Rate Monotonic Algorithm Research Articles

Contention-Free Scheduling for Single Preemption Multiprocessor Platforms

The Contention-Free (CF) policy has been extensively researched in the realm of real-time multi-processor scheduling due to its wide applicability and the performance enhancement benefits it provides to existing scheduling algorithms. The CF policy improves the feasibility of executing other real-time tasks by assigning the lowest priority to a task at a moment when it is guaranteed not to miss its deadline during the remaining execution time. Despite its effectiveness, existing studies on the CF policy are largely confined to preemptive scheduling, leaving the efficiency and applicability of limited preemption scheduling unexplored. Limited preemption scheduling permits a job to execute to completion with a limited number of preemptions, setting it apart from preemptive scheduling. This type of scheduling is crucial when preemption or migration overheads are either excessively large or unpredictable. In this paper, we introduce SP-CF, a single preemption scheduling approach that incorporates the CF policy. SP-CF allows a preemption only once during each job’s execution, following a priority demotion under the CF policy. We also propose a new schedulability analysis method for SP-CF to determine whether each task is executed in a timely manner and without missing its deadline. Through simulation experiments, we demonstrate that SP-CF can significantly enhance the schedulability of the traditional rate-monotonic algorithm and the earliest deadline first algorithm.

Determining rate monotonic schedulability of real-time periodic tasks using continued fractions

Fixed-priority scheduling algorithms are widely used for real-time systems with a single processor because of their implementation simplicity and relatively low run-time overheads. However, determining whether a task set is schedulable by a fixed-priority scheduling algorithm has been shown to be NP-hard. There are few exact schedulability test methods such as the time demand analysis or the worst-case response time analysis for Rate Monotonic scheduling, while much research has been done to find a tighter sufficient condition for the fixed-priority schedulability. In this paper, a new approach to analyze the schedulability of fixed-priority scheduling using well-known mathematical tool called continued fractions is presented. With continued fractions, a new schedulability test for Rate Monotonic algorithm is derived. The schedulability test condition is an exact condition that can be applied tasks with total utilization less than 1.

Analysis of thread schedulability in Huawei LiteOS

Huawei LiteOS is a real-time operating system. Thread schedulability is an important thing to be considered first when we use the RTOS in an application. There are a lot of methods to value thread schedulability in practical application. Rate monotonic scheduling algorithm is a widely used static priority scheduling algorithm. We discussed the thread schedulability in Huawei LiteOS.

An Energy and Performance Aware Scheduler for Real-Time Tasks in Cloud Datacentres

Datacentres provide the foundations for cloud computing, but require large amounts of electricity for their operation. Approaches that promise to reduce power use by minimizing execution time, for example using different scheduling and resource management techniques, are discussed in the literature. This paper summarizes some of the most important scheduling techniques in clouds focusing on power consumption, covering VM-level, host-level and task-level scheduling where the most promising approach is task level scheduling, with energy savings by means of load filtering, consolidation, adapted CPU throughput, or host power control. We explore use of the rate monotonic (RM) and backfilling algorithms for real-time task scheduling in cloud environment because RM is the simplest fixed priority scheduling technique, and thus the choice for modern real-time systems, and prior uses of RM in task scheduling have demonstrated power efficiency with optimal results. We specifically consider deadline-based tasks scheduling for real-time clouds which, to the best of our knowledge, has not been employed previously. RM with backfilling is experimentally evaluated and results show that, compared to the classical algorithms, all tasks were scheduled with minimum power consumption (5.5% - 29.3%), on minimum resources (3.9% - 25.2% less) while majority were meeting their deadlines (93.21% - 94.7%). The approach can guarantee deadline oriented Software as a Service (SaaS) in cloud if arrival rate i.e. network transfer time can be estimated in advance. We subsequently provided an extension of the proposed approach to task-based load balancing for almost balanced resource utilization and approximately 1.0% to 1.6% energy efficiency.

