Minimizing cache usage with fixed-priority and earliest deadline first scheduling

A real-time system is overloaded when all the tasks in a workload cannot meet their deadlines, and hence a robust algorithm is essential to maximize the number of tasks that meet their deadlines with the minimum number of miss rates and context switching. Although the Rate Monotonic (RM), Earliest Deadline First (EDF), and Least Laxity First (LLF) algorithms optimally perform and schedule tasks on a non-overloaded system, they have deficient performance when the system is overloaded. Therefore, we propose a new scheduling algorithm for uniprocessor and partitioned multiprocessor systems to address the overload situation. Since the proposed scheduling algorithm operates like EDF non-overloaded conditions, the proposed algorithm is optimal for non-overloaded systems. In addition, the proposed algorithm is robust against overloading situations as it executes the maximum possible tasks in the overload situation instead of missing deadlines of many tasks or burdening context switching to the system. The proposed algorithm allocates a processor to tasks based on the possibility of executing the task. The experimental results demonstrate that the proposed scheduling algorithm maximizes the number of tasks that meet their deadlines in overload conditions without a domino effect and context switching. In addition, the proposed algorithm achieves the lowest miss rate without context switching and the highest efficiency and processor utilization in the overloaded system compared with RM, EDF, and LLF.

Since 1973, Earliest Deadline First (EDF) uniprocessor scheduling has been known to be superior to its Rate Monotonic (Fixed-Priority, FPS) counterpart. Such superiority manifested in optimality, the capacity of EDF to feasibly sustain full utilization, which FPS can only achieve in certain favorable circumstances. In 2005, further research results argued that EDF's superiority would also extend to finer-grained performance indicators, such as preemption count, release and response-time jitter, resilience to transient overload. Recent work allowed EDF uniprocessor scheduling to be used in place of default FPS in Ada Ravenscar systems with unchanged application code: this development provides an interesting and practical avenue for empirical EDF-to-RM performance comparisons in an especially lean and efficient embedded setting. We leveraged that opportunity to develop a toolbox that enables quantitative comparison of EDF-to-RM uniprocessor scheduling with lightweight run-time tracing and offline analytic. In this work we present that toolbox and illustrate results we obtained with it, which shed new light on the presumed superiority of EDF to RM.

One of the core functions of an operating system is scheduling applications such that overall system provides a satisfactory result. Real-time embedded systems have an additional requisite to provide correct output within deadline; failure could be catastrophic for safety critical systems. In this paper, the feasibility of Primary-Backup Fault Tolerant Scheduling (PB-FTS) to handle application level faults by means of switching between primary and secondary copy of task is examined. PB-FTS, which is the secondary scheduler, is evaluated over the different traditional scheduling algorithms such as Rate Monotonic (RM), Deadline Monotonic (DM) and Earliest Deadline First (EDF) under various fault scenarios. The fault handling capacity and performance of PB-FTS is measured by running MATLAB based simulations. Simulation results indicate a decreasing trend in fault handling capacity from 100% at 0.6 utilization factor for one fault to 53% at 1.0 utilization factor for three faults.

Many of multimedia applications in distributed systems should transmit continuous audio/video across networks when clients request. Typically, messages for continuous media in packet-switched networks are split into periodic, different sized packets with deadlines. Since clients request different types services, traffic streams are heterogeneous. Furthermore, since the continuity of continuous media should be preserved, non-preemptive scheduling is preferred in multimedia communications. In this paper, we present a new non-preemptive scheduling algorithm which guarantees the timely delivery of more sets of messages for continuous media on a communication link connected to packet-switched networks. It schedules messages by using a heuristic based on the earliest deadline first (EDF) policy. It can always find a feasible schedule for messages which are schedulable by the EDF algorithm. We also present admission control given as sufficient conditions for a set of messages to be schedulable by our scheduling algorithm for controlling the traffic load on a link. If a new request and the previous messages satisfy these conditions, it accepts the new request. The accepted message transmission is done like the circuit-switched transmission non-preemptively. Finally, we show the improvements in performance of our scheduling algorithm by simulation results.

Internet of Things (IoT) based healthcare applications are time‐sensitive and any delay can cause alarming situations, including death of patients. The Earliest Deadline First (EDF) scheduling scheme has been proposed for use in IoT‐based healthcare applications. However, the EDF scheme performs poorly under overloaded conditions due to giving highest priority to packets that are close to missing their deadlines. Some studies have proposed the use of Priority EDF to overcome the challenges of EDF; however, Priority EDF still favours higher priority queues which increases the waiting times of lower priority queues. In order to overcome the limitation of EDF and its variants, this paper proposes a system model for a prioritized scheduling (PS) scheme. The PS scheme is an improvement of the Earliest Deadline First (EDF) scheme and its variants for IoT‐based healthcare applications. The PS scheme uses a heterogeneous multi‐server priority queuing system to provide service differentiation by prioritizing short packets over large packets and delay sensitive packets are serviced before delay tolerant packets. Numerical results demonstrate that the PS scheme minimizes the mean slowdown for both delay sensitive short and large packets at low and high load values. Additionally, the PS scheme performs better than the EDF and Priority EDF schemes in terms of reducing mean slowdown of packets and the PS scheme performs better than the EDF in terms of throughput for all packet sizes at both low and high load values. The performance improvement in terms of throughput is more pronounced at high load values. This addresses the challenge of the EDF scheme which performs poorly under overloaded conditions and the challenge of the Priority EDF scheme which favours higher priority queues at the expense of low priority queues.

