• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.7
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• pp.1304-1320
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• 1994

There are two computation techniques in real time systems : precise and imprecise computation. The imprecise computation technique is a means to provide scheduling flexibility in real time systems. The studies on imprecise scheduling using queueing theoretical formulation up to data are to explicitly quantify the costs and benifits in trade-off between the average result quality and the average waiting time of tasks. This paper uses two imprecise scheduling schemes and solves the imprecision probability, the probability of any task being imprecise under two imprecise scheduling schemes and analyzes the dependence of the imprecision probability on several parameters os the monotone imprecise system.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.42 no.3
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• pp.254-262
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• 2014

Radar task scheduling deals with the assignment of task to efficiently enhance the radar performance on the limited resource environment. In this paper, total weighted tardiness is adopted as the objective function of task scheduling in operation of multiple multi-function radars. To take into account real-time implementability, heuristic index-based methods are presented and investigated. Numerical simulations for generic search and track scenarios are performed to evaluate the proposed methods, in particular investigating the effectiveness of multi-radar operation concepts.

• Proceedings of the Korean Information Science Society Conference
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• 2001.04a
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• pp.82-84
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• 2001

Real-Time Linux는 기존의 Linux에 실시간 기능을 추가한 것으로서, 태스크 스케줄링 방법은 우선순위 기반의 스케줄링 방법을 사용한다. 그러나, 태스크의 개수가 많아지면 가장 높은 우선순위의 태스크를 찾는데 걸리는 시간이 태스크 개수에 비례해서 많이 걸린다. 이러한 이유로 태스크의 개수가 제한적일 수밖에 없다. 본 논문에서는 우선순위별로 서로 다른 목록을 유지하고, Bit Masking 기법을 사용함으로써 가장 높은 우선순위 태스크를 선택하는데 걸리는 시간을 상수시간으로 줄이고 각 태스크들의 시그널을 처리하는 부분을 좀더 효율적으로 처리하도록 함으로써 Real-Time Linux의 실시간 스케줄링 기능을 개선하였다.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.43 no.2 s.308
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• pp.12-20
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• 2006

In scheduling of real-time tasks, the required hardware performance for a given set of tasks is determined based on the worst case execution time. For soft real-time tasks as multimedia applications, a lower performance hardware can service the tasks. Since the execution time of a task can vary in time, we can reclaim the slacks of early completed tasks for those of longer than average execution times. Then, the average ratio of deadline-miss can be lowered. This paper presents an algorithm, Aggressive Slack Reclamation (ASR), that tasks share slacks aggressively. A simulation result shows that ASR enhances the deadline-miss ratio and number of context switches than previous results.

• Journal of KIISE:Computer Systems and Theory
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• v.30 no.1
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• pp.12-21
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• 2003

In this paper, we propose an on-line scheduling algorithm with the goal of maximizing the total reward of IRIS (Increasing Reward with Increasing Service) real-time tasks that have reward functions and arrive dynamically into the system. We focus on enhancing the performance of scheduling algorithm, which W.: based on the following two main ideas. First, we show that the problem to maximize the total reward of dynamic tasks can also be solved by the problem to find minimum of maximum derivatives of reward functions. Secondly, we observed that only a few of scheduled tasks are serviced until a new task arrives, and the rest tasks are rescheduled with the new task. Based on our observation, the Proposed algorithm doesn't schedules all tasks in the system at every scheduling print, but a part of tasks. The performance of the proposed algorithm is verified through the simulations for various cases. The simulation result showed that the computational complexity of proposed algorithm is$O(N_2)$ in the worst case which is equal to those of the previous algorithms, but close to O(N) on the average.

• Journal of Korea Multimedia Society
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• v.20 no.9
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• pp.1559-1566
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• 2017

Recently in the IoT(Internet of Things) environment, a data collection in real-time through device's sensor has increased with an emergence of various devices. Collected data from IoT environment shows a large scale, non-uniform generation cycle and atypical. For this reason, the distributed processing technique is required to analyze the IoT sensor data. However if you do not consider the optimal scheduling for data and the processor of IoT in a distributed processing environment complexity increase the amount in assigning a task, the user is difficult to guarantee the QoS(Quality of Service) for the sensor data. In this paper, we propose APQTA(Adaptive Priority Queue-driven Task Allocation method for sensor data processing) to efficiently process the sensor data generated by the IoT environment. APQTA is to separate the data into job and by applying the priority allocation scheduling based on the deadline to ensure that guarantee the QoS at the same time increasing the efficiency of the data processing.

• Journal of Korea Multimedia Society
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• v.14 no.7
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• pp.940-948
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• 2011

In this paper, we design and implement a task scheduler that considers real-time and fault tolerance in embedded system with a single processor. We propose a method how it can meet the deadlines of periodic tasks using RMS and complete the execution of aperiodic tasks by calculating surplus times from a periodic task set. And we describe a method how to recover of a transient fault task by managing backup time. We propose an important level of periodic tasks that can control the response time of periodic and aperiodic tasks. Finally, we analyse and evaluate the proposed methods by simulation.

• KIISE Transactions on Computing Practices
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• v.23 no.6
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• pp.392-396
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• 2017

Although mobile device-related technologies have developed rapidly, many problems arising from resource constraints have not been solved. Computation offloading that uses resources of cloud servers over the Internet was proposed to overcome physical limitations, and many studies have been conducted in terms of energy saving. However, completing tasks within their deadlines is more important than saving energy in real-time applications. In this paper, we proposed an offloading decision scheme considering the scheduling latency in the cloud to support real-time applications. The proposed scheme can improve the reliability of real-time tasks by comparing the estimated laxity of offloading a task with the estimated laxity of executing a task in a mobile device and selecting a more effective way to satisfy the task's deadline.

• Journal of the Korea Convergence Society
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• v.12 no.2
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• pp.15-20
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• 2021

The imprecise real-time scheduling can be used for minimizing the bad effects of timing faults by leaving less important tasks unfinished if necessary when a transient overload occured. In the imprecise scheduling, every time-critical task can be logically decomposed into two tasks : a mandatory task and an optional task. Recently, some studies in this field showed good schedulability performance and minimum total error by deferring the optional tasks. But the schedulability performance of the studies can be shown only when the execution time of each optional task was less than or equal to the execution time of its corresponding mandatory task. Therefore, in this paper, a new deferring strategy is proposed under the reverse execution time restriction to the previous studies. Nevertheless, the strategy produces comparable or superior schedulability performance to the previous studies and can minimize the total error also.

• Journal of Korea Multimedia Society
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• v.16 no.4
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• pp.493-501
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• 2013

A key challenge in massively multiplayer on-line game(MMOG) systems is providing real-time response latencies to the large number of concurrent game players. MMOG systems are a kind of soft real-time systems because requests from many players should be responded within specified time constraints. Client events have different timeliness and consistency requirements according to their nature in the game world. These requirements lead to tasks with different priorities on CPU processing. In order to meet their timing constraints, we propose priority scheduling methods that attempt to allocate preferentially more CPU bandwidth to serve an task with the higher priority level in the presence of transient overloading. The proposed scheduling methods are capable of enhancing real-time performance of MMOG system by maximizing the number of tasks with higher priority completed successfully within their deadlines while minimizing total average latency of tasks finished after given deadlines. The performance of these scheduling methods is evaluated through extensive simulation experiments.