• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.2
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• pp.27-37
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• 2009

Sensor nodes forming a sensor network have limited energy capacity such as small batteries and when these nodes are placed in a specific field, it is important to research minimizing sensor nodes' energy consumption because of difficulty in supplying additional energy for the sensor nodes. Clustering has been in the limelight as one of efficient techniques to reduce sensor nodes' energy consumption in sensor networks. However, energy saving results can vary greatly depending on election of cluster heads, the number and size of clusters and the distance among the sensor nodes. /This research has an aim to find the optimal set of clusters which can reduce sensor nodes' energy consumption. We use a Genetic Algorithm(GA), a stochastic search technique used in computing, to find optimal solutions. GA performs searching through evolution processes to find optimal clusters in terms of energy efficiency. Our results show that GA is more efficient than LEACH which is a clustering algorithm without evolution processes. The two-dimensional GA (2D-GA) proposed in this research can perform more efficient gene evolution than one-dimensional GA(1D-GA)by giving unique location information to each node existing in chromosomes. As a result, the 2D-GA can find rapidly and effectively optimal clusters to maximize lifetime of the sensor networks.

• KIPS Transactions on Computer and Communication Systems
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• v.4 no.6
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• pp.185-196
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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 let only the minimum number of servers needed to handle current user requests ON. Previous studies on energy aware server cluster put efforts to reduce power consumption further or to keep QoS, but they do not consider energy efficiency well. In this paper, we propose an energy efficient cluster management based on autonomous learning for energy aware server clusters. Using parameters optimized through autonomous learning, our method adjusts server power mode to achieve maximum performance with respect to power consumption. Our method repeats the following procedure for adjusting the power modes of servers. Firstly, according to the current load and traffic pattern, it classifies current workload pattern type in a predetermined way. Secondly, it searches learning table to check whether learning has been performed for the classified workload pattern type in the past. If yes, it uses the already-stored parameters. Otherwise, it performs learning for the classified workload pattern type to find the best parameters in terms of energy efficiency and stores the optimized parameters. Thirdly, it adjusts server power mode with the parameters. We implemented the proposed method and performed experiments with a cluster of 16 servers using three different kinds of load patterns. Experimental results show that the proposed method is better than the existing methods in terms of energy efficiency: the numbers of good response per unit power consumed in the proposed method are 99.8%, 107.5% and 141.8% of those in the existing static method, 102.0%, 107.0% and 106.8% of those in the existing prediction method for banking load pattern, real load pattern, and virtual load pattern, respectively.

• The Transactions of the Korean Institute of Power Electronics
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• v.4 no.1
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• pp.43-49
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• 1999

We propose a nonlinear feedback controller that can control the induction motors with high dynamic performance and high power efficiency by means of decoupling of motor speed and rotor flux. The nonlinear feedback controller needs the information on some motor parameters. New recursive adaptation algorithms for rotor resistance and mutual inductance which can be applied to our nonlinear feedback controller are also presented in this paper. The recursive adaptation algorithms make the estimated values of rotor resistance and mutual inductance track their real values. Some simulation and experimental results show that the adaptation algorithms are robust against the variation of stator resistance and stator inductance.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.938-940
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• 2012

전세계적으로 친환경, 에너지 절약과 맞물려 LED조명에 대한 관심이 증대되고 있다. 특히 우리나라는 삼면이 바다와 인접해 해안 항만 환경에 대한 관심이 높고, 해안산책로, 공원 등이 늘어나면서 LED 보안등에 대한 수요가 늘고 있는 추세이다. LED보안등의 수요가 늘어나면서 보안등의 주목적인 범죄예방에 대비하면서 에너지를 절감할 수 있는 시스템에 대한 관심이 증대되고 있다. 최근의 조명제어 시스템은 단순히 보행자 유무만을 인식하여 조명의 밝기를 제어하는 시스템이 대다수이며, 비, 바람, 안개, 해무 등의 실시간 변화가 잦은 해안환경에 대한 고려는 부족하다. 따라서, 본 논문에서는 보행자 유무와 비, 안개, 해무 등의 환경적 정보를 융합하여 보안등의 밝기를 통합 제어할 수 있는 스마트 제어 시스템을 설계하고자 한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2017.07a
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• pp.168-169
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• 2017

중앙 전력과 단절된 독립형 마이크로그리드는 발전된 신재생 에너지를 저장하는 ESS의 효율적인 운영을 통해 블랙아웃을 방지하고 디젤 발전기의 발전 비용을 최소화하는 것이 필요하다. 본 논문에서는 기상 정보를 이용하여 신재생 에너지 발전량을 예측하고, 최적화 알고리즘을 이용해 생성된 후보 계획의 평가 시 ESS의 SOC를 유지하지 못하는 경우 페널티를 부여함으로써 신재생 발전량 예측의 오류에 대비하였다. 시뮬레이션 실험을 통해 제안하는 SOC 유지를 고려한 운영 계획 최적화 방안이 기존의 예측 제어 기반 최적화 방안에 비해 블랙아웃을 방지하면서도 디젤 발전 비용을 절감할 수 있음을 확인하였다.