In this paper we show how to extend classical real time feasibility conditions to take into account kernel overheads for mixed preemptive and non- preemptive periodic tasks with Earliest Deadline First (EDF) scheduling policy. The EDF algorithm allows us to schedule some tasks sets which are not valid with FP/FIFO scheduling policy, the classical scheduling implemented for OSEK. That is why we have improved our OSEK by implementing EDF algorithm. First of all, we identify the sources of overheads that influence the response time of the tasks: the context switching, the mechanisms used to activates/terminates and reschedules tasks, and the granularity of the periodic timer used to implement the periodic task model. We then show how to take into account those overheads in the classical EDF feasibility conditions. We compare the response times computed with theoretical feasibility conditions with kernel overhead to the results obtained on a real implementation. We show that the kernel overheads cannot be neglected and that our theoretical results are valid and can be used for a real-time dimensioning of an OSEK system with EDF scheduling policy. Finally, we compare the performances of our EDF implementation to the FP/FIFO native scheduling showing the benefits of implementing EDF in OSEK.

Our primary goal is to develop a compositional real-time scheduling framework where global (system-level) timing properties are established by composing together independently (specified and) analyzed local (component-level) timing properties. In this paper, we define two problems and one design issue in developing such a framework and present our approaches to the problems and the design issue. The two problems are (1) the scheduling interface derivation problem that is to (exactly) abstract the collective real-time requirements of a component as a single real-time requirement, or a scheduling interface and (2) the scheduling interface composition problem that is to (exactly) compose the scheduling interfaces of components into the system-level scheduling interface. The design issue is how to define a scheduling interface model. Our approach is to use the standard periodic model as the scheduling interface model and to address the two problems with the periodic model. We introduce exact conditions under which our proposed periodic scheduling interface model can abstract the collective real-time requirements that a set of periodic tasks demands under EDF (earliest deadline first) and RM (rate monotonic) scheduling. We present simulation results to evaluate the overheads that the periodic scheduling interfaces incur in terms of utilization increase.KeywordsSchedule AlgorithmSchedulability AnalysisSchedule FrameworkSchedule ComponentRate MonotonicThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

The ability of the system to complete the task within the stipulated deadline is an important parameter for real time systems. The relative deadlines for the processes may vary under different process load which is analysed in this paper using two widely used scheduling algorithms, Earliest Deadline First (EDF) and Rate Monotonic (RM). Also, different load conditions are considered which are classified as minimum, medium and maximum load in a system. The performance of the system under different load is graphically represented considering wide range of processes.

For preemptive scheduling with shared cache, different tasks may cause interference in the shared cache, leading to Cache-Related Preemption Overhead (CRPD). Cache partitioning is a well-known technique for mitigating unpredictable cache interference in preemptive scheduling, but it reduces cache space available to each task, causing an increase in task execution time. Non-preemptive scheduling algorithms do not incur CRPD, but they generally have poor schedulability. Preemption Threshold Scheduling (PTS) is an effective approach to strike a balance between preemptive and non-preemptive scheduling. We propose integration of cache partitioning and PTS to optimize schedulability on a uniprocessor. We force each subset of tasks assigned the same cache partition to be a non-preemptive group, by assigning the same PT to all tasks in the subset that is equal to or higher than the highest priority of the tasks in that subset. This eliminates CRPD within each cache partition, and helps to improve schedulability. We present an ILP formulation as well as an efficient heuristic algorithm.

Multiprocessor hardware platforms are now being considered for embedded systems, due to their high computational power and little additional cost when compared to single processor systems. When scheduling real-time applications on multiprocessor platforms, a possibility is to use global scheduling, where a scheduling algorithm dynamically assign tasks to processors, and tasks can migrate from one processor to another during their execution. In this paper, we tackle the problem of schedulability analysis of sporadic tasks in global scheduling systems, where the scheduler is the earliest deadline first (EDF) algorithm. We provide two main contributions. First, we show that two recently proposed tests perform poorly when the task set contains heavy tasks (i.e. tasks with high utilization). We also show that neither test dominates the other. As a second contribution, we introduce a new schedulability test that improves significantly the percentage of accepted task sets, especially when considering task sets containing heavy tasks. We show the effectiveness of the proposed test through an extensive set of experiments.

