• Title/Summary/Keyword: CPU Management

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A Deadline_driven CPU Power Consumption Management Scheme of the TMO-eCos Real-Time Embedded OS (실시간 임베디드 운영체제 TMO-eCos의 데드라인 기반 CPU 소비 전력 관리)

  • Park, Jeong-Hwa;Kim, Jung-Guk
    • Journal of KIISE:Computing Practices and Letters
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    • v.15 no.4
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    • pp.304-308
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    • 2009
  • This paper presents the deadline driven CPU-Power management scheme for the Real-Time Embedded OS: named TMO-eCos. It used the scheduling scenarios generated by a task serialization technique for hard real- time TMO system. The serializer does a off-line analysis at design time with period, deadline and WCET of periodic tasks. Finally, TMO-eCos kernel controls the CPU speed to save the power consumption under the condition that periodic tasks do not violate deadlines. As a result, the system shows a reasonable amount of power saving. This paper presents all of these processes and test results.

The CPU power management technique in the Mobile Embedded System (Mobile 임베디드 시스템의 CPU 소모전력 관리 기법)

  • Kim, Wha-Young;Kim, Young-Kil
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.13 no.1
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    • pp.170-176
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    • 2009
  • The efficiently power management is an important requirement traditionally in the mobile communication system which uses battery as their power source. Especially, it has been emphasized in the most devices, which has to provide high performance and various functions with an extended operating time. In this article, the adaptive power management technique for the core CPU unit in Embedded systems used widely for the mobile system thanks to its advantage on power consumption and physical size, is proposed.

Evaluating Power Consumption and Real-time Performance of Android CPU Governors (안드로이드 CPU 거버너의 전력 소비 및 실시간 성능 평가)

  • Tak, Sungwoo
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.20 no.12
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    • pp.2401-2409
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    • 2016
  • Android CPU governors exploit the DVFS (Dynamic Voltage Frequency Scaling) technique. The DVFS is a power management technique where the CPU operating frequency is decreased to allow a corresponding reduction in the CPU supply voltage. The power consumed by a CPU is approximately proportional to the square of the CPU supply voltage. Therefore, lower CPU operating frequency allows the CPU supply voltage to be lowered. This helps to reduce the CPU power consumption. However, lower CPU operating frequency increases a task's execution time. Such an increase in the task's execution time makes the task's response time longer and makes the task's deadline miss occur. This finally leads to degrading the quality of service provided by the task. In this paper, we evaluated the performance of Android CPU governors in terms of the power consumption, tasks's response time and deadline miss ratio.

Twowheeled Motor Vehicle License Plate Recognition Algorithm using CPU based Deep Learning Convolutional Neural Network (CPU 기반의 딥러닝 컨볼루션 신경망을 이용한 이륜 차량 번호판 인식 알고리즘)

  • Kim Jinho
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.19 no.4
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    • pp.127-136
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    • 2023
  • Many research results on the traffic enforcement of illegal driving of twowheeled motor vehicles using license plate recognition are introduced. Deep learning convolutional neural networks can be used for character and word recognition of license plates because of better generalization capability compared to traditional Backpropagation neural networks. In the plates of twowheeled motor vehicles, the interdependent government and city words are included. If we implement the mutually independent word recognizers using error correction rules for two word recognition results, efficient license plate recognition results can be derived. The CPU based convolutional neural network without library under real time processing has an advantage of low cost real application compared to GPU based convolutional neural network with library. In this paper twowheeled motor vehicle license plate recognition algorithm is introduced using CPU based deep-learning convolutional neural network. The experimental results show that the proposed plate recognizer has 96.2% success rate for outdoor twowheeled motor vehicle images in real time.

An Integrated Power Management Framework for WiFi-based Mobile Embedded Systems (WiFi기반 모바일 임베디드 시스템을 위한 통합 전력 제어 기법)

  • Min Jung-Hi;Cha Ho-Jung
    • Journal of KIISE:Computer Systems and Theory
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    • v.33 no.9
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    • pp.658-665
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    • 2006
  • In these days, the demand of users to extend available period of mobile systems is increased according as the functions of mobile systems have been varied and the use of multimedia application has been increased. This paper proposes an integrated power management framework that considers executed workload types for effective energy management. The conventional methods use DVFS technique for CPU and DPM technique for WNIC separately or simply combine them based on the assumption that they are orthogonal one another. However, the proposed mechanism determines the kind of workload under analysis of the characteristics of workloads incoming through a WNIC. The proposed method can reduce energy consumption of system level effectively by controlling CPU and WNIC to proper power mode based on analyzed characteristics of workload. The experimental result shows the proposed method reduces energy consumption by 9% for BE (Best Effort) workload, CBR (Constant Bit Rate) workload, and Interactive workload on average and by 16% to maximum when compared with the conventional methods which simply combine DVFS technique for CPU and DPM technique for WNIC.