Improved schedulability analysis of the contention-free policy for real-time systems

Real-time scheduling is the primary research for designing real-time systems whose correctness is determined by not only logical correctness but also timely execution. Real-time scheduling involves two fundamental issues: scheduling algorithm design and schedulability analysis development, which aim at developing a prioritization policy for real-time tasks and offering their timing guarantees at design time, respectively. Among the numerous scheduling algorithms and schedulability analysis for a multiprocessor platform, the contention-free (CF) policy and response-time analysis (RTA) have received considerable attention owing to their wide applicability and high analytical performance, respectively. Notwithstanding their effectiveness, it has been conjectured that it is not feasible to exploit the two techniques together. In this study, we propose a new schedulability analysis for the CF policy, referred to as pseudo-response time analysis (PRTA), which exploits a new notion of pseudo-response time effectively capturing the time instant at which the schedulability of a task is guaranteed under the CF policy. To demonstrate the effectiveness of PRTA, we apply PRTA to the existing earliest deadline first and rate monotonic scheduling algorithms employing the CF policy, and show that up to 46.4% and 18.3% schedulability performance improvement can be achieved, respectively, compared to those applying the existing schedulability analysis.

Energy performance evaluation for dynamic frequency scaling on rate monotonic and earliest deadline first scheduling algorithm

Energy performance evaluation for dynamic frequency scaling on rate monotonic and earliest deadline first scheduling algorithm

Towards optimal solutions for the low power hard real-time task allocation on multiple heterogeneous processors

The usage of heterogeneous multicore platforms is appealing for applications, e.g. hard real-time systems, due to the potential reduced energy consumption offered by such platforms. However, even in such platforms the power wall phenomena still imposes limits to performance. Hard real-time systems are part of life critical environments and reducing the energy consumption on such systems is an onerous and complex process. We tackle the problem from the perspective of different representative integer programming mathematical formulations and their interplay on the search for optimal solutions for Rate Monotonic (RM) and Earliest Deadline First (EDF) scheduling algorithms. The proposed models are based on a well-established formulation in the operational research literature, namely, the Multilevel Generalized Assignment Problem (MGAP). This paper, therefore, assesses the problem of finding optimal allocations and frequency assignments of hard real-time tasks among heterogeneous processors targeting low power consumption, but taking into account timing constraints. Computational experiments show that finding optimal solutions reduces the estimated energy consumption of the evaluated cases when compared to state-of-the-art algorithms. • Representative theoretical models of several hard real-time scheduling policies. • New application of well-known classical combinatorial optimization problem: MGAP. • Applicability on embedded systems with low power and hard real-time requirements. • Optimal workload partitioning on heterogeneous processors in project time. • Computational experiments on finding optimal solutions for the proposed models.

Minimum energy consumption for rate monotonic scheduled tasks

Limited battery power is a typical constraint in stand-alone embedded systems. One way to extend the battery lifetime is by reducing CPU power consumption. Because of the quadratic relationship between power consumption in CMOS circuits and CPU voltage, power reduction can be obtained by scaling down supply voltage, or dynamic voltage scaling. However, reducing supply voltage slows down CPU speed since supply voltage has a proportional relationship with CPU frequency. On the other hand, in any real-time embedded environment (especially hard real-time), timing constraints are critical. In this paper, we focus on dynamic energy reduction of tasks scheduled by rate monotonic (RM) algorithm in a hard real-time embedded environment. The RM algorithm preemptively schedules any set of periodic tasks by assigning higher priorities to frequent tasks. For any periodic task set that satisfies the CPU utilization bound, we determine the provably optimal scaling of the worst-case execution time of each task that consumes minimum dynamic energy while satisfying the utilization bound. As RM algorithm is widely used, we expect this work can lead to better energy reduction management and expectations.

