• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.10
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• pp.2054-2061
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• 2015

Biologically inspired modeling techniques have received considerable attention for their robustness, scalability, and adaptability with simple local interactions and limited information. Among these modeling techniques, Gene Regulatory Networks (GRNs) play a central role in understanding natural evolution and the development of biological organisms from cells. In this paper, we apply GRN principles to the WSN system and propose a new GRN model for decentralized node scheduling design to achieve energy balancing while meeting delay requirements. Through this scheme, each sensor node schedules its state autonomously in response to gene expression and protein concentration, which are controlled by the proposed GRN-inspired node scheduling model. Simulation results indicate that the proposed scheme achieves superior performance with energy balancing as well as desirable delay compared with other well-known schemes.

• Environmental and Resource Economics Review
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• v.12 no.2
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• pp.245-274
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• 2003

This paper analyzes the economic and environmental impacts of domestic policy to reduce greenhouse gas emissions by focusing on carbon tax, domestic emissions trading and the mixture of these policies. By utilizing a dynamic CGE model, KORTEM, this study shows that the economic cost under carbon tax is projected to be higher than that under emission trading. It is because under carbon tax scheme each emitter in economy must meet its emission target regardless of the abatement cost. On the other hand, emission trading allows emitters to reduce the marginal cost of abatement through trading of emission permits. In designing policy portfolio to address the climate change problem in Korea, therefore, this paper proposes the introduction of domestic emission trading scheme as the main domestic policy Instrument.

• Land and Housing Review
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• v.13 no.3
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• pp.107-113
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• 2022

With increasing airtight building construction aimed at reducing energy consumption, indoor relative humidity is increasing which can lead to condensation and moisture damage in multi-family residential buildings. This has led to increased implementation of mechanical ventilation to control indoor moisture. However mechanical ventilation systems consume additional energy and generate noise. As this leads to occupant discomfort, it is necessary to select a ventilation system that addresses the energy and noise issues. This research measured the ventilation performance, energy consumption, and noise level of mechanical ventilation devices in multi-family residential buildings. TOPSIS, a multi-criteria decision making technique was used to determine appropriate ventilation strategies in addition to occupant ventilation system operation preference.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.01a
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• pp.107-108
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• 2019

모바일 엣지 컴퓨팅(Mobile Edge Computing, MEC)은 높은 컴퓨팅 성능을 요구하는 작업을 모바일 장치에서 가까운 MEC 서버로 오프로딩함으로써 모바일 서비스에 높은 계산 요구량을 효율적으로 제공할 수 있는 기술로 부상하였다. 본 논문에서는 실행 대기 시간과 장치 에너지 소비를 줄이기 위해 여러 가지의 독립적 작업을 통해 MEC 시스템에 대한 작업 오프로드 일정 및 전송 에너지 할당을 최적화하는 기법을 제안한다. 시뮬레이션 결과로 MEC 시스템에서 사용 가능한 무선 및 계산 리소스가 상대적으로 균형 잡혀있는 경우 작업 오프로딩 일정이 더 중요하다는 것을 확인했다.

• Journal of Intelligence and Information Systems
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• v.17 no.2
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• pp.23-38
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• 2011

Energy management aims to financial and ecological success by optimizing the energy consuming sources such as sensors, computers and appliances. Hence, acquiring energy-related data from the sources in an automated manner is the starting point of managing energy. Recently, awareness computing has been emerging in system and cybernetics area. Awareness is the most fundamental ability for any living things to survive, and also the first step to make systems intelligent with the help of artificial intelligence. Even though the potential reciprocal benefits between energy management and awareness computing, frameworks which show how awareness computing contributes to manage energy-related strategy have been very few. Hence, this paper aims to introduce the awareness computing issues to improve energy management. In particular, we focus on satisfaction awareness computing which potentially realize the balance of energy savings and user's utility.

• Journal of Korea Multimedia Society
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• v.17 no.4
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• pp.458-465
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• 2014

In this paper, we propose a strategy to distribute the energy consumption over the network. The proposed strategy is based on geographic routing. We use a smart base station that maintains the residual energy and location information of sensor nodes and selects a head node and an anchor node using this information. A head node gathers and aggregates data from the sensor nodes in a target region that interests the user. An anchor node then transmits the data that was forwarded from the head node back to the smart base station. The smart base station extends network lifetime by selecting an optimal head node and an optimal anchor node. We simulate the proposed protocol and compare it with the LEACH protocol in terms of energy consumption, the number of dead nodes, and a distribution map of dead node locations.

• Proceedings of the Korea Society for Simulation Conference
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• 2000.11a
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• pp.97-101
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• 2000

Energy consumption is considered as a principal ingredient in mobile wireless ad-hoc networks. In such a network, most of mobile nodes takes a role in forwarding messages received from neighbor nodes. Energy of these nodes is consumed in different rates depending on message traffic routes. This paper proposes a scheme to balance routing energy consumption by transferring routing function from node with small residual energy to node with enough residual energy. This scheme requires additional local message transfer, increasing the energy consumption of nodes to transfer routing function, and increasing total energy consumption of ad-hoc network. But balancing of energy consumption make the system lifetime the longer and increase the average node lifetime.

• The KIPS Transactions:PartC
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• v.15C no.4
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• pp.303-310
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• 2008

To increase the lifetime of ad-hoc networks, a ratio of energy consumption for each node should be kept constant by equally distributing network traffic loads into all of the nodes. In this paper, we propose a modified AODV routing protocol to determine a possible route by considering a remaining battery capacity of a node and the degree of its usage. In addition, to reduce the amount of energy consumption during the path rediscovery process due to the huge amount of the AODV control messages the limited number of possible routes are stored into a routing table of a source node. When some links of a route fail, another possible path can be looked up in the table before the route discovery process should be initiated. We have tested our proposed method with a conventional AODV and a MMBCR method which is one of the power-efficient energy routing protocols based on the three performance metrics, i.e., the total remaining battery capacity, network lifetime and the ratio of data packets received by the destination node to compare their performance.

• Environmental and Resource Economics Review
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• v.19 no.3
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• pp.509-546
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• 2010

Although coal has been utilized as major fuel, it is known as 'most climate unfriendly' fuel. Carbon tax or tradable permit policy has been discussed as major measure for reducing production and consumption of coal, but it might be more efficient to remove subsidy on coal production and consumption. This study examines economic and environmental effects of recycling revenue from reducing subsidy on the use of coal to foster climate friendly fuel (ligneous biomass) by price subsidy or increased public expenditure. A static CGE model was applied to analyze the welfare consequences and economic impacts of two policy measures. The result shows that price subsidy policy is more desirable than creation of public demand in terms of welfare as well as overall economic impacts.

• Journal of the Korea Society of Computer and Information
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• v.16 no.12
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• pp.247-255
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• 2011

Most existing clustering protocols have been aimed to provide balancing the residual energy of each node and maximizing life-time of wireless sensor networks. In this paper, we present the adaptive clustering strategy related to sink position for clustering protocols in wireless sensor networks. This protocol allows networks topology to be adaptive to the change of the sink position by using symmetrical clustering strategy that restricts the growth of clusters based on depth of the tree. In addition, it also guarantees each cluster the equal life-time, which may be extended compared with the existing clustering protocols. We evaluated the performance of our clustering scheme comparing to LEACH and EEUC, and observe that our protocol is observed to outperform existing protocols in terms of energy consumption and longevity of the network.