A Review on the CPU Scheduling Algorithms: Comparative Study

  • Ali, Shahad M.;Alshahrani, Razan F.;Hadadi, Amjad H.;Alghamdi, Tahany A.;Almuhsin, Fatimah H.;El-Sharawy, Enas E.
    • International Journal of Computer Science & Network Security
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    • v.21 no.1
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    • pp.19-26
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    • 2021
  • CPU is considered the main and most important resource in the computer system. The CPU scheduling is defined as a procedure that determines which process will enter the CPU to be executed, and another process will be waiting for its turn to be performed. CPU management scheduling algorithms are the major service in the operating systems that fulfill the maximum utilization of the CPU. This article aims to review the studies on the CPU scheduling algorithms towards comparing which is the best algorithm. After we conducted a review of the Round Robin, Shortest Job First, First Come First Served, and Priority algorithms, we found that several researchers have suggested various ways to improve CPU optimization criteria through different algorithms to improve the waiting time, response time, and turnaround time but there is no algorithm is better in all criteria.

Real-Time Scheduling Method to assign Virtual CPU in the Multocore Mobile Virtualization System (멀티코아 모바일 가상화 시스템에서 가상 CPU 할당 실시간 스케줄링 방법)

  • Kang, Yongho;Keum, Kimoon;Kim, Seongjong;Jin, Kwangyoun;Kim, Jooman
    • Journal of Digital Convergence
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    • v.12 no.3
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    • pp.227-235
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    • 2014
  • Mobile virtualization is an approach to mobile device management in which two virtual platforms are installed on a single wireless device. A smartphone, a single wireless device, might have one virtual environment for business use and one for personal use. Mobile virtualization might also allow one device to run two different operating systems, allowing the same phone to run both RTOS and Android apps. In this paper, we propose the techniques to virtualize the cores of a multicore, allowing the reassign any number of vCPUs that are exposed to a OS to any subset of the pCPUs. And then we also propose the real-time scheduling method to assigning the vCPUs to the pCPU. Suggested technology in this paper solves problem that increases time of real-time process when interrupt are handled, and is able more to fast processing than previous algorithm.

Optimizing LRU Lock Management in the Linux Kernel for Improving Parallel Write Throughout in Many-Core CPU Systems (매니코어 CPU 시스템의 병렬 쓰기 성능 향상을 위한 리눅스 커널의 LRU 관리 최적화 기법)

  • Eun-Kyu Byun;Gibeom Gu;Kwang-Jin Oh;Jiwoo Bang
    • KIPS Transactions on Computer and Communication Systems
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    • v.12 no.7
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    • pp.209-216
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    • 2023
  • Modern HPC systems are equipped with many-core CPUs with dozens of cores. When performing parallel I/O in such a system, there is a limit to scalability due to the problem of the LRU lock management policy of the Linux system. The study proposes an improved FinerLRU to solve this problem. Our new FinerLRU improves the parallel write performance of file systems using the buffer cache through granular lock management by increasing the number of LRU locks upto the maximum number of cores. The proposed method was implemented in Linux 5.18.11, and the performance was measured on two types of CPUs, Intel Icelake Xeon and Intel Knights landing, with different characteristics, and it was found that a performance improvement of about two times can be obtained in both types of systems.

A Dynamic Power Management System for Multiple Client in Cloud Computing Environment (클라우드 환경에서 다중 클라이언트를 위한 동적 전원관리 시스템)

  • Cha, Seung-Min;Lee, Bong-Hwan
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.16 no.2
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    • pp.213-221
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    • 2012
  • In this paper, a dynamic power management system is proposed to reduce energy consumption for multiple clients in cloud computing environments. The proposed system monitors both keyboard and mouse input from the user, available memory, and CPU usage in the virtual machine. If the system detects no keyboard and mouse input for a certain amount of time and both available memory and CPU usage reach predefined threshold value, the manager in the virtual machine orders the client to shutdown the client machine, which results in significant power save. The developed system is applied to the real university computer lab and the performance of the system is evaluated.