A Note on the EDF Preemption Behavior in “Rate Monotonic Versus EDF: Judgment Day”

In G. C. Buttazzo, Real-Time Syst., vol. 29, no. 1, pp. 5–26, 2005, the author empirically compared earliest deadline first (EDF) and rate monotonic (RM) scheduling algorithms and made a few EDF preemption behavior observations based on data obtained from the first 1000 time units of scheduling activities. However, based on test settings given in (G. C. Buttazzo, Real-Time Syst., vol. 29, no. 1, pp. 5–26, 2005), the first 1000 time units occupies only a small percentage of the entire task set’s hyper-period. We extend EDF preemption behavior study by extending scheduling activities from the first small percentage of a hyper-period of a given task to the entire hyper-period. The extended experiments indicate that the number of preemptions occurred at the beginning of a task set’s hyper-period does not necessarily represent the trend for the entire hyper-period. Hence, comparisons and conclusions made based on a small percentage of a scheduling interval over a task set’s hyper-period may not be accurate. Second, the total number of preemptions within a task set’s hyper-period does not decrease when the task set total utilization increases which is different from the observation obtained in (G. C. Buttazzo, Real-Time Syst., vol. 29, no. 1, pp. 5–26, 2005). We also investigate the impact of execution time differences among tasks on the preemption behavior.

Energy-efficient scheduling of real-time tasks with shared resources

This paper explores the energy-efficient scheduling of real-time tasks on a non-ideal DVS processor in the presence of resource sharing. We assume that tasks are periodic, preemptive and may access to shared resources. When dynamic-priority and fixed-priority scheduling are considered, we use the earliest deadline first (EDF) algorithm and the rate monotonic (RM) algorithm to schedule the given set of tasks. Based on the stack resource policy (SRP), we propose an approach, called blocking-aware two-speed (BATS) algorithm, to synchronize the tasks with shared resources and to calculate appropriate execution speeds so that the shared resources can be accessed in a mutual exclusive manner and the energy consumption can be reduced. Particularly, BATS uses a static low speed to execute tasks initially, and then it switches to a high speed dynamically whenever a task blocks a higher priority task. More specifically, the processor runs at the high speed from the beginning of the blocking until the deadline of the blocked task or the processor becomes idle. In order to guarantee that the deadlines of tasks are met, the static low speed and the dynamic high speeds are derived based on the theoretical analysis of the schedulability of tasks. Compared with existing work, BATS achieves more energy saving because its dynamic high speeds are lower than that of existing work and the processor has less chance to execute tasks at the high speeds. The schedulability analysis and the properties of our proposed BATS are provided in this paper. We also evaluated the capabilities of BATS by a series of experiments, for which we have some encouraging results.

Supporting fault-tolerance in a compositional real-time scheduling framework

Component-based analysis allows a robust time and space decomposition of a complex real-time system into components, which are then recomposed and hierarchically scheduled under potentially different scheduling policies. This mechanism is of great benefit to many critical systems as it enables fault isolation. To provide fault-tolerant scheduling in a compositional real-time scheduling framework, a few works have recently emerged, but remain inefficient in providing fault isolation or in terms of resource utilization. In this paper, we introduced a new interface model that takes into account the fault requirements of a component, and a fault-tolerant resource model that helps the component to effectively respond to each of its child components in presence of a fault. Finally, we analyzed the schedulability of the framework considering the Rate Monotonic scheduling algorithm.

A Review of Sufficient Schedulability Analysis for Fixed Priority Scheduling Systems

This papercarries out a survey of sufficient schedulability analysis forfixed priority (FP) scheduling. The most common used fixed priority assignment is the rate monotonic (RM) algorithm, according to its policy, the task priorities are ordered based on their activation rates, so that the task with the shortest period is assigned the highest priority. However, when each task’s relative deadline is not equal to its period, the RM algorithm is not suitable to assign the task priorities. When relative deadlines are less than or equal to periods,the deadline monotonic (DM) algorithm can be deployed to schedule the tasks. The utilization based schedulability analysis has the advantage of simple implementation, and manyexisting schedulability analyses on uniprocessor are covered.

