Synthesis of Hard Real-Time Application Specific Systems

The scheduling of parallel real-time tasks on multiprocessor systems is more complicated than the one of independent sequential tasks, specially for the Directed Acyclic Graph (DAG) model. The complexity is due to the structure of DAG tasks and the precedence constraints between their subtasks. The trivial DAG scheduling approach is to directly apply common real-time scheduling algorithms on DAGs despite their lack of compatibility with the parallel model. Another scheduling approach, which is called the stretching method, aims at transforming each parallel DAG task in the set into a collection of independent sequential threads that are easier to be scheduled. In this paper, we are interested in analyzing global preemptive scheduling of DAGs using both approaches by showing that they are not comparable when associated with Deadline Monotonic (DM) and Earliest Deadline First (EDF) scheduling algorithms. Then we use extensive simulations to evaluate their schedulability performance. To this end, we use our simulation tool YARTISS to generate random DAG tasks with many parameter variations so as to guarantee reliable experimental 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.

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.

PurposeIn recent years, it is imperative to establish the structure of manufacturing industry in the context of smart factory. Due to rising demand for exchange of information with various devices, and huge number of sensor nodes, the industrial wireless networks (IWNs) face network congestion and inefficient task scheduling. For this purpose, software-defined network (SDN) is the emerging technology for IWNs, which is integrated into cognitive industrial Internet of things for dynamic task scheduling in the context of industry 4.0.Design/methodology/approachIn this paper, the authors present SDN based dynamic resource management and scheduling (DRMS) for effective devising of the resource utilization, scheduling, and hence successful transmission in a congested medium. Moreover, the earliest deadline first (EDF) algorithm is introduced in authors’ proposed work for the following criteria’s to reduce the congestion in the network and to optimize the packet loss.FindingsThe result shows that the proposed work improves the success ratio versus resource usage probability and number of nodes versus successful joint ratio. At last, the proposed method outperforms the existing myopic algorithms in terms of query response time, energy consumption and success ratio (packet delivery) versus number of increasing nodes, respectively.Originality/valueThe authors proposed a priority based scheduling between the devices and it is done by the EDF approach. Therefore, the proposed work reduces the network delay time and minimizes the overall energy efficiency.

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.

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.

DYNAMIC SCHEDULING SOLUTIONS FOR REAL-TIME MULTIPROCESSOR SYSTEMS

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.

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.

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.

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.

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.