• Proceedings of the Korean Information Science Society Conference
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• 2006.10c
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• pp.93-97
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• 2006

센서 네트워크에서 질의 처리 기술은 통신 비용을 절감하고 신뢰성을 향상하고 에너지 효율성을 향상시키는데 목적을 두고 있다. 현재 에너지의 효율성을 위해서 센서 노드가 수행하는 질의를 최적화하여 전력 손실을 줄이고자 하는 연구가 활발하게 수행 중이다. 본 논문에서는 실체 뷰와 인덱싱 뷰를 이용하여 센서 네트워크에 맞는 효율적인 새로운 센싱 뷰라는 기법을 제안한다. 제안하는 질의 처리 알고리즘은 실체 뷰와 인덱싱 뷰의 개념을 바탕으로 기존의 분산 데이터베이스의 질의 처리 방법을 센서 네트워크에 적용하였다. 제안된 센싱 뷰 알고리즘은 센싱 뷰를 싱크 노드에 위치시킴으로서 센서 노드와의 통신 횟수를 최대한 줄임으로서 통신 비용과 에너지의 소모량을 줄일 수 있었다. 성능은 시뮬레이션을 통해서 평균적으로 약 30%정도의 성능 향상 효과를 보였다.

• Journal of Internet Computing and Services
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• v.9 no.4
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• pp.11-20
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• 2008

IEEE 802.16e has adopted sleep mode to minimize energy consumption of mobile nodes with high speed mobility. If the Base Station (BS) has no data to be sent to a Mobile Subscriber Station (MSS) at the instant of ending sleep window of the MSS, the MSS increases its sleep window interval by double until the window interval reaches to the maximum sleep window interval. Thus, during the operation of sleep mode, MSS repeatedly performs switch on/off action until there exist frames to be received from BS. The switch on/off operation significantly consumes energy of MSS. To effectively deal with the energy of the MSS, this paper proposes an algorithm which decides the minimum sleep window interval that will be used in next sleep mode based on the current sleep window interval. We evaluate the performance of IEEE 802.16e sleep mode algorithm and our proposed algorithm in terms of energy consumption and blocking probability. Compared with the current sleep mode algorithm used in IEEE 802.16e, the proposed algorithm decreases the energy consumption by about 30% without increasing blocking probability.

• Journal of Advanced Navigation Technology
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• v.22 no.6
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• pp.545-550
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• 2018

Ministry of Oceans and Fisheries declared action plan for the electric fishing gear using real name in order to prevent overusing the fishing gear and to reduce discarded fishing gear. It is needed for a technique that can efficiently transmit the information including the type and location of the fishing gear and the user's real name to the fishing boat and the control center using IoT-based communication. The marine tracker buoy system, which is placed on the water for a long time, transmit the position data and the state data of the buoys to the control center in the ground by using NB-IoT channels. In this paper, we propose the algorithm for the low-power operation of the marine tracker buoy system is proposed and test results of current consumption in the marine tracker buoy system with the proposed algorithm is investigated.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.4
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• pp.370-379
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• 2014

Recently, the interest in optical network with multifiber link is continuing to rise since the network traffic has been growing exponentially. However, growing traffic in network leads to increasing the energy consumption of the network equipment. In this paper, we propose a dynamic routing and wavelength assignment (RWA) algorithm based on V-like cost function and layered graph to improve energy efficiency in IP over WDM network with multifiber link. The V-like cost function is used to decide the fiber cost according to the number of used wavelengths. The layered graph with multifiber link is used to select the energy efficient route and wavelength. The proposed RWA algorithm is compared and analyzed with conventional algorithm in view of average power consumption and blocking probability through OPNET modeler.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.4
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• pp.932-938
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• 2017

This paper presents the structure of an energy management system for distributed energy resources of a grid-connected microgrid. The energy management system of a grid-connected microgrid collects information of the microgrid such as the status of distributed energy resources and the time varying pricing plan through various protocols. The energy management system performs forecasting and optimization based on the collected information. It derives the operation schedule of distributed energy resources to reduce the microgrid electricity bill. In order to achieve optimal operation, the energy management system should include an optimal scheduling algorithm and a protocol that transfers the derived schedule to distributed energy resources. The energy management system operates as a rolling horizon controller in order to reduce the effect of a prediction error. Derived control schedules are transmitted to the distributed energy resources in real time through the international standard communication protocol.