Semi-partitioned scheduling for fixed-priority real-time tasks based on intelligent rate monotonic algorithm

In this paper, a new semi-partitioned scheduling algorithm on multiprocessor platforms, based on intelligent rate monotonic algorithm is proposed. Intelligent rate monotonic algorithm is an extended version of the famous rate monotonic algorithm. By splitting some tasks between processors, semi-partitioning is used to enhance overall utilisation. Each semi-partitioned approach has two phases, partitioning and scheduling. The main challenge of semi-partitioned scheduling algorithms is how to partition and split tasks by which they are safely scheduled under the identified scheduling policy, with high utilisation. The partitioning phase of our proposed approach called Semi-Partitioned Intelligent Rate Monotonic-First-Fit SIRM-FF includes three sub-phases. Task splitting is done only in the third sub-phase. In the second sub-phase, processors are selected by a first-fit method. The use of first-fit method makes SIRM-FF create a lower number of sub-tasks in comparison to previous works, hence the number of context switches of sub-tasks and overhead due to task splitting is reduced. The feasibility of tasks and sub-tasks which are partitioned by SIRM-FF is formally proved and overall utilisation is compared with competitors.

Power-aware scheduling of compositional real-time frameworks

The energy consumption problem has become a great challenge in all computing areas from modern handheld devices to large data centers. Dynamic voltage scaling (DVS) is widely used as mean to reduce the energy consumption of computer systems by lowering whenever possible the voltage and operating frequency of processors. Unfortunately, existing compositional real-time scheduling frameworks have been focusing only on efficient scheduling of tasks inside their components given a resource model, providing no interest on power/energy consumption. In this paper, we define the real-time DVS problem for a compositional scheduling framework. Considering the periodic resource model, we propose optimal static DVS schemes at system, component, and task levels. We also introduce component and task level dynamic DVS schemes that take advantage of runtime unused slack times and resource availability to provide even better energy savings. Finally, we provide power-aware schedulability conditions to guarantee the feasibility of each component under DVS for the Earliest Deadline First and the Rate Monotonic scheduling algorithms. Through simulations, we showed that our schemes can reduce the energy consumption of a component by up to 96%.

Energy-Efficient Real-Time Scheduling of Tasks with Abortable Critical Sections

In this paper, an energy-efficient scheduling algorithm, called ceiling-based conditional abortable scheduling (CB-CAS) algorithm, is proposed to schedule periodic hard real-time tasks in a non-ideal DVS processor. Based on the schedulability analysis, CB-CAS calculates a proper processor speed for task execution so that the energy consumption can be reduced without violating the timing constraints of tasks. For saving more energy, we also assume that the critical sections of tasks are abortable, which is a strategy originally proposed to reduce priority inversions. In this paper, CB-CAS introduces a conditional abort rule and a dynamic speed adjustment method to work with the rate monotonic scheduling algorithm and the priority ceiling protocol so that the energy consumption could be reduced further. Whenever two tasks are conflicting for the same resource, CB-CAS will examine the cost of blocking the higher-priority task and the cost of aborting the lower-priority task. CB-CAS will abort the lower-priority task and adjust the processor speed dynamically only if it is more energy efficient. The schedulability analysis and the properties of CB-CAS are given in this paper. The capabilities of CB-CAS were also evaluated by a series of experiments, for which we have some encouraging results.

An Efficient Test Method for Rate Monotonic Schedulability

Rate Monotonic scheduling algorithm has been widely used in real-time systems for its optimality in fixed priority scheduling. Determining the Rate Monotonic schedulability of tasks is an important problem when designing a real-time system. There are exact schedulability test methods for Rate Monotonic scheduling, but the worst case response time analysis on which the exact tests are based is NP-hard. So the exact tests are often too complex to be executed on-line for large numbers of tasks. For practical use, polynomial time sufficient conditions for the Rate Monotonic schedulability have been studied. However, existing polynomial time tests are often too pessimistic. In this paper, we propose a new polynomial time sufficient condition based on the response time analysis, which is less pessimistic than existing ones. Simulation results show that our test significantly outperforms the existing tests and has performance close to the exact test.

