Soft real-time scheduling on multiprocessors

The design of real-time systems is being impacted by two trends. First, tightly-coupled multiprocessor platforms are becoming quite common. This is evidenced by the availability of affordable symmetric shared-memory multiprocessors and the emergence of multicore architectures. Second, there is an increase in the number of real-time systems that require only soft real-time guarantees and have workloads that necessitate a multiprocessor. Examples of such systems include some tracking, signal-processing, and multimedia systems. Due to the above trends, cost-effective multiprocessor-based soft real-time system designs are of growing importance. Most prior research on real-time scheduling on multiprocessors has focused only on hard real-time systems. In a hard real-time system, no deadline may ever be missed. To meet such stringent timing requirements, all known theoretically optimal scheduling algorithms tend to preempt process threads and migrate them across processors frequently, and also impose certain other restrictions. Hence, the overheads of such algorithms can significantly reduce the amount of useful work that is accomplished and limit their practical implementation. On the other hand, non-optimal algorithms that are more practical suffer from the drawback that their validation tests require workload restrictions that can approach roughly 50% of the available processing capacity. Thus, for soft real-time systems, which can tolerate occasional or bounded deadline misses, and hence, allow for a tradeoff between timeliness and improved processor utilization, the existing scheduling algorithms or their validation tests can be overkill. The thesis of this dissertation is: Processor utilization can be improved on multiprocessors while providing non-trivial soft real-time guarantees for different soft real-time applications, whose preemption and migration overheads can span different ranges and whose tolerances to tardiness are different, by designing new algorithms, simplifying optimal algorithms, and developing new validation tests. The above thesis is established by developing validation tests that are sufficient to provide soft real-time guarantees under non-optimal (but more practical) algorithms, designing and analyzing a new restricted-migration scheduling algorithm, determining the guarantees on timeliness that can be provided when some limiting restrictions of known optimal algorithms are relaxed, and quantifying the benefits of the proposed mechanisms through simulations. First, we show that both preemptive and non-preemptive global earliest-deadline-first(EDF) scheduling can guarantee bounded tardiness (that is, lateness) to every recurrent real-time task system while requiring no restriction on the workload (except that it not exceed the available processing capacity). The tardiness bounds that we derive can be used to devise validation tests for soft real-time systems that are EDF-scheduled. Though overheads due to migrations and other factors are lower under EDF (than under known optimal algorithms), task migrations are still unrestricted. This may be unappealing for some applications, but if migrations are forbidden entirely, then bounded tardiness cannot always be guaranteed. Hence, we consider providing an acceptable middle path between unrestricted-migration and no-migration algorithms, and as a second result, present a new algorithm that restricts, but does not eliminate, migrations. We also determine bounds on tardiness that can be guaranteed under this algorithm. Finally, we consider a more efficient but non-optimal variant of an optimal class of algorithms called Pfair scheduling algorithms. We show that under this variant, called earliest- pseudo-deadline-first (EPDF) scheduling, significantly more liberal restrictions on workloads than previously known are sufficient for ensuring a specified tardiness bound. We also show that bounded tardiness can be guaranteed if some limiting restrictions of optimal Pfair algorithms are relaxed. The algorithms considered in this dissertation differ in the tardiness bounds guaranteed and overheads imposed. Simulation studies show that these algorithms can guarantee bounded tardiness for a significant percentage of task sets that are not schedulable in a hard real-time sense. Furthermore, for each algorithm, conditions exist in which it may be the preferred choice

Compositional Analysis Techniques For Multiprocessor Soft Real-Time Scheduling

The design of systems in which timing constraints must be met (real-time systems) is being affected by three trends in hardware and software development. First, in the past few years, multiprocessor and multicore platforms have become standard in desktop and server systems and continue to expand in the domain of embedded systems. Second, real-time concepts are being applied in the design of general-purpose operating systems (like Linux) and attempts are being made to tailor these systems to support tasks with timing constraints. Third, in many embedded systems, it is now more economical to use a single multiprocessor instead of several uniprocessor elements; this motivates the need to share the increasing processing capacity of multiprocessor platforms among several applications supplied by different vendors and each having different timing constraints in a manner that ensures that these constraints were met. These trends suggest the need for mechanisms that enable real-time tasks to be bundled into multiple components and integrated in larger settings. There is a substantial body of prior work on the multiprocessor schedulability analysis of real-time systems modeled as periodic and sporadic task systems. Unfortunately, these standard task models can be pessimistic if long chains of dependent tasks are being analyzed. In work that introduces less pessimistic and more sophisticated workload models, only partitioned scheduling is assumed so that each task is statically assigned to some processor. This results in pessimism in the amount of needed processing resources. In this dissertation, we extend prior work on multiprocessor soft real-time scheduling and construct new analysis tools that can be used to design component-based soft real-time systems. These tools allow multiprocessor real-time systems to be designed and analyzed for which standard workload and platform models are inapplicable and for which state-of-the-art uniprocessor and multiprocessor analysis techniques give results that are too pessimistic

