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

A Response-Time Analysis for Non-Preemptive Job Sets under Global Scheduling

An effective way to increase the timing predictability of multicore platforms is to use non-preemptive scheduling. It reduces preemption and job migration overheads, avoids intra-core cache interference, and improves the accuracy of worst-case execution time (WCET) estimates. However, existing schedulability tests for global non-preemptive multiprocessor scheduling are pessimistic, especially when applied to periodic workloads. This paper reduces this pessimism by introducing a new type of sufficient schedulability analysis that is based on an exploration of the space of possible schedules using concise abstractions and state-pruning techniques. Specifically, we analyze the schedulability of non-preemptive job sets (with bounded release jitter and execution time variation) scheduled by a global job-level fixed-priority (JLFP) scheduling algorithm upon an identical multicore platform. The analysis yields a lower bound on the best-case response-time (BCRT) and an upper bound on the worst-case response time (WCRT) of the jobs. In an empirical evaluation with randomly generated workloads, we show that the method scales to 30 tasks, a hundred thousand jobs (per hyperperiod), and up to 9 cores.info:eu-repo/semantics/publishedVersio

A Response-Time Analysis for Non-Preemptive Job Sets under Global Scheduling

An effective way to increase the timing predictability of multicore platforms is to use non-preemptive scheduling. It reduces preemption and job migration overheads, avoids intra-core cache interference, and improves the accuracy of worst-case execution time (WCET) estimates. However, existing schedulability tests for global non-preemptive multiprocessor scheduling are pessimistic, especially when applied to periodic workloads. This paper reduces this pessimism by introducing a new type of sufficient schedulability analysis that is based on an exploration of the space of possible schedules using concise abstractions and state-pruning techniques. Specifically, we analyze the schedulability of non-preemptive job sets (with bounded release jitter and execution time variation) scheduled by a global job-level fixed-priority (JLFP) scheduling algorithm upon an identical multicore platform. The analysis yields a lower bound on the best-case response-time (BCRT) and an upper bound on the worst-case response time (WCRT) of the jobs. In an empirical evaluation with randomly generated workloads, we show that the method scales to 30 tasks, a hundred thousand jobs (per hyperperiod), and up to 9 cores

Using Imprecise Computing for Improved Real-Time Scheduling

Conventional hard real-time scheduling is often overly pessimistic due to the worst case execution time estimation. The pessimism can be mitigated by exploiting imprecise computing in applications where occasional small errors are acceptable. This leverage is investigated in a few previous works, which are restricted to preemptive cases. We study how to make use of imprecise computing in uniprocessor non-preemptive real-time scheduling, which is known to be more difficult than its preemptive counterpart. Several heuristic algorithms are developed for periodic tasks with independent or cumulative errors due to imprecision. Simulation results show that the proposed techniques can significantly improve task schedulability and achieve desired accuracy– schedulability tradeoff. The benefit of considering imprecise computing is further confirmed by a prototyping implementation in Linux system. Mixed-criticality system is a popular model for reducing pessimism in real-time scheduling while providing guarantee for critical tasks in presence of unexpected overrun. However, it is controversial due to some drawbacks. First, all low-criticality tasks are dropped in high-criticality mode, although they are still needed. Second, a single high-criticality job overrun leads to the pessimistic high-criticality mode for all high-criticality tasks and consequently resource utilization becomes inefficient. We attempt to tackle aforementioned two limitations of mixed-criticality system simultaneously in multiprocessor scheduling, while those two issues are mostly focused on uniprocessor scheduling in several recent works. We study how to achieve graceful degradation of low-criticality tasks by continuing their executions with imprecise computing or even precise computing if there is sufficient utilization slack. Schedulability conditions under this Variable-Precision Mixed-Criticality (VPMC) system model are investigated for partitioned scheduling and global fpEDF-VD scheduling. And a deferred switching protocol is introduced so that the chance of switching to high-criticality mode is significantly reduced. Moreover, we develop a precision optimization approach that maximizes precise computing of low-criticality tasks through 0-1 knapsack formulation. Experiments are performed through both software simulations and Linux proto- typing with consideration of overhead. Schedulability of the proposed methods is studied so that the Quality-of-Service for low-criticality tasks is improved with guarantee of satisfying all deadline constraints. The proposed precision optimization can largely reduce computing errors compared to constantly executing low-criticality tasks with imprecise computing in high-criticality mode

Response-Time Analysis of Limited-Preemptive Parallel DAG Tasks Under Global Scheduling

Most recurrent real-time applications can be modeled as a set of sequential code segments (or blocks) that must be (repeatedly) executed in a specific order. This paper provides a schedulability analysis for such systems modeled as a set of parallel DAG tasks executed under any limited-preemptive global job-level fixed priority scheduling policy. More precisely, we derive response-time bounds for a set of jobs subject to precedence constraints, release jitter, and execution-time uncertainty, which enables support for a wide variety of parallel, limited-preemptive execution models (e.g., periodic DAG tasks, transactional tasks, generalized multi-frame tasks, etc.). Our analysis explores the space of all possible schedules using a powerful new state abstraction and state-pruning technique. An empirical evaluation shows the analysis to identify between 10 to 90 percentage points more schedulable task sets than the state-of-the-art schedulability test for limited-preemptive sporadic DAG tasks. It scales to systems of up to 64 cores with 20 DAG tasks. Moreover, while our analysis is almost as accurate as the state-of-the-art exact schedulability test based on model checking (for sequential non-preemptive tasks), it is three orders of magnitude faster and hence capable of analyzing task sets with more than 60 tasks on 8 cores in a few seconds

A survey of techniques for reducing interference in real-time applications on multicore platforms

