• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.303-308
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• 1992

In this study, we propose a shared storage system which is more efficient policy than MIS(Mixed Intermediate Storage) policy for relatively rare storage system and can be called CIS(Common Intermediate Storage) policy. Using this strategy, we develop a new completion time algorithm and apply it to two kinds of optimal or near optimal scheduling method; combinatorial search and simulated annealing method. We also extend this strategy to other storage policy, for example MIS policy, with PLC(Programmable Logic Controller) logic and on/off action of electronic valves. It thus can be accepted as a basic form of FMS(Flexible Manufacturing System) for operating various storage policies. Finally we suggest the interlocking block to compansate for the shortcoming of CIS policy, i.e, complication of operation and safety, resulting in a basic batch process automation mode.

• Journal of Korean Institute of Industrial Engineers
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• v.35 no.4
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• pp.218-225
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• 2009

This paper considers a parallel-machine scheduling problem with job release times and sequence-dependent setup times. The objective of this problem is to determine the allocation policy of jobs and the scheduling policy of machines so as to minimize the weighted sum of setup times, delay times, and tardy times. A mathematical model for optimal solution is derived and a meta heuristic algorithm based on the improved ant colony system is proposed in this paper. The performance of the meta heuristic algorithm is evaluated through compare with optimal solutions using randomly generated several examples.

• Journal of Information Processing Systems
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• v.17 no.6
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• pp.1157-1169
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• 2021

Modern graphics processor unit (GPU) architectures offer significant hardware resource enhancements for parallel computing. However, without software optimization, GPUs continuously exhibit hardware resource underutilization. In this paper, we indicate the need to alter different warp scheduler schemes during different kernel execution periods to improve resource utilization. Existing warp schedulers cannot be aware of the kernel progress to provide an effective scheduling policy. In addition, we identified the potential for improving resource utilization for multiple-warp-scheduler GPUs by sharing stalling warps with selected warp schedulers. To address the efficiency issue of the present GPU, we coordinated the kernel-aware warp scheduler and warp sharing mechanism (KAWS). The proposed warp scheduler acknowledges the execution progress of the running kernel to adapt to a more effective scheduling policy when the kernel progress attains a point of resource underutilization. Meanwhile, the warp-sharing mechanism distributes stalling warps to different warp schedulers wherein the execution pipeline unit is ready. Our design achieves performance that is on an average higher than that of the traditional warp scheduler by 7.97% and employs marginal additional hardware overhead.

• Journal of Computing Science and Engineering
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• v.2 no.1
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• pp.74-97
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• 2008

A scheduling policy or a schedulability test is defined to be sustainable if any task system determined to be schedulable remains so if it behaves "better" than mandated by its system specifications. We provide a formal definition of sustainability, and subject the concept to systematic analysis in the context of the uniprocessor scheduling of periodic and sporadic task systems. We argue that it is, in general, preferable engineering practice to use sustainable tests if possible, and classify common uniprocessor schedulability tests according to whether they are sustainable or not.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.4
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• pp.57-64
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• 2012

Multiplayer, real-time games are a kind of soft real-time systems because a game server has to respond to requests from many clients within specified time constraints. Client events have different timeliness and consistency requirements according to their nature in the game world. These requirements lead to different priorities on CPU processing. Events can be divided into different groups, depending on their consistency degree and priority. To handle these events with different priority and meet their timing constraints, we propose a priority-based group task scheduling policy in this paper. The number of clients or events requested by each client may be increased temporarily. In the presence of transient overloading, the game server needs to allocate more CPU bandwidth to serve an event with the higher priority level preferentially. The proposed scheduling policy is capable of enhancing real-time performance of the entire system by maximizing the number of events with higher priority completed successfully within their deadlines. The performance of this policy is evaluated through extensive simulation experiments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.6
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• pp.1877-1891
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• 2022

As a part of cloud computing technology, algorithms for cloud task scheduling place an important influence on the area of cloud computing in data centers. In our earlier work, we proposed DeepEnergyJS, which was designed based on the original version of the policy gradient and reinforcement learning algorithm. We verified its effectiveness through simulation experiments. In this study, we used the Proximal Policy Optimization (PPO) algorithm to update DeepEnergyJS to DeepEnergyJSV2.0. First, we verify the convergence of the PPO algorithm on the dataset of Alibaba Cluster Data V2018. Then we contrast it with reinforcement learning algorithm in terms of convergence rate, converged value, and stability. The results indicate that PPO performed better in training and test data sets compared with reinforcement learning algorithm, as well as other general heuristic algorithms, such as First Fit, Random, and Tetris. DeepEnergyJSV2.0 achieves better energy efficiency than DeepEnergyJS by about 7.814%.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.343-348
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• 1988

