Harmonic Scheduling and Control Co-Design

Harmonic task scheduling has many attractive properties, including a utilization bound of 100% under rate-monotonic scheduling and reduced jitter. At the same time, it places a severe constraint on the task period assignment for any application. In this paper, we explore the use of harmonic task scheduling for applications with multiple feedback control tasks. We present an algorithm for finding harmonic task periods that minimizes the distance from an initial set of non-harmonic periods. We apply the algorithm in a scheduling and control co-design procedure, where the goal is to optimize the total performance of a number of control tasks that share a common computing platform. The procedure is evaluated in simulated randomized examples, where it is shown that, in general, harmonic scheduling combined with release offsets gives better control performance than standard, non-harmonic scheduling

Schedulability, Response Time Analysis and New Models of P-FRP Systems

Functional Reactive Programming (FRP) is a declarative approach for modeling and building reactive systems. FRP has been shown to be an expressive formalism for building applications of computer graphics, computer vision, robotics, etc. Priority-based FRP (P-FRP) is a formalism that allows preemption of executing programs and guarantees real-time response. Since functional programs cannot maintain state and mutable data, changes made by programs that are preempted have to be rolled back. Hence in P-FRP, a higher priority task can preempt the execution of a lower priority task, but the preempted lower priority task will have to restart after the higher priority task has completed execution. This execution paradigm is called Abort-and-Restart (AR). Current real-time research is focused on preemptive of non-preemptive models of execution and several state-of-the-art methods have been developed to analyze the real-time guarantees of these models. Unfortunately, due to its transactional nature where preempted tasks are aborted and have to restart, the execution semantics of P-FRP does not fit into the standard definitions of preemptive or non-preemptive execution, and the research on the standard preemptive and non-preemptive may not applicable for the P-FRP AR model. Out of many research areas that P-FRP may demands, we focus on task scheduling which includes task and system modeling, priority assignment, schedulability analysis, response time analysis, improved P-FRP AR models, algorithms and corresponding software. In this work, we review existing results on P-FRP task scheduling and then present our research contributions: (1) a tighter feasibility test interval regarding the task release offsets as well as a linked list based algorithm and implementation for scheduling simulation; (2) P-FRP with software transactional memory-lazy conflict detection (STM-LCD); (3) a non-work-conserving scheduling model called Deferred Start; (4) a multi-mode P-FRP task model; (5) SimSo-PFRP, the P-FRP extension of SimSo - a SimPy-based, highly extensible and user friendly task generator and task scheduling simulator.Computer Science, Department o

Flexible Scheduling in Middleware for Distributed rate-based real-time applications - Doctoral Dissertation, May 2002

Distributed rate-based real-time systems, such as process control and avionics mission computing systems, have traditionally been scheduled statically. Static scheduling provides assurance of schedulability prior to run-time overhead. However, static scheduling is brittle in the face of unanticipated overload, and treats invocation-to-invocation variations in resource requirements inflexibly. As a consequence, processing resources are often under-utilized in the average case, and the resulting systems are hard to adapt to meet new real-time processing requirements. Dynamic scheduling offers relief from the limitations of static scheduling. However, dynamic scheduling offers relief from the limitations of static scheduling. However, dynamic scheduling often has a high run-time cost because certain decisions are enforced on-line. Furthermore, under conditions of overload tasks can be scheduled dynamically that may never be dispatched, or that upon dispatch would miss their deadlines. We review the implications of these factors on rate-based distributed systems, and posits the necessity to combine static and dynamic approaches to exploit the strengths and compensate for the weakness of either approach in isolation. We present a general hybrid approach to real-time scheduling and dispatching in middleware, that can employ both static and dynamic components. This approach provides (1) feasibility assurance for the most critical tasks, (2) the ability to extend this assurance incrementally to operations in successively lower criticality equivalence classes, (3) the ability to trade off bounds on feasible utilization and dispatching over-head in cases where, for example, execution jitter is a factor or rates are not harmonically related, and (4) overall flexibility to make more optimal use of scarce computing resources and to enforce a wider range of application-specified execution requirements. This approach also meets additional constraints of an increasingly important class of rate-based systems, those with requirements for robust management of real-time performance in the face of rapidly and widely changing operating conditions. To support these requirements, we present a middleware framework that implements the hybrid scheduling and dispatching approach described above, and also provides support for (1) adaptive re-scheduling of operations at run-time and (2) reflective alternation among several scheduling strategies to improve real-time performance in the face of changing operating conditions. Adaptive re-scheduling must be performed whenever operating conditions exceed the ability of the scheduling and dispatching infrastructure to meet the critical real-time requirements of the system under the currently specified rates and execution times of operations. Adaptive re-scheduling relies on the ability to change the rates of execution of at least some operations, and may occur under the control of a higher-level middleware resource manager. Different rates of execution may be specified under different operating conditions, and the number of such possible combinations may be arbitrarily large. Furthermore, adaptive rescheduling may in turn require notification of rate-sensitive application components. It is therefore desirable to handle variations in operating conditions entirely within the scheduling and dispatching infrastructure when possible. A rate-based distributed real-time application, or a higher-level resource manager, could thus fall back on adaptive re-scheduling only when it cannot achieve acceptable real-time performance through self-adaptation. Reflective alternation among scheduling heuristics offers a way to tune real-time performance internally, and we offer foundational support for this approach. In particular, run-time observable information such as that provided by our metrics-feedback framework makes it possible to detect that a given current scheduling heuristic is underperforming the level of service another could provide. Furthermore we present empirical results for our framework in a realistic avionics mission computing environment. This forms the basis for guided adaption. This dissertation makes five contributions in support of flexible and adaptive scheduling and dispatching in middleware. First, we provide a middle scheduling framework that supports arbitrary and fine-grained composition of static/dynamic scheduling, to assure critical timeliness constraints while improving noncritical performance under a range of conditions. Second, we provide a flexible dispatching infrastructure framework composed of fine-grained primitives, and describe how appropriate configurations can be generated automatically based on the output of the scheduling framework. Third, we describe algorithms to reduce the overhead and duration of adaptive rescheduling, based on sorting for rate selection and priority assignment. Fourth, we provide timely and efficient performance information through an optimized metrics-feedback framework, to support higher-level reflection and adaptation decisions. Fifth, we present the results of empirical studies to quantify and evaluate the performance of alternative canonical scheduling heuristics, across a range of load and load jitter conditions. These studies were conducted within an avionics mission computing applications framework running on realistic middleware and embedded hardware. The results obtained from these studies (1) demonstrate the potential benefits of reflective alternation among distinct scheduling heuristics at run-time, and (2) suggest performance factors of interest for future work on adaptive control policies and mechanisms using this framework

