• Journal of KIISE:Computer Systems and Theory
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• v.27 no.6
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• pp.549-557
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• 2000

Distributed Memory Machine(DMM) is necessary for the effective computation of the data which is complicated and very large. Task scheduling is a method that reduces the communication time among tasks to reduce the total execution time of application program and is very important for the improvement of DMM. Task Duplicated based Scheduling(TDS) method improves execution time by reducing communication time of tasks. It uses clustering method which schedules tasks of the large communication time on the same processor. But there is a problem that cannot optimize communication time between task sending data and task receiving data. Hence, this paper proposes a new method which solves the above problem in TDS. Modified Task Duplicated based Scheduling(MTDS) method which can approximately optimize the communication time between task sending data and task receiving data by checking the optimal condition, resulted in the minimization of task execution time by reducing the communication time among tasks. Also system modeling shows that task execution time of MTDS is about 70% faster than that of TDS in the best case and the same as the result of TDS in the worst case. It proves that MTDS method is better than TDS method.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.1
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• pp.193-200
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• 2011

This paper presents an optimal checkpoint strategy for fault-tolerance in real-time systems. In our environment, multiple real-time tasks with arbitrary periods are scheduled in the system by Rate Monotonic (RM) algorithm, and checkpoints are inserted at a constant interval in each task while the width of interval is different with respect to the task. We propose a method to determine the optimal checkpoint interval for each task so that the probability of completing all the tasks is maximized. Whenever a fault occurs to a checkpoint interval of a task, the execution time of the task would be prolonged by rollback and re-execution of checkpoints. Our scheme includes the schedulability test to examine whether a task can be completed with an extended execution time. A numerical experiment is conducted to demonstrate the applicability of the proposed scheme.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.5
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• pp.875-880
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• 2008

In this paper, a novel method to determine the optimal checkpoint interval for real-time control task is proposed considering its performance degradation according to tasks's execution time. The control task in this paper has a specific sampling period shorter than its deadline. Control performance is degraded as the control task execution time is prolonged across the sampling period and eventually zero when reached to the deadline. A new performance index is defined to represent the performance variation due to the extension of task execution time accompanying rollback fault recovery. The procedure to find the optimal checkpoint interval is addressed and several simulation examples are presented.

• International Journal of Computer Science & Network Security
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• v.21 no.4
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• pp.19-27
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• 2021

Tasks scheduling have been gaining attention in both industry and research. The scheduling that ensures independent task execution is critical in real-time systems. While task scheduling has gained a lot of attention in recent years, there have been few works that have been implemented into real-time architecture. The efficiency of the classical scheduling strategy in real-time systems, in particular, is still understudied. To reduce total waiting time, we apply three scheduling approaches in this paper: First In/First Out (FIFO), Shortest Execution Time (SET), and Shortest-Longest Execution Time (SLET). Experimental results have demonstrated the efficacy of the SLET in comparison with the others in most cases in a wide range of configurations.

• Journal of KIISE:Computer Systems and Theory
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• v.29 no.11
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• pp.601-610
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• 2002

Intra-task voltage scheduling (IntraVS), which adjusts the supply voltage within an individual task boundary, is an effective technique for developing low-power applications. In this paper, we propose a novel intra-task voltage scheduling algorithm for hard real-time applications based on average-case execution time. Unlike the conventional IntraVS algorithm where voltage scaling decisions are based on the worst-case execution cycles, tile proposed algorithm improves the energy efficiency by controlling the execution speed based on average-case execution cycles while meeting the real-time constraints. The experimental results using an MPEG-4 decoder program show that the proposed algorithm reduces the energy consumption by up to 34% over conventional IntraVS algorithm.