This paper describes an application of the periodic scheduling policy to a class of flexible manufacturing systems. A heuristic algorithm is used to determine when each part should be loaded into the system. Simulation results based on a detailed model of metal-working manufacturing facility are presented.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.9A
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• pp.702-709
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• 2003

In this paper, we propose an efficient and QoS-aware MAC scheduling algorithm for Bluetooth, which considers both throughput and delay performance of each Master-Slave pair in scheduling decisions, and thus, attempts to maximize overall performance. The proposed algorithm, MTDPP (Modified Throughput-Delay Priority Policy), makes up for the drawbacks of T-D PP (Throughput-Delay Priority Policy) proposed in [6] and improves the performance. Since Bluetooth employs a master-driven TDD based scheduling algorithm, which is basically operated with the Round Robin policy, many slots may be wasted by POLL or NULL packets when there is no data waiting for transmission in queues. To overcome this link wastage problem, several algorithms have been proposed. Among them, queue state-based priority policy and low power mode-based algorithm can perform with high throughput and reasonable fairness. However, their performances may depend on traffic characteristics, i.e., static or dynamic, and they require additional computational and signaling overheads. In order to tackle such problems, we propose a new scheduling algorithm. Performance of our proposed algorithm is evaluated with respect to throughput and delay. Simulation results show that overall performances can be improved by selecting suitable parameters of our algorithm.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.5
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• pp.219-230
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• 2017

General-Purpose Graphics Processing Units (GPGPUs) build massively parallel architecture and apply multithreading technology to explore parallelism. By using programming models like CUDA, and OpenCL, GPGPUs are becoming the best in exploiting plentiful thread-level parallelism caused by parallel applications. Unfortunately, modern GPGPU cannot efficiently utilize its available hardware resources for numerous general-purpose applications. One of the primary reasons is the inefficiency of existing warp/thread block schedulers in hiding long latency instructions, resulting in lost opportunity to improve the performance. This paper studies the effects of hardware thread scheduling policy on GPGPU performance. We propose a novel warp scheduling policy that can alleviate the drawbacks of the traditional round-robin policy. The proposed warp scheduler first classifies the warps of a thread block into two groups, warps with long latency and warps with short latency and then schedules the warps with long latency before the warps with short latency. Furthermore, to support the proposed warp scheduler, we also propose a supplemental technique that can dynamically reduce the number of streaming multiprocessors to which will be assigned thread blocks when encountering a high contention degree at the memory and interconnection network. Based on our experiments on a 15-streaming multiprocessor GPGPU platform, the proposed warp scheduling policy provides an average IPC improvement of 7.5% over the baseline round-robin warp scheduling policy. This paper also shows that the GPGPU performance can be improved by approximately 8.9% on average when the two proposed techniques are combined.

• Journal of KIISE:Computing Practices and Letters
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• v.5 no.6
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• pp.738-747
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• 1999

본 논문에서는 분산 실시간 시스템의 특징인 분산 처리 과정의 신뢰성을 지원하기 위한 동적 트랜잭션 처리 구조를 연구하였다. 실시간 분산 처리 환경에서 동적으로 발생하는 실시간 분산 트랜잭션 처리를 위하여 트랜잭션 내에 필수적인 3가지 언어적 특성들을 제시하였다. 첫째는 트랜잭션 내에 실시간 시스템의 가장 중요한 특징인 시간적인 제약 조건들을 정의 할 수 있는 방안을 제시하고, 둘째는 비동기적인 처리 성격을 지닌 실시간 특성을 고려한 비동기적 트랜잭션 처리 방법을 제시한다. 또한, 분산 처리 과정에서 발생되는 예외 사항들을 처리하기 위하여 긴급성을 고려한 다중레벨 우선순위 스케줄링 (Multi-Level Priotiry Scheduling)이라 부르는 트랜잭션 스케줄링 방안을 제시한다. 그리고, 제시한 실시간 분산 트랜잭션 처리 구조의 타당성 및 가능성을 입증하기 위한 실시간 트랜잭션 처리 과정을 시물레이션을 통하여 제시한 언어적 특성에 대한 고려 사항들을 보여준다.Abstract We propose a dynamic transaction processing model that supports a reliability for distributed real-time processing. For the dynamic processing in distributed real-time transaction systems, we suggest three features that are defined in programming language. First, we propose a specification model to explicitly define the time constraints, needs in real-time distributed processing. Second, we describe an asynchronous transaction processing mechanism based on the real-time characteristics. So, we suggest three communication primitives to support asynchronous transaction processing. Lastly, a scheduling policy based on urgent transaction is suggested to manage the exception occurred during the distributed processing. This scheduling policy is called multi-level priotiry scheduling (MPLS). Based on three features and scheduling policy, we describe a direction to manage a dynamic transaction processing in distributed real-time systems.