Generalized tardiness bounds for global multiprocessor scheduling

We consider the issue of deadline tardiness under global multiprocessor scheduling algorithms. We present a general tardiness-bound derivation that is applicable to a wide variety of such algorithms (including some whose tardiness behavior has not been analyzed before). Our derivation is very general: job priorities may change rather arbitrarily at runtime, capacity restrictions may exist on certain processors, and, under certain conditions, non-preemptive regions are allowed. Our results show that, with the exception of static-priority algorithms, most global algorithms considered previously have bounded tardiness. In addition, our results provide a simple means for checking whether tardiness is bounded under newly-developed algorithms

Optimal rate-based scheduling on multiprocessors

The PD2 Pfair/ERfair scheduling algorithm is the most efficient known algorithm for optimally scheduling periodic tasks on multiprocessors. In this paper, we prove that PD2 is also optimal for scheduling “rate-based” tasks whose processing steps may be highly jittered. The rate-based task model we consider generalizes the widely-studied sporadic task model

An EDF-based restricted-migration scheduling algorithm for multiprocessor soft real-time systems

There has been much recent interest in the use of the earliest-deadline-first (EDF) algorithm for scheduling soft real-time sporadic task systems on identical multiprocessors. In hard real-time systems, a significant disparity exists between EDF-based schemes and Pfair scheduling: on M processors, the worst-case schedulable utilization for all known EDF variants is approximately M/2, whereas it is M for optimal Pfair algorithms. This is unfortunate because EDF-based algorithms entail lower scheduling and task-migration overheads. However, such a disparity in schedulability can be alleviated by easing the requirement that all deadlines be met, which may be sufficient for soft real-time systems. In particular, in recent work, we have shown that if task migrations are not restricted, then EDF (i.e., global EDF) can ensure bounded tardiness for a sporadic task system with no restrictions on total utilization. Unrestricted task migrations in global EDF may be unappealing for some systems, but if migrations are forbidden entirely, then bounded tardiness cannot be guaranteed. In this paper, we address the issue of striking a balance between task migrations and system utilization by proposing an algorithm called EDF-fm, which is based upon EDF and treads a middle path, by restricting, but not eliminating, task migrations. Specifically, under EDF-fm, the ability to migrate is required for at most M − 1 tasks, and it is sufficient that every such task migrate between two processors and at job boundaries only. EDF-fm, like global EDF, can ensure bounded tardiness to a sporadic task system as long as the available processing capacity is not exceeded, but, unlike global EDF, may require that per-task utilizations be capped. The required cap is quite liberal, hence, EDF-fm should enable a wide range of soft real-time applications to be scheduled with no constraints on total utilization

Tardiness bounds under global EDF scheduling on a multiprocessor

We consider the scheduling of a sporadic real-time task system on an identical multiprocessor. Though Pfair algorithms are theoretically optimal for such task systems, in practice, their runtime overheads can significantly reduce the amount of useful work that is accomplished. On the other hand, if all deadlines need to be met, then every known non-Pfair algorithm requires restrictions on total system utilization that can approach approximately 50% of the available processing capacity. This may be overkill for soft real-time systems, which can tolerate occasional or bounded deadline misses (i.e., bounded tardiness). In this paper we derive tardiness bounds under preemptive and non-preemptive global EDF when the total system utilization is not restricted, except that it not exceed the available processing capacity. Hence, processor utilization can be improved for soft real-time systems on multiprocessors. Our tardiness bounds depend on the total system utilization and 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

