• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.29 no.5
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• pp.19-25
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• 2015

The management of energy resources for efficient utilization of the energy resources while reducing the system costs is a critical technical issue. Among many kinds of the energy resource management, the energy reduction for indoor lighting systems is getting much concern as a large portion of energy consumption has been made for indoor lightings. In this paper, an energy-efficient lighting control scheme for indoor lighting systems in order to reduce the energy consumption by controlling the luminous flux and the lighting direction under the illuminance constraints is proposed. With the use of the user location information for the luminaire which is closely located to the user, the proposed scheme firstly sets the light direction of the luminaire to be aligned to the user location. Then, an optimization problem to find the luminous flux of each luminaire is formulated in order to minimize the luminous flux sum of the luminaires with the constraints for the dynamic ragne of the luminous flux, and the light flux for each luminaire is determined by the solution of the problem. Simulation results show that the proposed scheme outperforms the luminaire control scheme with only the luminous flux control in the evaluation of satisfaction of the required illuminance level.

• Electronics and Telecommunications Trends
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• v.33 no.5
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• pp.42-50
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• 2018

UDN is expected to be a type of network capable of satisfying the requirements various 5G services, such as the peak data rate, connection density, and area traffic capacity. Technical challenges for 5G UDN, such as interference management, resource management, mobility management, load balancing, and energy efficiency are discussed. In addition, candidate technologies for solving these challenges, and their related standardization trends, are summarized in this article.

• Journal of Communications and Networks
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• v.16 no.2
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• pp.121-129
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• 2014

The trend of an increasing demand for a high-quality user experience, coupled with a shortage of radio resources, has necessitated more advanced wireless techniques to cooperatively achieve the required quality-of-experience enhancement. In this study, we investigate the critical problem of rate splitting in heterogeneous cellular networks, where concurrent transmission, for instance, the coordinated multipoint transmission and reception of LTE-A systems, shows promise for improvement of network-wide capacity and the user experience. Unlike most current studies, which only deal with spectral efficiency enhancement, we implement an optimal rate splitting strategy to improve both spectral efficiency and energy efficiency by exploring and exploiting cooperation diversity. First, we introduce the motivation for our proposed algorithm, and then employ the typical cooperative bargaining game to formulate the problem. Next, we derive the best response function by analyzing the dual problem of the defined primal problem. The existence and uniqueness of the proposed cooperative bargaining equilibrium are proved, and more importantly, a distributed algorithm is designed to approach the optimal unique solution under mild conditions. Finally, numerical results show a performance improvement for our proposed distributed cooperative rate splitting algorithm.

• The Journal of the Korea Contents Association
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• v.10 no.2
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• pp.14-24
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• 2010

Because WSNs operate with limited resources of sensor nodes, its life is extended by cluster-based routing methods. In this study, we use data on direction, distance, density and residual energy in order to maximize the energy efficiency of cluster-based routing methods. Through this study, we expect to minimize the frequency of isolated nodes when selecting a new cluster head autonomously using information on the direction of the upper cluster head, and to reduce energy consumption by switching sensor nodes, which are included in both of the new cluster and the previous cluster and thus do not need to update information, into the sleep mode and updating information only for newly included sensor nodes at the setup phase using distance data. Furthermore, we enhance overall network efficiency by implementing secure and energy-efficient communication through key management robust against internal and external attacks in cluster-based routing techniques. This study suggests the modified cluster head selection scheme which uses the conserved energy in the steady-state phase by reducing unnecessary communications of unchanged nodes between selected cluster head and previous cluster head in the setup phase, and thus prolongs the network lifetime and provides secure and equal opportunity for being cluster head.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.11
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• pp.5476-5496
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• 2016

