Workload-Efficient Deadline and Period Assignment for Maintaining Temporal Consistency under EDF

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.

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.

The conventional model of real-time system cannot solve a problem when tasks come earlier than their earliest response time. Fazmah Arif Yulianto solved this problem by purposing a different model which has liveline as new time constraint. This new algorithm is called Earliest Deadline Earliest Liveline First-Fazmah (EDELF-F) which is developed based on EDF-DM algorithm. Then to determine the ability of the algorithm, the comparison between EDELF-F with conventional algorithms EDF (Earliest Deadline First) was performed with 3 scenarios: period > deadline, period = deadline and period < deadline for 10 tasks. After simulated, EDELF-F algorithm has a weakness in order to satisfy task's period. Author has modified EDELF algorithm (called EDELF-S) which is developed based on EDF-C algorithm to overcome weakness of EDELF-F algorithm. This EDELF-S has better response time and feasibility and also can solve the problem related to earliest response time. Both EDELF-F and EDELF-S can solve every case which can be solved by EDF but not vice versa. Both EDELF-F and EDELF-S also has a better feasibility than EDF.

The EDF (Earliest Deadline First) scheduling policy can take advantage of the existence of a synchronization clock mechanism to reach higher utilizations in distributed real-time systems, as indicated by theoretical research. In this work, we give the first steps to enable the usage of EDF and a global clock in a distributed system. To this end, our proposal relies on Linux to provide the global clock and on a Real-Time Operating System (RTOS) to provide the global EDF policy. The objective is the evaluation of global EDF to verify to what extent the theoretical results are met.

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.

Tasks of an embedded system application are managed by a real-time operating system (RTOS). Most RTOSs adopt just fixed priority scheduling, which is not optimal in all cases. Some applications require earliest deadline first (EDF) scheduling, which is an optimal scheduling algorithm. In order to develop an efficient real-time embedded system, the scheduling algorithm of a RTOS should be selectable. The paper presents a method to customize the scheduling algorithm and the resource access protocol of an OSEK OS using aspect-oriented programming. We define aspects to replace the fixed priority scheduling mechanism of the OSEK OS with an EDF scheduling mechanism. We also define aspects to replace the resource access protocol of the OSEK OS with the resource access protocol for EDF scheduling. By using the aspects, we can customize the scheduling algorithm and the resource access protocol without modifying the original source code. This improves the maintainability of the source code of a RTOS. We have applied the aspects to the OSEK OS and have got a customized RTOS with EDF scheduling. The evaluation results show that the overhead of aspect-oriented programming is small enough.

This paper develops a framework for statistically guaranteeing end-to-end delay bounds to envelope-constrained connections transporting real-time traffic in a network of switches employing the earliest deadline first (EDF) packet scheduling scheme in conjunction with per-hop traffic shaping. The performance of an isolated EDF scheduler fed by Markovian sources has been studied earlier in the literature; we extend the analysis to the multi-node setting in the presence of per-node traffic shaping. By making conservative approximations, we show that the analysis is tractable, and offers large performance gains over frameworks which offer deterministic services (the difference is as large as 25% for reasonably realistic traffic mixes). We also investigate the advantages of smoothing the traffic at the ingress to the network. Our framework, we believe, could be of great use in networks which statistically guarantee end-to-end delay bounds to real-time applications.

In multitasking real-time systems, the choice of scheduling algorithm is an important factor to ensure that response time requirements are met while maximising limited system resources. Two popular scheduling algorithms include fixed priority (FP) and earliest deadline first (EDF). While they have been studied in great detail before, they have not been compared when taking into account cache related pre-emption delays (CRPD). Memory and cache are split into a number of blocks containing instructions and data. During a pre-emption, cache blocks from the pre-empting task can evict those of the pre-empted task. When the pre-empted task is resumed, if it then has to re-load the evicted blocks, CRPD are introduced which then affect the schedulability of the task. In this paper we compare FP and EDF scheduling algorithms in the presence of CRPD using the state-of-the-art CRPD analysis. We find that when CRPD is accounted for, the performance gains offered by EDF over FP, while still notable, are diminished. Furthermore, we find that under scenarios that cause relatively high CRPD, task layout optimisation techniques can be applied to allow FP to schedule tasksets at a similar processor utilisation to EDF. Thus making the choice of the task layout in memory as important as the choice of scheduling algorithm. This is very relevant for industry, as it is much cheaper and simpler to adjust the task layout through the linker than it is to switch the scheduling algorithm.

Earliest deadline first (EDF) is a widely-used online algorithm for scheduling jobs with deadlines in real-time systems. Yet, existing results on the performance guarantee of EDF are limited to underloaded systems [6,12,14]. This paper initiates the study of EDF for overloaded systems, attaining similar performance guarantees as in the underloaded setting. Specifically, we show that EDF with a simple form of admission control is optimal for scheduling on both uniprocessor and multiprocessors when moderately faster processors are available (our analysis actually admits a tradeoff between speed and extra processors). This is the first result attaining optimality under overload. Another contribution of this paper is an improved analysis of the competitiveness for weighted deadline 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.

Deadlines are the most important events in real-time systems. Real-time programs must therefore be aware of deadlines, and be able to identify and react to missed deadlines. Moreover, Earliest Deadline First (EDF) is the most widely studied optimal dynamic scheduling algorithm for uniprocessor real-time systems. In this paper we explore how a resource sharing protocol (called the DFP – Deadline Floor inheritance Protocol), which has been proposed for languages such as Ada, can be incorporated into the language’s definition. We also address the programming of systems that have mixed scheduling (e.g. fixed priority and EDF). The incorporation of the DFP into Ada requires some changes to the current predefined packages. These changes are also of use in supporting the programming of deadline-aware systems even when not scheduling by EDF.KeywordsPriority LevelRound RobinEarliest Deadline FirstRelative DeadlineProtected ObjectThese 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.

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.

We propose a new scheme for multiclass packet scheduling which is a variant of EDF (earliest deadline first). The model corrects EDF domino effect in a nearly-overloaded system. Simulations results show that the proposed model performs better than classical EDF by enhancing QoS for soft-real time traffic without significant degradation of less constrained traffic.

This paper presents a system level approach for the synthesis of hard real-time multitask application specific systems. The algorithm takes into account task precedence constraints among multiple hard real-time tasks and targets a multiprocessor system consisting of a set of heterogeneous off-the-shelf processors. The optimization goal is to select a minimal cost multi-subset of processors while satisfying all the required timing and precedence constraints. There are three design phases: resource allocation, assignment, and scheduling. Since the resource allocation is a search for a minimal cost multi-subset of processors, we adopted an A* search based technique for the first synthesis phase. A variation of the force-directed optimization technique is used to assign a task to an allocated processor. The final scheduling of a hard-real time task is done by the task level scheduler which is based on Earliest Deadline First (EDF) scheduling policy. Our task level scheduler incorporates force-directed scheduling methodology to address the situations where EDF is not optimal. The experimental results on a variety of examples show that the approach is highly effective and efficient.