Scheduling Of Hard Real-time Tasks Research Articles

Correction: Mahmood et al. Hard Real-Time Task Scheduling in Cloud Computing Using an Adaptive Genetic Algorithm. Computers 2017, 6, 15

In article by Mahmood [1], the results for a genetic algorithm (GA), adaptive genetic algorithm (AGA), and greedy algorithm were not correctly reported in Section 5 due to a programming error[...]

Reliable real-time task scheduler based on Rocket Queue architecture

This paper presents the design of an improved task scheduler for real-time and safety-critical systems, where it is important to deal with real-time requirements and reliability requirements simultaneously. The proposed scheduler implements EDF algorithm for the optimal scheduling of hard real-time tasks, which is essential for real-time operating systems. The proposed task scheduler allows removing any task from the queue according to task ID and regardless of the actual position of the task within the queue, which is important for flexibility of the scheduler for its future extensions. Both operations of the scheduler, i.e. task adding and task killing take always constant time (two clock cycles) to execute regardless of the actual or the maximum number of tasks within the scheduler. The scheduler was verified using simplified version of UVM and applying millions of instructions with randomly generated sort values. The scheduler, implemented in a form of a coprocessor, was synthesized into Intel FPGA Cyclone V with 100MHz clock frequency. There are two improvements proposed that can significantly reduce resource costs of the scheduler, which is achieved by replacing static deadlines with dynamic deadlines and using a new Rocket Queue architecture for sorting of the tasks according to their deadline values. When both improvements are applied simultaneously, the total ALM cost savings are in the range from 42,59% to 60,18% and the total amount of registers is reduced by 73,74% to 74,87%, depending on the scheduler capacity. The spared resources are then used for implementation of two different variations of TMR in order to increase fault tolerance of the scheduler. The resource cost reductions achieved also indirectly increase the reliability of such scheduler because of reduced probability that a fault occurs.

Predictable CPU Architecture Designed for Small Real-Time Application - Concept and Theory of Operation

The purpose of this paper is to describe an predictable CPU architecture, based on the five stage pipeline assembly line and a hardware scheduler engine. We aim at developing a fine-grained multithreading implementation, named nMPRA-MT. The new proposed architecture uses replication and remapping techniques for the program counter, the register file, and the pipeline registers and is implemented with a FPGA device. An original implementation of a MIPS processor with thread interleaved pipeline is obtained, using dynamic scheduling of hard real-time tasks and interrupts. In terms of interrupts handling, the architecture uses a particular method consisting of assigning interrupts to tasks, which insures an efficient control for both the context switch, and the system real-time behavior. The originality of the approach resides in the predictability and spatial isolation of the hard real-time tasks, executed every two clock cycles. The nMPRA-MT architecture is enabled by an innovative scheme of predictable scheduling algorithm, without stalling the pipeline assembly line.

Fault tolerant scheduling of hard real-time tasks on multiprocessor system using a hybrid genetic algorithm

Conventional methods for fault-tolerant scheduling of real-time tasks based on traditional heuristic approach offer poor performance and inefficient system utilization. The primary-backup (PB) approach is often used as a fault-tolerant scheduling technique to guarantee RT tasks to meet their deadline despite the presence of fault. We propose a novel scheduling algorithm using optimization approach based on genetic algorithm (GA) hybridized with knowledge from the real-time task scheduling domain for providing fault-tolerance (FT) in multiprocessor environment. Exhaustive simulation reveals that the new GA based primary-backup fault-tolerant scheduling (PBFTS) approach outperforms other fault-tolerant scheduling schemes in terms of system utilization and efficiency.

Operating systems for reconfigurable embedded platforms: online scheduling of real-time tasks

Today's reconfigurable hardware devices have huge densities and are partially reconfigurable, allowing for the configuration and execution of hardware tasks in a true multitasking manner. This makes reconfigurable platforms an ideal target for many modern embedded systems that combine high computation demands with dynamic task sets. A rather new line of research is engaged in the construction of operating systems for reconfigurable embedded platforms. Such an operating system provides a minimal programming model and a runtime system. The runtime system performs online task and resource management. In this paper, we first discuss design issues for reconfigurable hardware operating systems. Then, we focus on a runtime system for guarantee-based scheduling of hard real-time tasks. We formulate the scheduling problem for the 1D and 2D resource models and present two heuristics, the horizon and the stuffing technique, to tackle it. Simulation experiments conducted with synthetic workloads evaluate the performance and the runtime efficiency of the proposed schedulers. The scheduling performance for the 1D resource model is strongly dependent on the aspect ratios of the tasks. Compared to the 1D model, the 2D resource model is clearly superior. Finally, the runtime overhead of the scheduling algorithms is shown to be acceptably low.

