• Proceedings of the Korean Information Science Society Conference
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• 2004.04a
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• pp.100-102
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• 2004

예측할 수 없이 빈번하게 발생하는 인터럽트와 인터럽트 처리시간의 대부분을 차지하는 하반부 처리시간에 의해서 스케줄러는 사용자 프로세스에게 정상적으로 CPU를 할당해 줄 수 없는 이른바 “ 빼앗긴 시간 문제” 가 발생하게 된다. 본 논문에서는 이러한 문제를 해결하기 위해서, 하반부들이 사용할 수 있는 최대시간을 동적으로 계산하고, 처리시간을 제한하는 “하반부 스케줄링” 방범을 제안하고, 제안한 구조를 리눅스에서 구현하고 제안된 구조에 의해서 사용자 프로세스에게 할당된 CPU 시간을 안정화시킬 수 있음을 멀티미디어 응용을 사용한 실험을 통해서 보이고자 한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2013.01a
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• pp.9-12
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• 2013

리눅스 기반 안드로이드 단말에서는 CFS(Completely Fair scheduler)가 사용되고 있다. 그리고 CFS는 태스크의 nice값 조절을 통해서 응용프로그램의 CPU 점유율을 제어할 수 있다. 하지만 안드로이드를 업그레이드할 때마다 수많은 태스크의 nice값을 적절하게 맞추는 일은 매우 어려운 일이다. 이러한 문제를 해결하기 위하여 안드로이드 단말은 리눅스의 cgroup(control group)을 사용하여 태스크들을 그룹으로 나눈다. 고성능과 빠른 응답 특성이 필요한 태스크들을 apps 그룹에 할당하여 높은 CPU 점유율을 보장하고, 그렇지 않은 태스크들을 background 그룹에 할당한다. 하지만 안드로이드의 버전이 업그레이드 되면서 각 그룹에 속한 태스크들에도 변화가 생긴다. 그 결과 동일하게 제작된 태스크들의 CPU 점유율이 달라지게 되고 예기치 못한 성능 저하가 발생할 수 있다. 본 연구에서는 안드로이드 버전 향상에 따라 동종 태스크들이 이전 버전에서보다 성능이 하락하는 현상의 원인을 파악하였다. 아울러 분석과 실험을 통하여 태스크의 nice 값보다 그룹 스케줄링 메커니즘이 어떻게 태스크의 CPU 점유율을 결정 짓는지 규명하였다.

• Journal of Information Technology Applications and Management
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• v.22 no.2
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• pp.1-17
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• 2015

In this research, we develop and suggest branch and bound algorithms for a two-machine permutation flowshop scheduling problem with the objective of minimizing makespan. In this scheduling problem, after each job is operated on the machine 1 (first machine), the job has to start its second operation on machine 2 (second machine) within its corresponding limited waiting time. In addition, each job has its corresponding ready time at the machine 1. For this scheduling problem, we develop various dominance properties and three lower bounding schemes, which are used for the suggested branch and bound algorithm. In the results of computational tests, the branch and bound algorithms with dominance properties and lower bounding schemes, which are suggested in this paper, can give optimal solution within shorter CPU times than the branch and bound algorithms without those. Therefore, we can say that the suggested dominance properties and lower bounding schemes are efficient.

• International Journal of Computer Science & Network Security
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• v.22 no.10
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• pp.374-388
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• 2022

Cloud computing has been one of the most critical technology in the last few decades. It has been invented for several purposes as an example meeting the user requirements and is to satisfy the needs of the user in simple ways. Since cloud computing has been invented, it had followed the traditional approaches in elasticity, which is the key characteristic of cloud computing. Elasticity is that feature in cloud computing which is seeking to meet the needs of the user's with no interruption at run time. There are traditional approaches to do elasticity which have been conducted for several years and have been done with different modelling of mathematical. Even though mathematical modellings have done a forward step in meeting the user's needs, there is still a lack in the optimisation of elasticity. To optimise the elasticity in the cloud, it could be better to benefit of Machine Learning algorithms to predict upcoming workloads and assign them to the scheduling algorithm which would achieve an excellent provision of the cloud services and would improve the Quality of Service (QoS) and save power consumption. Therefore, this paper aims to investigate the use of machine learning techniques in order to predict the workload of Physical Hosts (PH) on the cloud and their energy consumption. The environment of the cloud will be the school of computing cloud testbed (SoC) which will host the experiments. The experiments will take on real applications with different behaviours, by changing workloads over time. The results of the experiments demonstrate that our machine learning techniques used in scheduling algorithm is able to predict the workload of physical hosts (CPU utilisation) and that would contribute to reducing power consumption by scheduling the upcoming virtual machines to the lowest CPU utilisation in the environment of physical hosts. Additionally, there are a number of tools, which are used and explored in this paper, such as the WEKA tool to train the real data to explore Machine learning algorithms and the Zabbix tool to monitor the power consumption before and after scheduling the virtual machines to physical hosts. Moreover, the methodology of the paper is the agile approach that helps us in achieving our solution and managing our paper effectively.

