• Proceedings of the Korea Information Processing Society Conference
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• 2002.11a
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• pp.229-232
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• 2002

분간 병렬 시스템에서 사용되는 배치 작업 스케줄링 기법으로 잘 알리진 것은 Gang Scheduling과 Backfilling Scheduler가 있다. 특히 IBM SP 시스템에서 주로 사용되는 작업 스케줄러인 LoadLeveler 최신 버전에서는 이전 버전에서도 지원하였던 Backfilling Scheduler 뿐만 아니라 Gang Scheduling 기법을 새롭게 지원하게 되었다. 이에 따라 KISTI 슈퍼컴퓨팅센터에서는 슈퍼컴퓨터 3호기로 신규 도입된 IBM p690 시스템에서 LoadLeveler의 Gang Scheduling 혹은 Backfilling Scheduler 중의 한 가지 기법을 선택하여 서비스 레벨 클래스를 구현하고자 하였다. 이러한 노력의 일환으로 두 가지 스케줄링 기법을 테스트 및 분석하였다. 이에 따르면 Gang Scheduler가 개념상 여러 가지 장점을 가지므로 Backfilling Scheduler에 비하여 서비스 레벨 클래스 구성에는 용이하지만, 불완전한 구현 및 특히 CPU Utilization이 저하되는 심각한 문제점을 가지고 있었다. 따라서 Backfilling Scheduler를 통한 제한적인 서비스 레벨 클래스를 구성하기로 결론지었다.

• International Journal of Contents
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• v.6 no.4
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• pp.30-34
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• 2010

Effective job scheduling scheme is a crucial part of complex heterogeneous distributed systems. Gang scheduling is a scheduling algorithm for grid systems that schedules related grid jobs to run simultaneously on servers in different local sites. In this paper, we address grid jobs (gangs) schedule modeling using Stochastic reward nets (SRNs), which is concerned for static and dynamic scheduling policies. SRN is an extension of Stochastic Petri Net (SPN) and provides compact modeling facilities for system analysis. Threshold queue is adopted to smooth the variations of performance measures. System throughput and response time are compared and analyzed by giving reward measures in SRNs.

• Proceedings of the Korea Information Processing Society Conference
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• 2007.11a
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• pp.630-633
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• 2007

클러스터를 이용하여 다수의 작업을 실행시키는 경우에 효율적으로 사용자들이 자원을 사용하기 위해서는 작업 스케줄링이 매우 중요하다. 다양한 스케줄링 방법들이 제안되었으며 그 중 효율적으로 병렬 작업을 스케쥴링하기 위해 제안된 방법으로는 backfilling, co-scheduling, gang scheduling을 들 수 있다. 이러한 연구에서는 이론적인 논의가 많았고, 실제로 구현을 했다고 하더라고 multiprocessor 를 대상으로 backfilling 을 다룬 내용이 대부분이었다. 이 논문은 클러스터상에서의 parallel job scheduling 에 대해 조사하였다.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.20 no.1
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• pp.14-23
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• 1996

Scheduling jobs effectively under consideration of actual loads on machines is one of the most complicated tasks in production control. The complexity of the finite capacity scheduling often makes the conventional methods of industrial engineering fail. As an alternative, Knowledge-based approaches to job-shop scheduling have been evolved recently. This paper presents a blackboard- based scheduling expert system which combines knowledge-based scheduling with interactive scheduling. It is shown to be possible to generate the feasible schedule within a reasonable time. Flexible reaction management is also possible while keeping the changes in the generated schedule to the minimal and adjusting the schedule to tardy operations or working environmental changes. The system is equipped with a rule base with heuristics for handling conflicted event. A case study applying the implemented system is described.

• Journal of Communications and Networks
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• v.7 no.4
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• pp.408-416
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• 2005

Quality of service (QoS) provision is an important and indispensable function for multi-service wireless networks. In this paper, we present a new scheduling/admission control frame­work, including an efficient rate-guaranteed opportunistic scheduling (ROS) scheme and a coordinated admission control (ROS­CAC) policy to support statistic QoS guarantee in multi-service wireless networks. Based on our proposed mathematical model, we derive the probability distribution function (PDF) of queue length under ROS and deduce the packet loss rate (PLR) for individual flows. The new admission control policy makes admission decision for a new incoming flow to ensure that the PLR requirements of all flows (including the new flow) are satisfied. The numerical results based on ns-2 simulations demonstrate the effectiveness of the new joint packet scheduling/admission control framework.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.37 no.4
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• pp.26-36
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• 2000

This paper proposes a neural network algorithm for real-time multiprocessor scheduling problem. The proposed algorithm is developed base on Hopfield neural network for a benefit of parallel processing, in order to finish a requested task within a deadline time. To compare the performance of the proposed algorithm, we used EDA and LLA algorithm that has studied real-time multiprocessor scheduling before. The proposed algorithm is implemented hardware using VHDL.

• Journal of Korean Institute of Industrial Engineers
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• v.13 no.2
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• pp.9-16
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• 1987

This paper develops an optimal manpower scheduling algorithm that gives an optimal workforce size and day-off scheduling required to satisfy following conditions. First, everyone is to have two consecutive day-off per cycle in a continuous operating environment. Second, everyone is to have at least A weekends off in a cycle of B Weeks. The model addressed is under the circumstance that the demands can vary from day to day in a weekly cycle. The proposed algorithm makes it possible to minimize the maximum workstretch and to maximize the number of weekends off. It is also possible to minimize the variance of idle manpower distribution in order that idle manpower may be utilized in case of emergency.

• Proceedings of the Safety Management and Science Conference
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• 2007.11a
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• pp.411-423
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• 2007

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.9
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• pp.839-845
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• 2013

A CSTR (Continuous Stirred Tank Reactor) is a highly nonlinear process with varying parameters during operation. Therefore, tuning of the controller and determining the transition policy of controller parameters are required to guarantee the best performance of the CSTR for overall operating regions. In this paper, a methodology employing the 2DOF (Two-Degree-of-Freedom) PID controller, the anti-windup technique and a fuzzy gain scheduler is presented for the temperature control of the CSTR. First, both a local model and an EA (Evolutionary Algorithm) are used to tune the optimal controller parameters at each operating region by minimizing the IAE (Integral of Absolute Error). Then, a set of controller parameters are expressed as functions of the gain scheduling variable. Those functions are implemented using a set of "if-then" fuzzy rules, which is of Sugeno's form. Simulation works for reference tracking, disturbance rejecting and noise rejecting performances show the feasibility of using the proposed method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.3
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• pp.1091-1110
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• 2016

Hybrid deployment under current cloud data centers is a combination of online and offline services, which improves the utilization of the cluster resources. However, the performance of the cluster is often affected by the online services in the hybrid deployment environment. To improve the response time of online service (e.g. search engine), an effective scheduling algorithm based on Storm is proposed. At the component level, the algorithm dispatches the component with more influence to the optimal performance node. Inside the component, a reasonable resource allocation strategy is used. By searching the compressed index first and then filtering the complete index, the execution speed of the component is improved with similar accuracy. Experiments show that our algorithm can guarantee search accuracy of 95.94%, while increasing the response speed by 68.03%.