Sporadic task scheduling with overload conditions

Hard real-time task scheduling in a dynamic environment has been an important area of research, posing difficult problems. In an overloaded system where periodic and sporadic tasks have computational demands that are greater than the CPU time in that interval, the scheduler faces the question of which tasks must really make their deadlines. Assuming that periodic tasks have priority over sporadic ones, we end up with a system where some sporadic tasks may not make their deadlines. It is known that through the assignment of priorities to tasks based on the earliest deadline policy, there is no way to predict which sporadic task will miss the deadline and which will not. In order to prevent important sporadic tasks from missing their deadlines, we assign each task an importance function that is used by the scheduling algorithm. Generally, the summation of important function values must be maximized to allow the most important tasks to meet their timing constraints. We present two novel scheduling algorithms that try to maximize this summation. We show that these algorithms have better performance compared to related algorithms regarding complexity and benefit optimization.

Conditions for On-line Scheduling of Hard Real-Time Tasks on Multiprocessors

In this paper we consider the problem ofon-linescheduling ofhard real-timetasks onmultipleprocessors. For a given set of ready tasks, one can propose many schedules. These schedules, however, may not necessarily be suitable for on-line scheduling. A suitable on-line schedule is one which can accommodate any future task set when it arrives. The traditional approach to solve the on-line scheduling problem is to propose a heuristic, and then to prove its effectiveness by comparing it with existing heuristics using simulation. No attempt has, however, been made to obtain a condition on the current schedule which when satisfied will permit one to schedule an arbitrary future task. In this paper, we aim at developing such a condition on the current schedule for the set of ready tasks which when satisfied can guarantee an on-line schedule for any futurefeasibletask set.

DYNAMIC SCHEDULING SOLUTIONS FOR REAL-TIME MULTIPROCESSOR SYSTEMS

This paper analyzes the behavior and performance of four dynamic algorithms for multiprocessor scheduling of hard real-time tasks. The well-known algorithms are the Earliest Deadline First (EDF) algorithm and the Least Laxity First (LLF) algorithm. An important feature of the original ones is that they are guarantee-oriented. The performance of these algorithms has been measured through simulations which analyze the behavior of the algorithms under two main load hypotheses: static loads and dynamic loads. The simulation results present practical bounds and a comparative study of the loads that they are able to guarantee, context switches and cpu utilization. Copyright © 1997 Elsevier Science Ltd

Dynamic Scheduling Solutions for Real-Time Multiprocessor Systems

This paper analyzes the behavior and performance of four dynamic algorithms for multiprocessor scheduling of hard real-time tasks. The well known algorithms are the Earliest Deadline First (EDF) algorithm and the Least Laxity First (LLF) algorithm. An important feature of the original ones is that they are guarantee-oriented.The performance of these algorithms has been measured through simulations which analyze the behavior of the algorithms under two main load hypothesis: static load and dynamic load. Simulation results present practical bounds and a comparative study on the loads that they are able to guarantee, context switches and cpu utilization.

Dynamic scheduling of hard real-time tasks and real-time threads

The authors investigate the dynamic scheduling of tasks with well-defined timing constraints. They present a dynamic uniprocessor scheduling algorithm with an O(n log n) worst-case complexity. The preemptive scheduling performed by the algorithm is shown to be of higher efficiency than that of other known algorithms. Furthermore, tasks may be related by precedence constraints, and they may have arbitrary deadlines and start times (which need not equal their arrival times). An experimental evaluation of the algorithm compares its average case behavior to the worst case. An analytic model used for explanation of the experimental results is validated with actual system measurements. The dynamic scheduling algorithm is the basis of a real-time multiprocessor operating system kernel developed in conjunction with this research. Specifically, this algorithm is used at the lowest, threads-based layer of the kernel whenever threads are created. >