Deriving deadlines and periods for update transactions so as to maintain timeliness and data freshness while minimizing imposed workload has long been recognized an important problem in real-time database research. Despite years of active research, the state-of-the-art still has much room for improvement, particularly for periodic transactions scheduled by the Earliest Deadline First (EDF) algorithm. In this paper, we propose a practical and efficient two-phase algorithm, GEneral EDF (GE <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">EDF</sub> ), for assigning periods and deadlines to EDF-scheduled update transactions. Phase 1 of GE <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">EDF</sub> aims at finding solutions for most inputs in linear time, based on the observation that the execution times of update transactions are relatively small compared to the validity interval lengths of real-time data objects in many real-time applications. In the remaining cases for which Phase 1 fails to derive solutions, Phase 2 is invoked by employing an existing deadline-monotonic-based algorithm, which we show is also applicable to our problem. Meanwhile, we have devised several techniques which significantly reduce the cost of schedulability test, and hence greatly improve time efficiency. Our experimental results demonstrate that GE <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">EDF</sub> outperforms existing approaches in terms of generated workloads. Although Phase 2 has a pseudopolynomial time complexity, our experimental study shows that it runs much faster than other solutions with comparable quality.

Considering the execution order restriction of control tasks and message tasks in asynchronous networked control system (NCS), this paper proposes a hybrid scheduling scheme based on earliest deadline first (EDF) algorithm and genetic algorithm (GA). GA is used to allocate control tasks on multiprocessors in order to achieve load balance. For the purpose of meeting message deadlines and maximizing network utilization, non-preemptive EDF is used for the transmission of messages on networks. Finally, a tasks and messages scheduling paradigm is constructed within a least common multiple (LCM) which contains information about execution time and resource allocation of messages and tasks. Simulation results show that execution order restriction and timing constraints can be satisfied and a considerable high resource utilization rate can be achieved through our scheduling scheme.

EDF (Earliest Deadline First) has been proved to be optimal scheduling algorithm for single processor real-time system. It also performs well for multiprocessor system. Limitation of EDF is that its performance decreases exponentially when system becomes slightly overloaded. ACO (Ant Colony Optimization) based scheduling algorithm performs well in both underloaded and overloaded conditions. But its limitation is that it takes more time for execution compared to EDF. In this paper, an adaptive algorithm for multiprocessor real-time system is proposed, which is combination of both of these algorithms. The proposed algorithm along with EDF and ACO based algorithm is simulated for real-time multiprocessor system and the results are obtained. The performance is measured in terms of Success Ratio (SR) and Effective CPU Utilization (ECU). Execution Time taken by each scheduling algorithm is also measured. From analysis and experiments, it reveals that the proposed algorithm is fast as well as efficient in both underloaded and overloaded conditions for real-time multiprocessor systems.

In order to analyze and evaluate real-time performance of CAN network, the OPNET models of CAN network with Fixed Priority Scheduling (FPS) and Earliest Deadline First (EDF) have been set up in this paper. Based on simulation experiments, the performances of average delay and transmission success ratio in the two models are analyzed and the experiments also indicate that under normal load condition the two scheduling algorithm both can send data frame successfully before the deadline. In a slight overload condition FPS algorithm makes the transmission delay of low priority data frame significantly increased, and even occurs the phenomenon that low priority data frame can not be sent at all times; while the EDF algorithm can make all the nodes to complete the data frames in less than 3ms transmission delay, it meets the delay requirements that are delay should less than 10ms in most control systems, it indicates that EDF algorithm has the better scheduling and availability in soft real-time system.

Many algorithms have recently been studied for scheduling mixed-criticality (MC) tasks. However, most existing MC scheduling algorithms guarantee the timely executions of high-criticality (HC) tasks at the expense of discarding low-criticality (LC) tasks, which can cause serious service interruption for such tasks. In this work, aiming at providing guaranteed services for LC tasks, we study an elastic mixed-criticality (E-MC) task model for dual-criticality systems. Specifically, the model allows each LC task to specify its maximum period (i.e., minimum service level) and a set of early-release points. We propose an early-release (ER) mechanism that enables LC tasks to be released more frequently and thus improve their service levels at runtime, with both conservative and aggressive approaches to exploiting system slack being considered, which is applied to both earliest deadline first (EDF) and preference-oriented earliest-deadline schedulers. We formally prove the correctness of the proposed early-release--earliest deadline first scheduler on guaranteeing the timeliness of all tasks through judicious management of the early releases of LC tasks. The proposed model and schedulers are evaluated through extensive simulations. The results show that by moderately relaxing the service requirements of LC tasks in MC task sets (i.e., by having LC tasks’ maximum periods in the E-MC model be two to three times their desired MC periods), most transformed E-MC task sets can be successfully scheduled without sacrificing the timeliness of HC tasks. Moreover, with the proposed ER mechanism, the runtime performance of tasks (e.g., execution frequencies of LC tasks, response times, and jitters of HC tasks) can be significantly improved under the ER schedulers when compared to that of the state-of-the-art earliest deadline first—virtual deadline scheduler.