• 제목/요약/키워드: CPU scheduling algorithm

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멀티 혼합 중요도 시스템에서 태스크 마이그레이션의 스케줄가능성 분석 (Schedulability Analysis for Task Migration under Multiple Mixed-Criticality Systems)

  • 백전성;강경태
    • 한국컴퓨터정보학회:학술대회논문집
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    • 한국컴퓨터정보학회 2019년도 제60차 하계학술대회논문집 27권2호
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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.

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이동망의 채널할당과 작업 스케줄링 관련 모델 및 성능분석 (Performance of Job scheduling Model And Channel Allocation of Cellular Network)

  • 손동철;김동현;류충상
    • 한국전자통신학회논문지
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    • 제3권1호
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    • pp.26-30
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    • 2008
  • CDMA 이동망 환경에서는 한정된 자원을 효율적으로 사용하여 멀티미디어 서비스 요구에 따른 무선 트래픽 채널을 할당하는 기법은 무선이라는 특수 환경으로 인해 제약을 받을 수밖에 없다. 이동망의 기지국의 경우 여러 무선 가입자 보드로부터 요구되는 서비스별 트래픽 요구에 대한 채널 할당과 이에 대한 메인보드에서 처리해야 하는 작업 스케줄링은 무선과 CPU라는 서로 다른 환경을 잘 매핑하는 과제를 안고 있다. 본 논문에서는 음성과 데이터 호를 동시에 서비스하는 셀룰러 시스템에서 멀티미디어 서비스 트래픽 특성을 고려한 주파수할당과 작업 스케줄링이라는 두 가지 요소를 접목할 때 적합한 작업 스케줄링 방식을 제안한다.

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FlashEDF: An EDF-style Scheduling Scheme for Serving Real-time I/O Requests in Flash Storage

  • Lim, Seong-Chae
    • International Journal of Internet, Broadcasting and Communication
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    • 제10권3호
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    • pp.26-34
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    • 2018
  • In this paper, we propose a scheduling scheme that can efficiently serve I/O requests having deadlines in flash storage. The I/O requests with deadlines, namely, real-time requests, are assumed to be issued for streaming services of continuous media. Since a Web-based streaming server commonly supports downloads of HTMLs or images, we also aim to quickly process non-real-time I/O requests, together with real-time ones. For this purpose, we adopt the well-known rate-reservation EDF (RR-EDF) algorithm for determining scheduling priorities among mixed I/O requests. In fact, for the use of an EDF-style algorithm, overhead of task's switching should be low and predictable, as with its application of CPU scheduling. In other words, the EDF algorithm is inherently unsuitable for scheduling I/O requests in HDD storage because of highly varying latency times of HDD. Unlike HDD, time for reading a block in flash storage is almost uniform with respect to its physical location. This is because flash storage has no mechanical component, differently from HDD. By capitalizing on this uniform block read time, we compute bandwidth utilization rates of real-time requests from streams. Then, the RR-EDF algorithm is applied for determining how much storage bandwidth can be assigned to non-real-time requests, while meeting deadlines of real-time requests. From this, we can improve the service times of non-real-time requests, which are issued for downloads of static files. Because the proposed scheme can expand flexibly the scheduling periods of streams, it can provide a full usage of slack times, thereby improving the overall throughput of flash storage significantly.

실시간 운영체제를 위한 프로세스의 효율적인 스케줄링 알고리즘 (Effective Scheduling) Algorithm of Process for Real Time Operating System)

  • 정선아;이지영
    • 한국정보과학회:학술대회논문집
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    • 한국정보과학회 2002년도 가을 학술발표논문집 Vol.29 No.2 (1)
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    • pp.373-375
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    • 2002
  • 본 논문은 실시간 운영체제에서 프로세스의 효율적인 관리를 위한 스케줄링 알고리즘을 제안한다. 따라서 CPU의 활용도를 높이고 스케줄링 시간과 인터럽트 시간을 줄임으로서 자원을 효율적으로 관리할 수 있다. 본 논문에서 제안하는 방법으로는 다중 큐에 PIT(Process Information Table)를 두어 각각의 큐에 프로세스가 들어오면 우선순위에 따라 CPU를 할당하는 방법이다. 기존의 다중 큐와는 달리 우선순위 프로세스를 보다 정확하고 빨리 찾아내어 외부 또는 내부의 인터럽트에 응답 할 수 있게 하였다. 또한 우선순위에 밀려 실행하지 못하는 프로세스는 일정 시간이 경과하면 CPU를 선점할 수 있다. 그러므로 CPU는 활용도가 높아지고 유휴 시간은 짧아지게 된다. 본 논문은 일반 펜티엄 PC에서 실험하였으며 현재 사용되는 RTOS(VxWorks, QNX)와 비교하여 다소 우수함을 보였다.

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Exploring Support Vector Machine Learning for Cloud Computing Workload Prediction

  • ALOUFI, OMAR
    • International Journal of Computer Science & Network Security
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    • 제22권10호
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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.