• Journal of Korea Multimedia Society
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• v.7 no.7
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• pp.886-895
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• 2004

In this paper, we propose the dynamic allocation scheme of the CPU bandwidth to efficiently integrate and schedule these tasks in the same system, where multimedia tasks and hard real-time tasks can coexist simultaneously. Hard real-time tasks are guaranteed based on worst case execution times, whereas multimedia tasks modeled as soft real-time tasks are served based on mean parameters. This paper describes a server-based allocation scheme for assigning the CPU resource to two types of tasks. Especially for MPEG video streams, we show how to dynamically control the fraction of the CPU bandwidth allocated to each multimedia task. The primary purpose of the proposed method is to minimize the mean tardiness of multimedia tasks while satisfying the timing constraints of hard real-time tasks present in the system. We showed through simulations that the tardiness experienced by multimedia tasks under the proposed allocation scheme is much smaller than that experienced by using other scheme.

• Journal of KIISE:Computer Systems and Theory
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• v.26 no.7
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• pp.788-812
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• 1999

본 논문에서는 범용 워크스테이션 환경하에서 수행되는 멀티미디어 응용프로그램(application)을 지원하기 위한 비례지분 방식의 CPU 스케줄러를 제시한다. 이러한 목적을 위하여 일반적 태스크의 지원을 위해 설계된 스트라이드 스케줄러를 확장한다. 멀티미디어 응용프로그램의 시간 요구사항을 명시하기 위하여 새로운 스케줄링 파라미터들을 도입한다. 비율조정기를 도입한 결과 스케줄링의 정확도의 오차는 O(1)로 감소하였다. 별도의 태스크 그룹을 설정하여 상대적 지분과 절대적 지분을 부여했다. 모의실험을 사용하여 스케줄러의 성능을 평가하였다. 그 결과, 제안된 스케줄러는 증가된 정확도와 적응성 및 유연성을 가짐을 알 수 있었다. Abstract This paper presents a proportional-share CPU scheduler which can support multimedia applications in a general-purpose workstation environment. For this purpose, we have extended the stride scheduler which is designed originally for conventional tasks. New scheduling parameters are introduced to specify timing requirements of multimedia applications. Through the use of the rate regulator, the accuracy error of the scheduling is reduced to O(1). Separate task groups are proposed to represent both relative shares and absolute shares. The proposed scheduler is evaluated using a simulation study. The results show that the proposed scheduler achieves improved accuracy and adaptability as well as flexibility.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.223-226
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• 2015

최근 클라우드를 지원하는 Xen 가상화 환경에서 HPC를 구현하는 서비스의 수가 증가하고 있다. 따라서 SMP기반의 병렬컴퓨팅 구현을 위한 표준 라이브러리인 OpenMP 연산효율의 중요성이 높아지고 있다. 본 논문에서는 Xen 가상화 기반 OpenMP 환경에서 CPU Pinning 적용 여부에 따라 다양한 태스크 스케줄링의 성능 변화를 측정하기 위한 실험을 수행하였다. 실험결과, CPU Pinning을 적용했을 시정적 스케줄링은 3.7%, 동적 스케줄링은 3.4%, 태스크 지시자 스케줄링은 3.8%의 성능 향상을 보였다. 이러한 결과는 Xen 가상화 환경에서 효율적인 병렬 컴퓨팅 기법 설계를 위한 방향을 제시한다.

• Journal of Korean Institute of Industrial Engineers
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• v.21 no.2
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• pp.207-216
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• 1995

Constructing a distributed management system has its own advantages in addressing the issue of implementing a quick responsive management system in dynamically changing environment of enterprise. We suggest a basic scheduling methodology applicable to a distributed production management system. A new concept of "flexible schedule" is introduced as a tool to accommodate dynamically changing situations of job shops. Then a search technique (referred to as CSP-CBA search) is presented to obtain such a schedule for the job shop scheduling problem, which is converted into a constraint satisfaction problem(CSP), by using the constraint based analysis(CBA). This approach is tested on more than 100 test problems. The results show that the suggested approach required shorter CPU time and solved more problems in given time than another fixed schedule method.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.07a
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• pp.7-8
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• 2019

In this paper, we applied the migration technique to real-time tasks that have relatively low criticality but still important to be dropped by the mixed-criticality scheduling algorithms. The proposed drop and migrate algorithm analyzes the schedulability by calculating CPU utilization and response time of using task migration. We provide analysis to guarantee the deadline of LO-tasks, by transforming the response time equation specified with migration time. The transformed response time equation was able to analyze the migration schedulability. This algorithm can be used with various mixed-criticality schedulers as a supplementary method. We expect this algorithm will be used for scheduling LO-tasks such as communication task that requires safety guarantee especially in platooning and autonomous driving by utilizing the advantages of multiple node connectivities.

• Journal of the Korea Society of Computer and Information
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• v.12 no.5
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• pp.49-56
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• 2007

This paper deals with grid job allocation and grid resource scheduling to provide a stable and quicker job processing service to grid users. In this paper, we proposed a fuzzy logic-based grid job scheduling model for an effective job scheduling in computational grid environment. The fuzzy logic-based grid job scheduling model measures resource efficiency of all grid resources by a fuzzy logic system based on diverse input parameters like CPU speed and network latency and divides resources into several groups by resource efficiency. And, the model allocates jobs to resources of a group with the highest resource efficiency. For performance evaluation, we implemented the fuzzy logic-based grid job scheduling model on the DEVS modeling and simulation environment and measured reduction rates of turnaround time, job loss, and communication messages in comparison with existing job scheduling models such as the random scheduling model and the MCT(Minimum Completion time) model. Experiment results that the proposed model is useful to improve the QoS of the grid job processing service.