SS-DRM: Semi-Partitioned Scheduling Based on Delayed Rate Monotonic on Multiprocessor Platforms

Semi-partitioned scheduling is a new approach for allocating tasks on multiprocessor platforms. By splitting some tasks between processors, semi-partitioned scheduling is used to improve processor utilization. In this paper, a new semi-partitioned scheduling algorithm called SS-DRM is proposed for multiprocessor platforms. The scheduling policy used in SS-DRM is based on the delayed rate monotonic algorithm, which is a modified version of the rate monotonic algorithm that can achieve higher processor utilization. This algorithm can safely schedule any system composed of two tasks with total utilization less than or equal to that on a single processor. First, it is formally proven that any task which is feasible under the rate monotonic algorithm will be feasible under the delayed rate monotonic algorithm as well. Then, the existing allocation method is extended to the delayed rate monotonic algorithm. After that, two improvements are proposed to achieve more processor utilization with the SS-DRM algorithm than with the rate monotonic algorithm. According to the simulation results, SS-DRM improves the scheduling performance compared with previous work in terms of processor utilization, the number of required processors, and the number of created subtasks.

Power-aware fixed priority scheduling for sporadic tasks in hard real-time systems

In this paper, we consider the generalized power model in which the focus is the dynamic power and the static power, and we study the problem of the canonical sporadic task scheduling based on the rate-monotonic (RM) scheme. Moreover, we combine with the dynamic voltage scaling (DVS) and dynamic power management (DPM). We present a static low power sporadic tasks scheduling algorithm (SSTLPSA), assuming that each task presents its worst-case work-load to the processor at every instance. In addition, a more energy efficient approach called a dynamic low power sporadic tasks scheduling algorithm (DSTLPSA) is proposed, based on reclaiming the dynamic slack and adjusting the speed of other tasks on-the-fly in order to reduce energy consumption while still meeting the deadlines. The experimental results show that the SSTLPSA algorithm consumes 26.55–38.67% less energy than that of the RM algorithm and the DSTLPSA algorithm reduces the energy consumption up to 18.38–30.51% over the existing DVS algorithm.

An SRP-based energy-efficient scheduling algorithm for dependent real-time tasks

In this paper, we are interested in the energy-efficient scheduling of dependent real-time tasks which may access multiunit resources. Based on the well-known stack resource policy (SRP), we propose the blocking-time stealing (BTS) algorithm to schedule dynamic-priority and fixed-priority tasks on a non-ideal dynamic voltage scaling (DVS) processor. Under the BTS algorithm, tasks are scheduled to be executed at proper processor speeds which are determined according to the sufficient schedulability conditions of the earliest deadline first (EDF) and the rate monotonic (RM) algorithms. The BTS algorithm measures dynamically the slack between the actual blocking time of a task and its estimated worst-case blocking time. The slack is then exploited to lower the processor speed guaranteeing that the feasibility of tasks is not affected. As a result, the energy consumption can be reduced while satisfying the timing constraints of real-time tasks.

Utilization Bound Scheduling Analysis for Nonpreemptive Uniprocessor Architecture Using UML-RT

The key for adopting the utilization-based schedulability test is to derive the utilization bound. Given the computation times, this paper proposes two utilization bound algorithms to derive interrelease times for nonpreemptive periodic tasks, using a new priority scheme, “Rate Monotonic Algorithm-Shortest Job First.” The obtained task set possesses the advantage of Rate Monotonic Algorithm and Shortest Job First priority scheme. Further, the task set is tested for schedulability, by first deriving a general schedulability condition from “problem window” analysis and, a necessary and sufficient schedulability condition for a task to be scheduled, at any release time are also derived. As a technical contribution, success ratio and effective processor utilization are analyzed for our proposed utilization bound algorithms on a uniprocessor architecture modeled using UML-RT.