• Journal of the Institute of Electronics Engineers of Korea CI
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• v.44 no.3
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• pp.14-22
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• 2007

Wireless sensor networks are composed of numerous sensor nodes and exchange or recharging of the battery is impossible after deployment. Thus, sonsor nodes must be very energy-efficient. As neighboring sensor nodes generally have the data of similar information, duplicate transmission of similar information is usual. To prevent energy wastes by duplicate transmissions, it is advantageous to organize sensors into clusters. The performance of clustering scheme is influenced by the cluster-head election method and the size or the number of clusters. Thus, we should optimize these factors to maximize the energy efficiency of the clustering scheme. In this paper, we propose a new energy consumption model for LEACH which is a well-known clustering protocol and determine the optimal number of clusters based on our model. Our model has accuracy over 80% compared with the simulation and is considerably superior to the existing model of LEACH.

• Journal of the Korea Society of Computer and Information
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• v.16 no.3
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• pp.121-129
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• 2011

One of the major challenges of minimum energy consumption for wireless sensor networks(WSN) environment. LEACH protocol is hierarchical routing protocol that obtains energy efficiency by using clustering. However, LEACH protocol in each round, because the new cluster configuration, cluster configuration, whenever the energy consumed shorten the life of the network. Therefore in this paper, the cluster is formed in WSN environment in early stage and the problems with energy waste have been solved by selecting C-node. In the initial round of proposed model uses 26 percent more than traditional LEACH energy consumption. However, as the round is ongoing, it has been proved by the network simulation tool that the waste of energy could be diminished up to 35%.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2009.06a
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• pp.397-401
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• 2009

On the crisis of international economy, the government is making an effort to seek economic growing motivation with the method of overcoming economic crisis and 'low carbon green growth'. Furthermore, to promote maritime vessel traffic service related inefficient energy wastage was revealed and eco-friendly alternative energy was accepted because of high price of oil in the beginning of 2008. In this situation, I'm going to discuss the possibility of eco-friendly energy system in maritime vessel traffic service with the way of cutting the budget and expansion of solar power generation system which was promoted to meet governmental 'energy saving plan for high price of oil'.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.1
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• pp.14-21
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• 2021

Green networking has become a issue to reduce energy wastes and CO2 emission by adding energy managing mechanism to wired data networks. Energy consumption of the overall wired data networks is driven by access networks, expect for end devices. However, on a global scale, it is more difficult to manage centrally energy, measure and model the real energy use and energy savings potential of the access networks. This paper presented the multiple linear regression model to predict energy consumption of wired access networks using supervised learning of machine learning with data collected by existing investigated materials, actual measured values and results of many models. In addition, this work optimized the performance of it by various experiments and predict energy consumption of wired access networks. The performance evaluation of the regression model was achieved by well-knowned evaluation metrics.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.2
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• pp.45-49
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• 2015

In this paper, we proposed not specturm sensing but also save energy without consume energy of secondary network that spectrum sensing of cognitive applied energy harvesting scheme. Algorithms of sensing and harvesting is determine active or idle of primary network, compares the amount of energy that is harvested by energy harvesting scheme with the threshold. If secondary network to send a message and primary network is active, by changing frequency to use the spectrum. Further, if secondary network have no message, continues energy harvest. Therefore, spectrum sensing applied energy harvesting scheme, energy of secondary network is remove waste and charge energy, efficiency and utilization of cognitive network can be increase.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.5
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• pp.123-129
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• 2014

This paper suggests that it provides a electricity management system for wasting electricity, from power demand growth environments. This Energy management system based on ICT(Information & Communication Technology) can control Smart Power Outlet connecting to this system with Web Browser and Android phone, anytime, anywhere. Through analysis of acquisition data from them, this proposed system can monitor and control power consumption efficiently. This system was organized mesh network of Smart Power Outlet, gateway by wireless Zigbee, and ESS(Energy Saving System) by TCP/IP beyond existing limit of communication distance and space.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.3
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• pp.73-76
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• 2015

In this paper, we propose energy harvesting apply to spectrum sensing. In this case, we can be spectrum sensing without consume energy. Algorithms of sensing and harvesting are determine active or idle of primary network, Compares with the threshold energy and the amount of energy that is harvested by energy harvesting scheme. If the secondary network want to send a message while the primary network is active, secondary users will change frequency to use the spectrum. Further, if the secondary network has not message, it will continues harvest energy. Therefore, spectrum sensing applied the energy harvesting method, energy of secondary network is remove waste and charge energy. So, efficiency and utilization of cognitive network can be increase.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.1A
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• pp.28-36
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• 2005

Wireless Sensor Networks are the technology, in which various applications such as surveillance and information gathering are possible in the uncontrollable area of human. And numerous studies are being processed for the application of ubiquitous network environment. One of major issues in sensor network is the research for prolonging the lifetime of nodes through the use of various algorithms, suggested in the mac and routing layer. In this paper, aiming at reducing energy waste, caused by redundant transmission and receipt message, we propose the mac protocol using active signal and analysis performance through simulation.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.144-146
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• 2022

차량 환경에서 발생하는 계산 집약적인 태스크가 증가하면서 모바일 엣지 컴퓨팅(MEC, Mobile Edge Computing)의 필요성이 높아지고 있다. 하지만 지상에 존재하는 MEC 서버는 출퇴근 시간과 같이 태스크가 일시적으로 급증하는 상황에 유동적으로 대처할 수 없으며, 이러한 상황을 대비하기 위해 지상 MEC 서버를 추가로 설치하는 것은 자원의 낭비를 불러온다. 최근 이 문제를 해결하기 위해 UAV(Unmanned Aerial Vehicle)기반 MEC 서버를 추가로 사용해 엣지 서비스를 제공하는 연구가 진행되고 있다. 그러나 UAV MEC 서버는 지상 MEC 서버와 달리 한정적인 배터리 용량으로 인해 서버 간 로드밸런싱을 통해 에너지 사용량을 최소화 하는 것이 필요하다. 본 논문에서는 UAV MEC 서버의 에너지 사용량을 고려한 마이그레이션 기법을 제안한다. 또한 GRU(Gated Recurrent Unit) 모델을 활용한 트래픽 예측을 바탕으로 한 마이그레이션을 통해 지연시간을 최소화할 수 있도록 한다. 제안 시스템의 성능을 평가하기 위해 MEC의 마이그레이션 시점을 결정하는 기준점와 차량의 밀도에 따라 실험을 진행하고, 서버의 로드 편차, UAV MEC 서버의 에너지 사용량 그리고 평균 지연 시간 측면에서 성능을 분석한다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.8
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• pp.928-941
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• 2016

Energy consumption of today's wired data networks is driven by access networks. Today, green networking has become a issue to reduce energy wastes and $CO_2$ emission by adding energy managing mechanism to wired data networks. However, energy consumption and environmental impacts of wired access networks are largely unknown. In addition, there is a lack of general and quantitative valuation basis of energy use of large-scale access networks and $CO_2$ emissions from them. This paper compared and analyzed limits of existing models estimating energy consumption of access networks and it proposed a model to estimate energy consumption of large-scale access networks by top-down approach. In addition, this work presented models that assess environmental(anti-greening) impacts of access networks using results from our models. The performance evaluation of the proposed models are achieved by comparing with previous models based on existing investigated materials and actual measured values in accordance with real cases.