• Journal of Computing Science and Engineering
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• v.4 no.3
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• pp.189-206
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• 2010

It is generally accepted that dynamic voltage scaling (DVS) is one of the most effective techniques of energy minimization for real-time applications in embedded system design. The effectiveness comes from the fact that the amount of energy consumption is quadractically proportional to the voltage applied to the processor. The penalty is the execution delay, which is linearly and inversely proportional to the voltage. According to the granularity of tasks to which voltage scaling is applied, the DVS problem is divided into two subproblems: inter-task DVS problem, in which the determination of the voltage is carried out on a task-by-task basis and the voltage assigned to the task is unchanged during the whole execution of the task, and intra-task DVS problem, in which the operating voltage of a task is dynamically adjusted according to the execution behavior to reflect the changes of the required number of cycles to finish the task before the deadline. Frequent voltage transitions may cause an adverse effect on energy minimization due to the increase of the overhead of transition time and energy. In addition, DVS needs to be carefully applied so that the dynamically varying chip temperature should not exceed a certain threshold because a drastic increase of chip temperature is highly likely to cause system function failure. This paper reviews representative works on the theoretical solutions to DVS problems regarding inter-task DVS, intra-task DVS, voltage transition, and thermal-aware DVS.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.7
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• pp.1704-1712
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• 2014

The unused Worst-Case Execution Time (WCET) allocated to a real-time task occurs when the actual execution time of the task can be far less than the WCET preassigned to the task for a schedulability test. Any unused WCET allocated to the task can be exploited to reduce the power consumption of battery-powered sensor nodes through real-time power-aware scheduling techniques. From the distribution perspective of the unused WCET, the unused WCET distribution policy is classified into three types: Conservative Unused WCET (CU-WCET), Moderate Unused WCET (MU-WCET), and Aggressive Unused WCET (AU-WCET) distribution policies. We evaluated the performance of real-time power-aware scheduling techniques incorporating each of three unused WCET distribution policies in terms of low power consumption.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.1
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• pp.162-169
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• 2022

Arduino is used in various places such as education, experimentation, and industry. Due to the easy accessibility of Arduino, it is often used by non-majors, and it is also used in media art and toy programs. Although Arduino is relatively easy to use compared to other devices, it is not easy to control various IoT components at the same time. Some tasks run independently of other tasks, while others run dependently. In this paper, I proposed the Arduino Task Framework to efficiently execute many tasks in these various situations. The design framework of this paper is largely composed of two types: synchronous execution and asynchronous execution. These two execution methods can be combined to create several independent and dependent execution routines. Asynchronous tasks are independently executed tasks and are managed by AsyncTaskGroup, while synchronous tasks are dependently executed tasks and are managed by SyncTaskGroup. AsyncTaskGroup instance and SyncTaskGroup instance are instances of the same Task and can be used in combination with another task. The Arduino framework proposed in this paper simplifies the program structure and can easily compose various tasks.

• Journal of Information Processing Systems
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• v.7 no.4
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• pp.707-716
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• 2011

It is important that desktop grids should be able to aggressively deal with the dynamic properties that arise from the volatility and heterogeneity of resources. Therefore, it is required that task scheduling be able to positively consider the execution behavior that is characterized by an individual resource. In this paper, we implement a log analysis system with REST web services, which can analyze the execution behavior by utilizing the actual log data of desktop grid systems. To verify the log analysis system, we conducted simulations and showed that the resource group-based task scheduling, based on the analysis of the execution behavior, offers a faster turnaround time than the existing one even if few resources are used.

• The Transactions of the Korea Information Processing Society
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• v.4 no.9
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• pp.2235-2246
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• 1997

This paper presents an effective heuristic task scheduling algorithm for multiprocessor systems. To execute task scheduling effectively which is defined as an allocation of m's tasks onto n's processors(m > n), several problems almost at NP-hard should be cleaned up. The purpose of the task scheduling obtains the minimum execution time by mapping the tasks on a system topology or reduces the total execution time to give a minimum system topology. In order to solve this problem, in this paper, the task scheduling is done by redefining a task graph to a reconstructed task graph (RTG). An RTG is obtained by merging or copying nodes to equal the number of nodes on each level of the task graph to the number of processors of the system topology and then directly scheduled to the system topology. This method obtains a fast scheduling time and a simple scheduling method, and near-optimal execution time without executing steps such as the refinement step and the duplication step after the task scheduling.