Rate Monotonic Scheduling Algorithm Research Articles

Solution] End-to-end Scheduling of Real-time Task Pipelines on Multiprocessors

Task pipelines are common in today’s embedded systems, as data moves from source to sink in sensing-processing-actuation task chains. A real-time task pipeline is constructed by connecting a series of periodic tasks with data buffers. In a time-critical system, end-to-end timing and data-transfer properties of a task pipeline must be guaranteed. A guarantee could be mathematically expressed by assigning constraints to the tasks of a pipeline. However, deriving task scheduling parameters to meet end-to-end guarantees is an NP-hard constraint optimization problem. Hence, a traditional constraint solver is not a suitable runtime solution.In this paper, we present a heuristic constraint solver algorithm, CoPi, to derive the execution times and periods of pipelined tasks that meet the end-to-end constraints and schedulability requirements. We consider two upper bound constraints on a task pipeline: end-to-end delay and loss-rate. After satisfying these constraints, CoPi schedules a pipeline as a set of asynchronous and data independent periodic tasks, under the rate-monotonic scheduling algorithm. Simulations show that CoPi has a comparable pipeline acceptance ratio and significantly better runtime than open-source MINLPsolvers. Furthermore, we use CoPi to map multiple task pipelines to a multiprocessor system. We demonstrate that a partitioned multiprocessor scheduling algorithm coupled with CoPi accommodates dynamically appearing pipelines, while attempting to minimize task migrations.

Fault Tolerance in the Joint EDF-RMS Algorithm: A Comparative Simulation Study

Failure is a systemic error that affects overall system performance and may eventually crash across the entire configuration. In Real-Time Systems (RTS), deadline is the key to successful completion of the program. If tasks effectively meet the deadline, it means the system is working in pristine order. However, missing the deadline means a systemic fault due to which the system can crash (hard RTS) or degrade inclusive performance (soft RTS). To fine-tune the RTS, tolerance is the critical issue and must be handled with extreme care. This article explains the context of fault tolerance with improvised Joint EDF-RMS algorithm in RTS. The backup method has been derived to prevent the system from being recursively migrating the same task. If any task migrates three times, this migrated task will get shifted to the backup queue. This backup queue assigns the task to a backup processor and is destined for final execution. For performance evaluation purposes, a relative graph between fault and failure rates, failure and total processor utilization along with other averages have been evaluated. Furthermore, these archived results are compared with fault-tolerant Earliest Deadline First (EDF) and Rate Monotonic Scheduling (RMS) algorithms independently in relatively similar conditions. These comparisons show better performance against overloading conditions.

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.

Energy-cognizant scheduling for preference-oriented fixed-priority real-time tasks

Abstract Energy management is one of the crucial design issues when executing real-time applications with stringent timing requirements. Dynamic slowdown of processor voltage if accompanied with processor shutdown method, helps in better saving energy. Traditionally, energy management has been applied to real-time scheduling algorithms that prioritize tasks based on timing parameters only, however, recently applications having tasks with different execution-preferences on the same computing unit found significant importance in various areas. In this paper, dynamic voltage scaling (DVS) and dynamic power management (DPM) techniques are used for energy management while scheduling preference-oriented fixed-priority periodic real-time tasks. Preference-oriented energy-aware rate-monotonic scheduling (PER) and preference-oriented extended energy-aware rate-monotonic scheduling (PEER) algorithms are proposed that maximize energy savings while fulfilling preference-value of tasks. Extensive simulations show that PER and PEER outperforms in terms of energy savings when compared to several related studies.

A novel evolutionary algorithm (MFO) with rate monotonic scheduling for load balancing in LTE advanced networks

In recent days, long term evolution (LTE)-advanced is the newest 4G technology. In this cellular network, the femto cells offered a viable and cost-effective method of enhancing the cellular reporting and capability for each WLAN and WiMAX. However, network allocates resource dissimilar to each and every users. To overcome this difficulty, moth flame optimisation (MFO) technique is used to provide equal resource allocation to user. Using this MFO method to balance the load for routing process. Rate-monotonic scheduling (RMS) algorithm is applied to share the load equally to available user, which increases the throughput and control the overload during communication time instance. The simulation results show that the proposed MFO technique has achieved improved network performance than existing hybrid multilevel feedback queue with round robin (HMFQ-RR) and hybrid weighted round robin with shortest job first (HWRR-SJF) in terms to reduce packet loss rate, packet delay and end to end delay.