Measurements, Models, Systems and Design

531 s.

실시간 멀티코어 플루이드 스케줄링에서 전체 시스템의 시간 · 밀도 트레이드오프

학위논문 (박사)-- 서울대학교 대학원 공과대학 전기·컴퓨터공학부, 2017. 8. 이창건.Recent parallel programming frameworks such as OpenCL and OpenMP allow us to enjoy the parallelization freedom for real-time tasks. The parallelization freedom creates the time vs. density tradeoff problem in fluid scheduling, i.e., more parallelization reduces thread execution times but increases the density. By system-widely exercising this tradeoff, this dissertation proposes a parameter tuning of real-time tasks aiming at maximizing the schedulability of multicore fluid scheduling. The experimental study by both simulation and actual implementation shows that the proposed approach well balances the time and the density, and results in up to 80% improvement of the schedulability.1 Introduction 1 1.1 Motivation and Objective 1 1.2 Approach 3 1.3 Organization 4 2 Related Work 6 2.1 Real-Time Scheduling 6 2.1.1 Workload Model 6 2.1.2 Scheduling on Multicore Systems 7 2.1.3 Period Control 9 2.1.4 Real-Time Operating System 10 2.2 Parallel Computing 10 2.2.1 Parallel Computing Framework 10 2.2.2 Shared Resource Management 12 3 System-wide Time vs. Density Tradeoff with Parallelizable Periodic Single Segment Tasks 14 3.1 Introduction 14 3.2 Problem Description 14 3.3 Motivating Example 21 3.4 Proposed Approach 26 3.4.1 Per-task Optimal Tradeoff of Time and Density 26 3.4.2 Peak Density Minimization for a Task Group with the Same Period 27 3.4.3 Heuristic Algorithm for System-wide Time vs. Density Tradeoff 38 3.5 Experimental Results 45 3.5.1 Simulation Study 45 3.5.2 Actual Implementation Results 51 4 System-wide Time vs. Density Tradeoff with Parallelizable Periodic Multi-segment Tasks 64 4.1 Introduction 64 4.2 Problem Description 64 4.3 Extension to Parallelizable Periodic Multi-segment Task Model 70 4.3.1 Peak Density Minimization for a Task Group of Multi-segment Tasks with Same Period 71 4.3.2 Heuristic Algorithm for System-wide Time vs. Density Tradeoff 78 5 Conclusion 81 5.1 Summary 81 5.2 Future Work 82 References 84 Appendices 100 A Period Harmonization 100Docto

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

A Real-time Calculus Approach for Integrating Sporadic Events in Time-triggered Systems

In time-triggered systems, where the schedule table is predefined and statically configured at design time, sporadic event-triggered (ET) tasks can only be handled within specially dedicated slots or when time-triggered (TT) tasks finish their execution early. We introduce a new paradigm for synthesizing TT schedules that guarantee the correct temporal behavior of TT tasks and the schedulability of sporadic ET tasks with arbitrary deadlines. The approach first expresses a constraint for the TT task schedule in the form of a maximal affine envelope that guarantees that as long as the schedule generation respects this envelope, all sporadic ET tasks meet their deadline. The second step consists of modeling this envelope as a burst limiting constraint and building the TT schedule via simulating a modified Least-Laxity-First (LLF) scheduler. Using this novel technique, we show that we achieve equal or better schedulability and a faster schedule generation for most use-cases compared to other approaches inspired by, e.g., hierarchical scheduling. Moreover, we present an extension to our method that finds the most favourable schedule for TT tasks with respect to ET schedulability, thus increasing the probability of the computed TT schedule remaining feasible when ET tasks are later added or changed