Adaptive Multiprocessor Real-Time Systems

Over the past few years, as multicore technology has become cost-effective, multiprocessor systems have become increasingly prevalent. The growing availability of such systems has spurred the development of computationally-intensive applications for which single-processor designs are insufficient. Many such applications have timing constraints; such timing constraints are often not static, but may change in response to both external and internal stimuli. Examples of such applications include tracking systems and many multimedia applications. Motivated by these observations, this dissertation proposes several different adaptive scheduling algorithms that are capable of guaranteeing flexible timing constraints on multiprocessor platforms. Under traditional task models (e.g., periodic, sporadic, etc.), the schedulability of a system is based on each task’s worst-case execution time (WCET), which defines the maximum amount of time that each of its jobs can execute. The disadvantage of using WCETs is that systems may be deemed unschedulable even if they would function correctly most of the time when deployed. Adaptive real-time scheduling algorithms allow the timing constraints of applications to be adjusted based upon runtime conditions, instead of always using fixed timing constraints based upon WCETs. While there is a substantial body of prior work on scheduling applications with static timing constraints on multiprocessor systems, prior to this dissertation, no adaptive multiprocessor scheduling approach existed that is capable of ensuring bounded “error” (where error is measured by comparison to an ideal allocation). In this dissertation, this limitation is addressed by proposing five different multiprocessor scheduling algorithms that allow a task’s timing constraints to change at runtime. The five proposed adaptive algorithms are based on different non-adaptive multiprocessor scheduling algorithms that place different restrictions on task migrations and preemptions. The relative advantages of these algorithms are compared by simulating both the Whisper human tracking system and the Virtual Exposure Camera (VEC), both of which were developed at The University of North Carolina at Chapel Hill. In addition, a feedback-based adaptive framework is proposed that not only allows timing constraints to adapt at runtime, but also detects which adaptions are needed. An implementation of this adaptive framework on a real-time multiprocessor testbed is discussed and its performance is evaluated by using the core operations of both Whisper and VEC. From this dissertation, it can be concluded that feedback and optimization techniques can be used to determine at runtime which adaptions are needed. Moreover, the accuracy of an adaptive algorithm can be improved by allowing more frequent task migrations and preemptions; however, this accuracy comes at the expense of higher migration and preemption costs, which impacts average-case performance. Thus, there is a tradeoff between accuracy and average-case performance that depends on the frequency of task migrations/preemptions and their cost

On the design and implementation of a cache-aware soft real-time scheduler for multicore platforms

Real-time systems are those for which timing constraints must be satisfied. In this dissertation, research on multiprocessor real-time systems is extended to support multicore platforms, which contain multiple processing cores on a single chip. Specifically, this dissertation focuses on designing a cache-aware real-time scheduler to reduce shared cache miss rates, and increase the level of shared cache reuse, on multicore platforms when timing constraints must be satisfied. This scheduler, implemented in Linux, employs: (1) a scheduling method for real-time workloads that satisfies timing constraints while making scheduling choices that reduce shared cache miss rates; and (2) a profiler that quantitatively approximates the cache impact of every task during its execution. In experiments, it is shown that the proposed cache-aware scheduler can result in significantly reduced shared cache miss rates over other approaches. This is especially true when sufficient hardware support is provided, primarily in the form of cache-related performance monitoring features. It is also shown that scheduler-related overheads are comparable to other scheduling approaches, and therefore overheads would not be expected to offset any reduction in cache miss rate. Finally, in experiments involving a multimedia server workload, it was found that the use of the proposed cache-aware scheduler allowed the size of the workload to be increased. Prior work in the area of cache-aware scheduling for multicore platforms has not addressed support for real-time workloads, and prior work in the area of real-time scheduling has not addressed shared caches on multicore platforms. For real-time workloads running on multicore platforms, a decrease in shared cache miss rates can result in a corresponding decrease in execution times, which may allow a larger real-time workload to be supported, or hardware requirements (or costs) to be reduced. As multicore platforms are becoming ubiquitous in many domains, including those in which real-time constraints must be satisfied, cache-aware scheduling approaches such as that presented in this dissertation are of growing importance. If the chip manufacturing industry continues to adhere to the multicore paradigm (which is likely, given current projections), then such approaches should remain relevant as processors evolve

Improved Conditions for Bounded Tardiness under EPDF Pfair Multiprocessor Scheduling ✩

The earliest-pseudo-deadline-first (EPDF) Pfair algorithm is more efficient than other known Pfair scheduling algorithms, but is not optimal for scheduling recurrent real-time task systems on more than two identical processors. Although not optimal, EPDF may be preferable for real-time systems instantiated on less-powerful platforms, those with soft timing constraints, or those whose task composition can change at run-time. In prior work, Srinivasan and Anderson established a sufficient per-task utilization restriction for ensuring a tardiness of at most q quanta, where q ≥ 1, under EPDF. They also conjectured that under this algorithm, a tardiness bound of one quantum applies to task systems that are not subject to any restriction other than the obvious restrictions, namely, that the total system utilization not exceed the available processing capacity and per-task utilizations not exceed 1.0. In this paper, we present counterexamples that show that their conjecture is false and present sufficient per-task utilization restrictions that are more liberal than theirs. For ensuring a tardiness bound of one quantum, our restriction presents an improvement of 50 % over the previous one. Key words: soft real-time, multiprocessors, Pfairness, scheduling, tardiness bound