• 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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.761-764
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• 2010

Interest in vehicle infotainment system, that provides both entertainment of driving and information for safe and convenient driving, has been recently increased. MOST is defined as the network transmitting high-bandwidth infortainment data to vehicle, and it has been standardized as MOST150. In this research, dynamic behavior method that deals with roles and functions of each devices connected to MOST150 Network, and Power Management Method was studied. MOST Network consists of a master device, including function block 'NetworkMaster', and all other devices called slave devices. The purpose of this study is to apply the analysis of the methods of operating and power management based on condition of master device and slave devices on MOST150 network to the future development of MOST150 devices.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.11a
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• pp.546-548
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• 2011

컴퓨터 실습실에서 사용되고 있는 씬 클라이언트 PC는 개인별로 할당된 것이 아니라 다수의 사용자들이 공유하기 때문에 씬 클라이언트 PC를 관리하기 위한 별도의 관리시스템(Management System)이 필요하다. 본 논문에서는 컴퓨터 실습실 환경에서 가상머신에 원격으로 접속된 씬 클라이언트 PC의 전원관리를 효과적으로 할 수 있는 방법을 제안한다. 사용자가 이용하는 씬 클라이언트 PC에 대해 일정시간 동안 키보드/마우스의 입력이 없으면 해당 씬 클라이언트 PC로 메시지를 전송하여 사용 여부를 확인하고 해당 사용자로부터 아무런 응답이 없을 경우 씬 클라이언트 PC를 Shutdown 한다. 이러한 관리 방법은 사용되지 않는 씬 클라이언트 PC에 대해 불필요하게 낭비되는 전력을 줄일 수 있어 효율적으로 컴퓨터 실습실을 운영할 수 있을 것으로 예상된다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.7B
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• pp.411-421
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• 2007

It is well known that the biggest problem of wireless sensor networks is power conservation. There have been two major approaches to efficiently use energy in wireless sensor networks. One is to use a dynamic power management scheme and the other is to use energy efficient protocols. In the former, the power manager is responsible for managing the proper power state of CPU and each I/O with respect to the events, but the power manager does not concern about the internal operation of the underlying network protocols. Thus such conventional power managers can waste unpredicted power during communication period. On the other hand, the energy efficient protocols are just focused on the power saving operation of the radio PHY. In this paper, we introduce an energy-efficient power saving mechanism that can significantly reduce unwanted power consumption of wireless sensor nodes through the communication event-driven power management. We show that our scheme improves the energy conservation in the entire network through simulations.

• KIPS Transactions on Computer and Communication Systems
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• v.4 no.11
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• pp.369-382
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• 2015

Energy aware server clusters aim to reduce power consumption at maximum while keeping QoS(quality of service) compared to energy non-aware server clusters. They adjust the power mode of each server in a fixed or variable time interval to activate only the minimum number of servers needed to handle current user requests. Previous studies on energy aware server cluster put efforts to reduce power consumption or heat dissipation, but they do not consider energy efficiency well. In this paper, we propose an energy efficient cluster management method to improve not only performance per watt but also QoS of the existing server power mode control method based on autonomous learning. Our proposed method is to adjust server power mode based on a hybrid approach of autonomous learning method with multi level thresholds and power consumption prediction method. Autonomous learning method with multi level thresholds is applied under normal load situation whereas power consumption prediction method is applied under abnormal load situation. The decision on whether current load is normal or abnormal depends on the ratio of the number of current user requests over the average number of user requests during recent past few minutes. Also, a dynamic shutdown method is additionally applied to shorten the time delay to make servers off. We performed experiments with a cluster of 16 servers using three different kinds of load patterns. The multi-threshold based learning method with prediction and dynamic shutdown shows the best result in terms of normalized QoS and performance per watt (valid responses). For banking load pattern, real load pattern, and virtual load pattern, the numbers of good response per watt in the proposed method increase by 1.66%, 2.9% and 3.84%, respectively, whereas QoS in the proposed method increase by 0.45%, 1.33% and 8.82%, respectively, compared to those in the existing autonomous learning method with single level threshold.

• 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.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.1119-1120
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• 2008

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 recent 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 processor unit in embedded systems used widely for the mobile system thanks to its advantage on power consumption and physical size, is proposed.

• The Journal of the Korea Contents Association
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• v.6 no.12
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• pp.71-79
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• 2006

Recently, embedded systems like mobile and portable devices are quickly disseminated around the world. Since these.devices need more computation power as the applications become gradually complicated, the bettery lifetime becomes the most serious constraints. So research efforts have been focused on reducing the power consumption, resulting in producing devices with low-power H/W and S/W components. In this paper, we propose a low-power Java API set using the dynamic power management (DPM) scheme in the J2ME Java Platform on the real-time operating system UbiFOSTM and show that we could save energy up to 30% through experiments using the API set.

• Proceedings of the Korean Information Science Society Conference
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• 2004.10c
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• pp.688-690
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• 2004

최근 무선 접속망의 급속한 발전으로 이동 통신 환경에서 인터넷 서비스 제공에 대한 요구가 늘어남에 따라, IP기반의 이동성 지원과 마이크로 이동성에 따른 위치관리 트래픽을 줄일 수 있도록 해주는 HMIPv6 프로토콜이 제안되었다. HMIPv6에 페이징을 적용함으로서 MN의 위치등록에 필요한 시그널링 및 위치정보 데이터베이스의 갱신을 위한 처리와 단말의 전원 소모를 줄일 수 있다. 본 논문에서는 각기 다른 특성을 갖는 MN들에 하나의 동일한 페이징 영역이 적용되는 것이 아닌, 각 MN의 특성을 고려하여 각각의 MN에 적합한 최적의 페이징 영역이 설정되는 HMIPv6 환경에서의 동적 페이징 영역 설정 기법(DP-HMIPv6)을 제안한다.

• KIISE Transactions on Computing Practices
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• v.22 no.6
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• pp.296-301
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• 2016

Object-based storage is an efficient storage solution that can handle unstructured data and shows better security and scalability than traditional block-based storage. However, in terms of power management, Object-based storage writes multiple copies in storage cluster, hence many servers consume unnecessary power in idle state. In order to resolve this problem, it is necessary to apply power management strategy by adjusting power mode of servers in idle state according to their workloads. In this paper, we proposed a new dynamic power management (DPM) method to transform power mode of storage servers dynamically according to workload information sent from proxy server. The experimental result shows that the proposed power management technic reduces total power consumption by 12% in the OpenStack based Swift object storage.