A novel evolutionary algorithm (MFO) with rate monotonic scheduling for load balancing in LTE advanced networks

In recent days, long term evolution (LTE)-advanced is the newest 4G technology. In this cellular network, the femto cells offered a viable and cost-effective method of enhancing the cellular reporting and capability for each WLAN and WiMAX. However, network allocates resource dissimilar to each and every users. To overcome this difficulty, moth flame optimisation (MFO) technique is used to provide equal resource allocation to user. Using this MFO method to balance the load for routing process. Rate-monotonic scheduling (RMS) algorithm is applied to share the load equally to available user, which increases the throughput and control the overload during communication time instance. The simulation results show that the proposed MFO technique has achieved improved network performance than existing hybrid multilevel feedback queue with round robin (HMFQ-RR) and hybrid weighted round robin with shortest job first (HWRR-SJF) in terms to reduce packet loss rate, packet delay and end to end delay.

Static Schedule Generation for Time‐Triggered Ethernet Based on Fuzzy Particle Swarm Optimization

In time-triggered ethernet (TTEthernet), designing and optimizing the static scheduling of TT messages to improve the real-time performance of the whole network control system is important. When there is a high load on TTEthernet network communication, the conventional static scheduling policy introduces certain problems, such as increased packet loss rate, load imbalance, and transmission delay. Meanwhile, basic artificial intelligence algorithms generally features convergence within only a few steps, leading to higher probability to fall into a local optimal solution. To realize these targets, Fuzzy particle swarm optimization (FPSO) based on population diversity is established. By combining Particle swarm optimization (PSO) with a fuzzy algorithm, setting the adjustment of the inertia weight and the regulation of the mutation factor as the controlled variables of the Fuzzy logic controller (FLC), and adjusting the FLC inference rules, a novel static schedule generation for TTEthernet is proposed. Simulation results prove that, compared to the conventional rate-monotonic scheduling algorithm and the PSO algorithm, FPSO has a strong global search capability when the communication of the TTEthernet system is in a high-load state. FPSO improves the load balancing of the network and reduces the transmission delay of TT message packets. FPSO shows excellent ability to optimize scheduling tables and guarantee the real-time performance of the TTEthernet system.

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.

A Heuristic Task Periods Selection Algorithm for Real-Time Control Systems on a Multi-Core Processor

The performance optimization problem is investigated for discrete-time control systems on a multi-core platform. An integrated approach which considers both control performance and real-time scheduling aspects is applied to allocate optimal periods to controller tasks. A real-time control system is modeled as a set of directed acyclic graphs with weighted edges in this paper. The system allows producer/consumer relationship between tasks, and the data dependence relationships between tasks are uncoupled by attaching harmonic constraints to task periods. The period assignment problem is formulated as an optimization problem, which minimizes the system performance loss index under multi-core schedulability constraints. A heuristic search algorithm is proposed to solve this optimization problem and select periods for real-time tasks scheduled by rate-monotonic scheduling algorithm. Experimental results demonstrate that the proposed heuristic algorithm is capable of finding a high quality local optimal solution with fast computing speed. The proposed method is applicable to online failure recovery and reconfiguration in real-time control systems.

Preference-oriented fixed-priority scheduling for periodic real-time tasks

A preference priority assignment (PPA) scheme that explicitly incorporates the ASAP and ALAP execution preferences of periodic real-time tasks is proposed.An online dual-queue based preference-oriented fixed- priority (POFP) scheduler is proposed 4, which is preemptive and non-work-conserving in nature to better serve the tasks ASAP and ALAP execution preferences.Runtime techniques are also investigated to further delay (expedite) the executions of ALAP (ASAP) tasks by exploiting system slack at runtime.The proposed PPA scheme, POFP scheduler and runtime techniques are evaluated through extensive simulations with synthetic tasks, which are shown to be very effective to fulfill the tasks ASAP and ALAP execution requirements, when compared to that of the preference- oblivious RMS scheduler. Traditionally, real-time scheduling algorithms prioritize tasks solely based on their timing parameters and cannot effectively handle tasks that have different execution preferences. In this paper, for a set of periodic real-time tasks running on a single processor, where some tasks are preferably executed as soon as possible (ASAP) and others as late as possible (ALAP), we investigate Preference-Oriented Fixed-Priority (POFP) scheduling techniques. First, based on Audsley's Optimal Priority Assignment (OPA), we study a Preference Priority Assignment (PPA) scheme that attempts to assign ALAP (ASAP) tasks lower (higher) priorities, whenever possible. Then, by considering the non-work-conserving strategy, we exploit the promotion times of ALAP tasks and devise an online dual-queue based POFP scheduling algorithm. Basically, with the objective of fulfilling the execution preferences of all tasks, the POFP scheduler retains ALAP tasks in the delay queue until their promotion times while putting ASAP tasks into the ready queue right after their arrivals. In addition, to further expedite (delay) the executions of ASAP (ALAP) tasks using system slack, runtime techniques based on dummy and wrapper tasks are investigated. The proposed schemes are evaluated through extensive simulations. The results show that, compared to the classical fixed-priority Rate Monotonic Scheduling (RMS) algorithm, the proposed priority assignment scheme and POFP scheduler can achieve significant improvement in terms of fulfilling the execution preferences of both ASAP and ALAP tasks, which can be further enhanced at runtime with the wrapper-task based slack management technique.

