A Survey for Task Scheduling in Real Time Distributed System

Scheduling is a technique which makes an arrangement of performing certain tasks at specified period. The intervals between each function have been clearly defined by the algorithm to avoid any overlapping. The real time computing systems are those in which there are strict timing constraints that have to be met to get the correct output i.e. the output not only depend on the correctness of the outcome but also on the time at which results are produced. Real time systems are expected to change its state in real time even after the controlling processor has stopped its execution. The bound in which real time applications are needed to respond to the stimuli is known as deadline. In order to achieve optimized results in a real rime operations the scheduling techniques has been used. In the paper we classify the various scheduling techniques based on different parameters. Also techniques used for scheduling in real time environment are analyzed and comparison between different techniques have been done. The various issues have been presented on which there is still a need to work.

Scheduling of real time tasks are very important aspect in systems as processes should complete its task at a specific time. There is a need of high energy efficiency and low response time in large data stream so for this energy efficient resources and optimized frameworks are needed. Both hard real time and mixed critically systems are targeted. Soft deadline can be handled while hard deadlines are difficult to cater. Different algorithms are used to schedule tasks like rate monotonic, earliest deadline first, deadline monotonic etc.

IJRCAR, 2014

The problem of real-time scheduling spans a broad spectrum of algorithms from simple uniprocessor to highly sophisticated multiprocessor scheduling algorithms. Real-time software must satisfy not only functional correctness requirements but also timeliness requirements. A lot of real-time researches were focused on analysis rather than testing recently, observes that real-time testing is still a “lost-world” compared to “civilization” developed in other areas of software, reflecting the little work done in the area. In this paper, we have studied the various scheduling algorithm of the real time system.

Real-Time systems are becoming pervasive. In a Real-Time System the correctness of the system behavior depends not only on the logical results of the computations, but also on the physical instant at which these results are produced. A missed deadline in hard real-time systems is catastrophic and in soft real-time systems it can lead to a significant loss .This work talks about static and dynamic scheduling algorithms for real time task. The problem of real-time scheduling spans a broad spectrum of algorithms from simple uniprocessor to highly sophisticated multiprocessor scheduling algorithms which are priority driven and divided into three classes fixed priority, dynamic priority and hybrid priority. Finally conclusion shows that Instantaneous utilization factor scheduling Algorithm gives better result in uniprocessor scheduling algorithms and Modified Instantaneous utilization factor scheduling Algorithm gives better context switching, response time and CPU utilization as compared to previous scheduling algorithms.

IEEE Transactions on Parallel and Distributed Systems, 1998

Many time-critical applications require predictable performance and tasks in these applications have deadlines to be met. In this paper, we propose an efficient algorithm for nonpreemptive scheduling of dynamically arriving real-time tasks (aperiodic tasks) in multiprocessor systems. A real-time task is characterized by its deadline, resource requirements, and worst case computation time on p processors, where p is the degree of parallelization of the task. We use this parallelism in tasks to meet their deadlines and, thus, obtain better schedulability compared to nonparallelizable task scheduling algorithms. To study the effectiveness of the proposed scheduling algorithm, we have conducted extensive simulation studies and compared its performance with the myopic [8] scheduling algorithm. The simulation studies show that the schedulability of the proposed algorithm is always higher than that of the myopic algorithm for a wide variety of task parameters.

1998

In a parallelizable task model, a task can be parallelized and the component tasks can be executed concurrently on multiple processors. We use this parallelism in tasks to meet their deadlines and also obtain better processor utilisation compared to non-parallelized tasks. Non-preemptive parallelizable task scheduling combines the advantages of higher schedulability and lower scheduling overhead o ered by the preemptive and non-preemptive task scheduling models, respectively. We propose a new approach to maximize the bene ts from task parallelization. It involves checking the schedulability of periodic tasks (if necessary, by parallelizing them) o-line and run-time scheduling of the schedulable periodic tasks together with dynamically arriving aperiodic tasks. To avoid the run-time anomaly that may occur when the actual computation time of a task is less than its worst case computation time, we propose e cient run-time mechanisms. We have carried out extensive simulation to study the e ectiveness of the proposed approach by comparing the schedulability o ered by it with that of dynamic scheduling using Earliest Deadline First (EDF), and by comparing its storage e ciency with that of the static table-driven approach. We found that the schedulability o ered by parallelizable task scheduling is always higher than that of the EDF algorithm for a wide variety of task parameters and the storage overhead incurred by it is less than 3.6% of the static table-driven approach even under heavy task loads.

We evaluate the options available to the designers of schedulers or real-time tasks in distributed systems. We also present a select subset of scheduling algorithms ranging from the classic Rate Monotonic Scheduling algorithm to the recent Real Time Self Adjusting Dynamic scheduling algorithm. Each algorithm is evaluated on the design choices made and their applicability to the problem at hand.

Asian Journal of Research in Computer Science

The term "Real-Time Operating System (RTOS)" refers to systems wherein the time component is critical. For example, one or more of a computer's peripheral devices send a signal, and the computer must respond appropriately within a specified period of time. Examples include: the monitoring system in a hospital care unit, the autopilot in the aircraft, and the safety control system in the nuclear reactor. Scheduling is a method that ensures that jobs are performed at certain times. In the real-time systems, accuracy does not only rely on the outcomes of calculation, and also on the time it takes to provide the results. It must be completed within the specified time frame. The scheduling strategy is crucial in any real-time system, which is required to prevent overlapping execution in the system. The paper review classifies several previews works on many characteristics. Also, strategies utilized for scheduling in real time are examined and their features compared.

2014 Seventh International Conference on Contemporary Computing (IC3), 2014

This paper presents a real time scheduling algorithm for mixed task set on homogeneous multi-core platform. Periodic tasks are scheduled using Partitioned Earliest Deadline First (P-EDF) technique. Aperiodic tasks are assigned globally to different processor cores and scheduled using Total Bandwidth Server (TBS) on each core. In the proposed algorithm, the excess processing capacity of the cores left unused by the periodic tasks can be utilized by assigning aperiodic task to each core. This improves the overall utilization of individual core. Work conserving nature of global assignment reduces response time of aperiodic task. The proposed algorithm is implemented using java based simulator and tested on large number of synthetic test data. Results show improvement in utilization of individual processing core and improvement in response time of aperiodic tasks. Keywords-multi-core processors, partitioned approach, mixed real time task set, Response Time etc. I.

Most currently existing optimal real-time multiprocessor scheduling algorithms follow the fairness rule, in which all tasks are forced to make progress in their executions proportional to their utilization, to ensure the optimality of the algorithm. However, obeying the fairness rule results in large number of task preemptions and migrations and these highly affect the practicability of the algorithm. In this paper, we present an efficient real-time multiprocessor scheduling algorithm in which the fairness rule is completely relaxed and a semi-greedy algorithm is introduced. In the simulation, the proposed algorithm showed promising results in terms of number of task preemptions and migrations that are very few compared to the current state of the art real-time multiprocessor scheduling algorithms. Although the algorithm can sometimes miss a very few deadlines, we assume that these deadline misses can be tolerated in view of the great reduction of task preemptions and migrations.