately 50 % of the available processing capacity will have to be sacrificed in the worst case. This may be overkill for soft real-time systems that can tolerate deadline misses by bounded amounts (i.e., bounded tardiness). In this paper, we derive tardiness bounds under preemptive and non-preemptive global EDF on multiprocessors when the total utilization of a task system is not restricted and may equal the number of pro-cessors. Our tardiness bounds depend on per-task utilizations and execution costs — the lower these values, the lower the tardiness bounds. As a final remark, we note that global EDF may be superior to partitioned EDF for multiprocessor-based soft real-time systems in that the latter does not offer any scope to improve system utilization even if bounded tardiness can be tolerated.

This paper presents a probabilistic approach to guarantee the performance of a real-time system. While traditional real-time system analysis tends to guarantee that each task instance will complete its execution before its absolute deadline (hard guarantee), our approach permits to estimate the probability that it will happen. Such a statistical guarantee is performed based on interarrival and execution times probability distributions, rather than their worst case values. The advantage of a probabilistic approach is a more efficient usage of system resources, allowing to give a certain level of deadline guarantee to task sets that the classical schedulability analysis would reject.

This paper presents resource management techniques that achieve the qualityof service (QoS) requirements of dynamic real-time systems using open architectures and commercial o-the-shelf technologies (COTS). Dynamic real-time systems are subject to constant changes such as a varying external environment, overload of internal systems, component failure, and evolving operational requirements. Examples of such systems include the emerging generation of computer-based, command and control systems of the U.S. Navy. To enable the engineering of such systems,w present adaptive resource management middlew are techniques that achieve the QoS requirements of the system. The middlew re performs QoS monitoring and failure detection, QoS diagnosis, and reallocation of resources to adapt the system to achieve acceptable levels of QoS. Experimental characterizations of the middlew are using a real-time benchmark illustrate its eectiveness for adapting the system for achieving the desired real-time and survivability QoS during overloaded situations. Keywords

Statistical Rate Monotonic Scheduling (SRMS) is a generalization of the classical RMS results of Liu and Layland [LL73] for periodic tasks with highly variable execution times and statistical QoS requirements. The main tenet of SRMS is that the variability in task resource requirements could be smoothed through aggregation to yield guaranteed QoS. This aggregation is done over time for a given task and across multiple tasks for a given period of time. Similar to RMS, SRMS has two components: a feasibility test and a scheduling algorithm. SRMS feasibility test ensures that it is possible for a given periodic task set to share a given resource without violating any of the statistical QoS constraints imposed on each task in the set. The SRMS scheduling algorithm consists of two parts: a job admission controller and a scheduler. The SRMS scheduler is a simple, preemptive, fixed-priority scheduler. The SRMS job admission controller manages the QoS delivered to the various tasks through admi...

The report gives a state-of-the-art survey of the field of integrated control and scheduling. Subtopics discussed are implementation and scheduling of periodic control loops, scheduling under overload, control and scheduling co-design, dynamic task adaptation, feedback scheduling, and scheduling of imprecise calculations. The report also presents the background, motivation, and research topics in the ARTES project “Integrated

The limitations of the deterministic formulation of scheduling are outlined and a probabilistic approach is motivated. A number of models are reviewed with one being chosen as a basic framework. Response-time analysis is extended to incorporate a probabilistic characterisation of task arrivals and execution times.

Abstract—The More-Less (ML) scheme has been shown to be an efficient approach for maintaining temporal consistency of real-time data objects. Although ML provides a deterministic guarantee in temporal consistency, the number of update transactions that can be supported in a system is limited. This is due to its use of the worst-case computation time in deriving deadlines and periods of update transactions. This paper studies the problem of temporal consistency maintenance where a certain degree of temporal inconsistency is tolerable. A suite of Statistical More-Less (SML) approaches are proposed to explore the trade-off between quality of service (QoS) of temporal consistency and the number of supported transactions. It begins with a base-line algorithm, SML-BA, which provides the requested QoS of temporal consistency. Then, SML with Optimization (SML-OPT) is proposed to further improve the QoS by better utilizing the excess processor capacity. Finally, SML-OPT is enhanced with a Slack Reclaiming scheme (SML-SR). The reclaimed slacks are used to process jobs whose required computation time is larger than the guaranteed computation time. Simulation experiments are conducted to compare the performance of these schemes (SML-BA, SML-OPT, and SML-SR) together with the deterministic More-Less and Half-Half schemes. The results show that the SML schemes are effective in trading the schedulability of transactions for the QoS guaranteed. Moreover, SML-SR performs best and offers a significant QoS improvement over SML-BA and SML-OPT. Index Terms—Real-time database, probabilistic temporal consistency, transactions scheduling, quality of service. 1

In the past decade, the limitations of models considering fixed (worst case) task execution times have been acknowledged for large application classes within soft real-time systems. A more realistic model considers the tasks having varying execution times with given probability distributions. Considering such a model with specified task execution time probability distribution functions, an important performance indicator of the system is the expected deadline miss ratio of the tasks and of the task graphs. This article presents an approach for obtaining this indicator in an analytic way. Our goal is to keep the analysis cost low, in terms of required analysis time and memory, while considering as general classes of target application models as possible. The following main assumptions have been made on the applications which are modelled as sets of task graphs: the tasks are periodic, the task execution times have given generalised probability distribution functions, the task execution deadlines are given and arbitrary, the scheduling policy can belong to practically any class of non-preemptive scheduling policies, and a designer supplied maximum number of concurrent instantiations of the same task graph is tolerated in the system. Experiments show the efficiency of the proposed technique for monoprocessor systems.

. Traditionally, real-time systems require that the deadlines of all jobs be met. For many applications, however, this is an overly stringent requirement. An occasional missed deadline may cause decreased performance but is nevertheless acceptable. We present an analysis technique by which a lower bound on the percentage of deadlines that a periodic task meets is determined and compare the lower bound with simulation results for an example system. We have implemented the technique in the PERTS real-time system prototyping environment [6, 7]. 1 Introduction A distinguishing characteristic of real-time computer systems is the requirement that the system meet its temporal constraints. While there are many different types of constraints, the most common form is expressed in terms of deadlines: a job completes its execution by its deadline. In a hard real-time system, all jobs must meet their deadlines and a missed deadline is treated as a fatal fault. Hence hard real-time systems are desi...

In addition to correctness requirements, a real-time system must also meet its temporal constraints, often expressed as deadlines. We call safety or mission critical real-time systems which may miss some deadlines critical soft real-time systems to distinguish them from hard real-time systems, where all deadlines must be met, and from soft real-time systems which are not safety or mission critical. The performance of a critical soft real-time system is acceptable as long as the deadline miss rate is below an application specific threshold. Architectural features of computer systems, such as caches and branch prediction hardware, are designed to improve average performance. Deterministic real-time design and analysis approaches require that such features be disabled to increase predictability. Alternatively, allowances must be made for for their effects by designing for the worst case. Either approach leads to a decrease in average performance. Since critical soft real-time systems do not require that all deadlines be met, average performance can be improved by adopting a probabilitistic approach. In order to allow a trade-off between deadlines met and average