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.

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.

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.

Comprehensive Comparison of Schedulability Tests for Uniprocessor Rate-Monotonic Scheduling

Schedulability conditions are used in real-time systems to verify the fulfillment of the temporal constraints of task sets. In this paper, a performance analysis is conducted for the best-known real-time schedulability conditions that can be used in online admission control on uni-processor systems executing under the Rate-Monotonic scheduling policy. Since Liu and Layland introduced the Rate-Monotonic scheduling algorithm, many research studies have been conducted on the schedulability analysis of real-time periodic task sets. However, in most cases, the performance of the proposed schedulability conditions were compared only against the Liu and Layland test and not against the remaining schedulability tests. The goal of this paper is to provide guidelines for system designers in order to decide which schedulability condition provides better performance under different task characteristics. Extensive simulation experiments were conducted to evaluate the inexact schedulability conditions and compare their performance and computational complexity.

Schedulability Test for Multiprocessor Scheduling Based on Hyperbolic Bound

The utilization bound for multiprocessor systems using the rate-monotonic scheduling algorithm and first fit allocation policy proposed by Lopez, et al. offers the best performance among all O(m) complexity schedulability tests. In this paper, a utilization bound is derived for the same target problem. The main difference between these two bounds lies in the technique to verify the schedulability of task sets on uniprocessors; the schedulability test here is performed based on the hyperbolic bound proposed by Bini, et al. The new bound surpasses the existing one under quite a lot parameter settings, and the combination of these two schedulability test methods, which are compatible with each other, can significantly improve the number of schedulable task sets with little extra overhead.

Model Checking Rate Monotonic Scheduling Algorithm Based on Propositional Projection Temporal Logic

A propositional projection temporal logic(PPTL) based model checking approach for rate monotonic scheduling(RMS) is presented.With this approach,RMS controlled systems are modeled by PROMELA,which is the system modeling language in model checker SPIN.The desired property is specified by a PPTL formula.Next,whether or not the system satisfies the property can be verified with SPIN.Accordingly,the schedulability of a group of tasks can be obtained;meanwhile,other properties of the tasks scheduling system under RMS algorithm can also be verified.

Schedulability analysis of global rate-monotonic scheduling algorithms on multiprocessor platforms

In the Rate-Monotonic (RM) global scheduling for multi-processor system,when the highest-priority task is fewer than the number of processors,the worst-case calculation interference given by Bertogna is too pessimistic.The authors proved that the interference of the task with highest priority on a task was not so pessimistic.But the interference of the task without highest priority on a task may be as pessimistic as the worst case presented by Bertogna,et al.The possible maximum interference of the tasks with highest priority was given by analysis,and then a tighter schedulability policy was put forward.The experimental results show that the proposed schedulability policy increases the amount of detected task set.

Hardware-Aware Rate Monotonic Scheduling Algorithm for Embedded Multimedia Systems

Many embedded multimedia systems employ special hardware blocks to co-process with the main processor. Even though an efficient handling of such hardware blocks is critical on the overall performance of real-time multimedia systems, traditional real-time scheduling techniques cannot afford to guarantee a high quality of multimedia playbacks with neither delay nor jerking. This paper presents a hardware-aware rate monotonic scheduling (HA-RMS) algorithm to manage hardware tasks efficiently and handle special hardware blocks in the embedded multimedia system. The HA-RMS prioritizes the hardware tasks over software tasks not only to increase the hardware utilization of the system but also to reduce the output jitter of multimedia applications, which results in reducing the overall response time.