This survey reviews the scientific literature on techniques for reducing interference in real-time multicore systems, focusing on the approaches proposed between 2015 and 2020. It also presents proposals that use interference reduction techniques without considering the predictability issue. The survey highlights interference sources and categorizes proposals from the perspective of the shared resource. It covers techniques for reducing contentions in main memory, cache memory, a memory bus, and the integration of interference effects into schedulability analysis. Every section contains an overview of each proposal and an assessment of its advantages and disadvantages.This work was supported in part by the Comunidad de Madrid Government "Nuevas Técnicas de Desarrollo de Software de Tiempo Real Embarcado Para Plataformas. MPSoC de Próxima Generación" under Grant IND2019/TIC-17261

Sharing Non-Processor Resources in Multiprocessor Real-Time Systems

Computing devices are increasingly being leveraged in cyber-physical systems, in which computing devices sense, control, and interact with the physical world. Associated with many such real-world interactions are strict timing constraints, which if unsatisfied, can lead to catastrophic consequences. Modern examples of such timing constraints are prevalent in automotive systems, such as airbag controllers, anti-lock brakes, and new autonomous features. In all of these examples, a failure to correctly respond to an event in a timely fashion could lead to a crash, damage, injury and even loss of life. Systems with imperative timing constraints are called real-time systems, and are broadly the subject of this dissertation. Much previous work on real-time systems and scheduling theory assumes that computing tasks are independent, i.e., the only resource they share is the platform upon which they are executed. In practice, however, tasks share many resources, ranging from more overt resources such as shared memory objects, to less overt ones, including data buses and other hardware and I/O devices. Accesses to some such resources must be synchronized to ensure safety, i.e., logical correctness, while other resources may exhibit better run-time performance if accesses are explicitly synchronized. The goal of this dissertation was to develop new synchronization algorithms and associated analysis techniques that can be used to synchronize access to many classes of resources, while improving the overall resource utilization, specifically as measured by real-time schedulability. Towards that goal, the Real-Time Nested Locking Protocol (RNLP), the first multiprocessor real-time locking protocol that supports lock nesting or fine-grained locking is proposed and analyzed. Furthermore, the RNLP is extended to support reader/writer locking, as well as k-exclusion locking. All presented RNLP variants are proven optimal. Furthermore, experimental results demonstrate the schedulability-related benefits of the RNLP. Additionally, three new synchronization algorithms are presented, which are specifically motivated by the need to manage shared hardware resources to improve real-time predictability. Furthermore, two new classes of shared resources are defined, and the first synchronization algorithms for them are proposed. To analyze these new algorithms, a novel analysis technique called idleness analysis is presented, which can be used to incorporate the effects of blocking into schedulability analysis.Doctor of Philosoph

Real-Time Wireless Sensor-Actuator Networks for Cyber-Physical Systems

A cyber-physical system (CPS) employs tight integration of, and coordination between computational, networking, and physical elements. Wireless sensor-actuator networks provide a new communication technology for a broad range of CPS applications such as process control, smart manufacturing, and data center management. Sensing and control in these systems need to meet stringent real-time performance requirements on communication latency in challenging environments. There have been limited results on real-time scheduling theory for wireless sensor-actuator networks. Real-time transmission scheduling and analysis for wireless sensor-actuator networks requires new methodologies to deal with unique characteristics of wireless communication. Furthermore, the performance of a wireless control involves intricate interactions between real-time communication and control. This thesis research tackles these challenges and make a series of contributions to the theory and system for wireless CPS. (1) We establish a new real-time scheduling theory for wireless sensor-actuator networks. (2) We develop a scheduling-control co-design approach for holistic optimization of control performance in a wireless control system. (3) We design and implement a wireless sensor-actuator network for CPS in data center power management. (4) We expand our research to develop scheduling algorithms and analyses for real-time parallel computing to support computation-intensive CPS

Scheduling and locking in multiprocessor real-time operating systems

With the widespread adoption of multicore architectures, multiprocessors are now a standard deployment platform for (soft) real-time applications. This dissertation addresses two questions fundamental to the design of multicore-ready real-time operating systems: (1) Which scheduling policies offer the greatest flexibility in satisfying temporal constraints; and (2) which locking algorithms should be used to avoid unpredictable delays? With regard to Question 1, LITMUSRT, a real-time extension of the Linux kernel, is presented and its design is discussed in detail. Notably, LITMUSRT implements link-based scheduling, a novel approach to controlling blocking due to non-preemptive sections. Each implemented scheduler (22 configurations in total) is evaluated under consideration of overheads on a 24-core Intel Xeon platform. The experiments show that partitioned earliest-deadline first (EDF) scheduling is generally preferable in a hard real-time setting, whereas global and clustered EDF scheduling are effective in a soft real-time setting. With regard to Question 2, real-time locking protocols are required to ensure that the maximum delay due to priority inversion can be bounded a priori. Several spinlock- and semaphore-based multiprocessor real-time locking protocols for mutual exclusion (mutex), reader-writer (RW) exclusion, and k-exclusion are proposed and analyzed. A new category of RW locks suited to worst-case analysis, termed phase-fair locks, is proposed and three efficient phase-fair spinlock implementations are provided (one with few atomic operations, one with low space requirements, and one with constant RMR complexity). Maximum priority-inversion blocking is proposed as a natural complexity measure for semaphore protocols. It is shown that there are two classes of schedulability analysis, namely suspension-oblivious and suspension-aware analysis, that yield two different lower bounds on blocking. Five asymptotically optimal locking protocols are designed and analyzed: a family of mutex, RW, and k-exclusion protocols for global, partitioned, and clustered scheduling that are asymptotically optimal in the suspension-oblivious case, and a mutex protocol for partitioned scheduling that is asymptotically optimal in the suspension-aware case. A LITMUSRT-based empirical evaluation is presented that shows these protocols to be practical