Energy efficiency of resource-constrained wireless sensor networks is critical in applications such as real-time monitoring/surveillance. To improve the energy efficiency and reduce the energy consumption, the time series data can be compressed before transmission. However, most of the compression algorithms for time series data were developed only for single variate scenarios, while in practice there are often multiple sensor nodes in one application and the collected data is actually multivariate time series. In this paper, we propose to compress the time series data by the Lasso (least absolute shrinkage and selection operator) approximation. We show that, our approach can be naturally extended for compressing the multivariate time series data. Our extension is novel since it constructs an optimal projection of the original multivariates where the best energy efficiency can be realized. The two algorithms are named by ULasso (Univariate Lasso) and MLasso (Multivariate Lasso), for which we also provide practical guidance for parameter selection. Finally, empirically evaluation is implemented with several publicly available real-world data sets from different application domains. We quantify the algorithm performance by measuring the approximation error, compression ratio, and computation complexity. The results show that ULasso and MLasso are superior to or at least equivalent to compression performance of LTC and PLAMlis. Particularly, MLasso can significantly reduce the smooth multivariate time series data, without breaking the major trends and important changes of the sensor network system.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.6
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• pp.85-91
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• 2014

Nowadays, Dynamic lighting control and management skills are studied and used. If the system which is to manage multiple intelligent spot applied ubiquitous service technology is built with decision making and used in the complex intelligent space like a apartment then will improve energy efficiency and provide comfortability in optimal conditions. To solve this problem distributed autonomous control middleware and energy management system which process data gathering by zigbee mesh network and search proper services to save energy by the existing state of things is necessary. In paper we designed DDLEMS (Distributed Dynamic Lighting Energy Management System) that is to service duplex communication embedded by software based home server platform to provide mobile services in the smart place and support decision making about energy saving to the best use of wireless censor node and controled network, energy display devices.

• Advances in Energy Research
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• v.6 no.1
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• pp.1-15
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• 2019

The objective of the study is to examine the relationship between water resources, energy demand, food production, and environmental pollutants in selected SAARC nations, namely, Bangladesh, India, Pakistan, and Sri Lanka, during the period of 1990-2016. The results show that water, energy, and food (WEF) resources substantially affected air quality in the form of high mass carbon emissions, fossil fuel energy demand, methane discharges, nitrous oxide emissions, and greenhouse gas emissions in these countries. Food production and food deficit largely increase $CO_2$ emissions due to unsustainable production and malnutrition, while land use under cereal production increases $CH_4$ and $N_2O$ emissions. Electricity production escalates $CO_2$ emissions and fossil emissions across countries. The results support the carbon EKC hypothesis, while monotonic increasing function exists in case of fossil fuel energy. The study emphasizes the need to ensure environmental sustainability agenda by adopting cleaner production technologies in WEF resources.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.9A
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• pp.884-891
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• 2006

A wireless sensor node is typically battery operated and energy constrained. Therefore it is critical to design efficient power management technique and scheduling technique. In this paper, we propose an OS-level power management technique for energy saving of wireless sensor node, it is called EA-SENTAS (Energy-Aware Sensor Node TAsk Scheduling). It can decrease the energy consumption of a wireless sensor node to use task scheduling technique that shut down components or use low power mode of each component when not needed. Simulation results show that EA-SENTAS saves energy up to 56 percent to compare with conventional duty cycle.

• Smart Media Journal
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• v.9 no.1
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• pp.84-91
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• 2020

Along with increasing the renewable energy utilization, many researches have paid attention on the utilization and efficiency of energy storage systems. Especially, it is required an operational model in order to actively respond with each system's failure of sub-systems in the solar energy storage system. This paper proposes an energy management scheme by estimating the newly generated power based on the solar power generation samples. With comparing the estimated battery charging power in real time and the total charging power of the battery rack, a charge model is applied to adjust the charging power, As a result, the stability of energy storage system would be improved by suppressing the battery heat while maintaining battery C-Rate.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.41-42
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• 2021

The Green New Deal policy was established to innovate the government's energy consumption structure, establish a third basic energy plan to strengthen the global competitiveness of the energy industry, and realize a carbon neutral society due to the increased need for transition to a low-carbon economy. Waterworks such as drinking water, water purification plant, and pressurization plant analyze control factors and energy consumption status by process to improve energy management efficiency and reduce energy usage through the 4th industrial revolution. Ultimately, we want to realize net-zero water purification plant.