Optimization Algorithms for a Two-Machine Permutation Flowshop with Limited Waiting Times Constraint and Ready Times of Jobs

  • Choi, Seong-Woo
    • Journal of Information Technology Applications and Management
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    • 제22권2호
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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.

큐 분리 및 패킷 분할을 이용한 효율적인 점보패킷 스케쥴링 방법 (Effective Scheduling Algorithm using Queue Separation and Packet Segmentation for Jumbo Packets)

  • 윤빈영;고남석;김환우
    • 한국통신학회논문지
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    • 제28권9A호
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    • pp.663-668
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    • 2003
  • 고속 네트워킹 기술 발전과 더불어 대용량의 데이터 처리는 컴퓨터의 CPU 사이클을 많이 소모하므로 컴퓨터의 성능을 저하시킨다. 따라서 고속의 네트워크 환경에서 컴퓨터 성능을 향상시키기 위해서는 데이터 처리로 소모되는 컴퓨터의 CPU 사이클을 최대한 억제해야 한다. 이러한 방법 중의 하나가 점보그램과 점보프레임 같은 패킷 길이가 긴 점보패킷을 사용하는 것이다. 그러나 점보패킷이 전달 지연에 민감한 VoIP 패킷들과 동시에 처리되는 경우 이 들 서비스에 질적인 저하를 가져올 수 있다. 뿐만 아니라, 심각한 패킷 손실이 발생된다. 본 고에서는 점보패킷을 수용하는 경우에도 기존의 일반 패킷 전단 지연 및 손실을 거의 동일하게 유지시킬 수 있는 스케쥴링 방법을 제안한다.

저지연 서비스를 위한 Multi-access Edge Computing 스케줄러 (Multi-access Edge Computing Scheduler for Low Latency Services)

  • 김태현;김태영;진성근
    • 대한임베디드공학회논문지
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    • 제15권6호
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    • pp.299-305
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    • 2020
  • We have developed a scheduler that additionally consider network performance by extending the Kubernetes developed to manage lots of containers in cloud computing nodes. The network delay adapt characteristics of the compute nodes were learned during server operation and the learned results were utilized to develop placement algorithm by considering the existing measurement units, CPU, memory, and volume together, and it was confirmed that the low delay network service was provided through placement algorithm.

가상화 클라우드 데이터센터에서 가상 머신 간의 균등한 성능 보장을 위한 제어 알고리즘 (Control Algorithm for Virtual Machine-Level Fairness in Virtualized Cloud Data center)

  • 김환태;김황남
    • 한국통신학회논문지
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    • 제38C권6호
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    • pp.512-520
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    • 2013
  • 본 논문은 가상 머신 기반의 클라우드 데이터센터에서 가상 머신의 CPU 스케줄링으로 인해 발생할 수 있는 네트워크 불평등 현상을 해결하는 가상머신 수준의 제어 알고리즘을 제안한다. 이를 위해 이기종 호스트들로 구성된 클라우드 데이터 센터 테스트베드를 구축하고, 가상 머신간의 네트워크 불평등 현상이 발생함을 실험적으로 보인다. 그리고 이를 해결할 수 있는 PID 제어 기법 기반의 가상 머신 네트워크 성능 보장 제어 알고리즘을 설계하고, 이를 실제 시스템에 구현하기 위한 방안을 설명한다. 실제 테스트베드에 제안하는 알고리즘을 구현하여 알고리즘 동작 결과를 분석한다.

최소 종료시간 사격 스케줄을 위한 분지계획법 알고리즘 연구 (A Branch-and-Bound Algorithm to Minimize the Makespan in a Fire Scheduling Problem)

  • 차영호;방준영
    • 산업경영시스템학회지
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    • 제38권4호
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    • pp.132-141
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    • 2015
  • We focus on the fire scheduling problem (FSP), the problem of determining the sequence of targets to be fired at, for the objective of minimizing makespan to achieve tactical goals. In this paper, we assume that there are m available weapons to fire at n targets (> m) and the weapons are already allocated to targets. One weapon or multiple weapons can fire at one target and these fire operations should start simultaneously while the finish time of them may be different. We develop several dominance properties and a lower bound for the problem, and suggest a branch and bound algorithm implementing them. Also, In addition, heuristic algorithms that can be used for obtaining an initial upper bound in the B&B algorithm and for obtaining good solutions in a short time were developed. Computational experiments are performed on randomly generated test problems and results show that the suggested algorithm solves problems of a medium size in a reasonable amount of computation time. The proposed lower bound, the dominance properties, and the heuristics for upper bound are tested in B&B respectively, and the result showed that lower bound is effective to fathoming nodes and the dominance properties and heuristics also worked well. Also, it is showed that the CPU time required by this algorithm increases rapidly as the problem size increases. Therefore, the suggested B&B algorithm would be limited to solve large size problems. However, the employed heuristic algorithms can be effectively used in the B&B algorithm and can give good solutions for large problems within a few seconds.