• Journal of information and communication convergence engineering
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• v.20 no.3
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• pp.143-152
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• 2022

The ongoing adoption of 5G will increase the data traffic, throughput, multimedia services, and power consumption for future wireless applications and services, including sensor and mobile networks. Multipath fading on wireless channels also reduces the system performance and increases energy consumption. To address these issues, device-to-device (D2D) and cooperative communications have been proposed. In this study, we propose two inter-clustering models using the relay selection method to improve system performance and increase energy efficiency in cooperative D2D networks. We develop two inter-clustering models and present their respective algorithms. Subsequently, we run a computer simulation to evaluate each model's outage probability (OP) performance, throughput, and energy efficiency. The simulation results show that inter-clustering model II has the lowest OP, highest throughput, and highest energy efficiency compared with inter-clustering model I and the conventional inter-clustering-based multirelay method. These results demonstrate that inter-clustering model II is well-suited for use in 5G overlay D2D and cellular communications.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.10
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• pp.1873-1880
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• 2016

Most of the energy used to operate a cellular network is consumed by a base station (BS), and reducing the transmission power of a BS is required for energy-efficient cellular networks. In this paper, a distributed transmit power control (TPC) algorithm is proposed based on the flocking model to improve the energy efficiency of a cellular network. Just as each bird in a flock attempts to match its velocity with the average velocity of adjacent birds, in the proposed algorithm each mobile station (MS) in a cell matches its rate with the average rate of the co-channel MSs in adjacent cells by controlling the transmit power of its serving BS. Simulation results show that the proposed TPC algorithm follows the same convergence properties as the flocking model and also effectively reduces the power consumption at the BSs while maintaining a low outage probability as the inter-cell interference increases. Consequently, it significantly improves the energy efficiency of a cellular network.

• Journal of Energy Engineering
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• v.22 no.1
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• pp.38-43
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• 2013

There was a dire need to compile data about energy consumption data by use to analyze residential energy consumption patterns relating to changes in lifestyles, or changes in life behavior. Accordingly, bottom-up model for residential energy consumption by residential use was developed by life behavior classification in an attempt to analyze energy consumption. This paper multiplied each appliance's running times by each appliance by life behavior and built a residential bottoms-up model to figure out the energy consumption of each household. The uses by life behavior were broken down into lighting, heating, cooling, entertainment, obtaining information, hygiene, and cooking.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.10
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• pp.5014-5034
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• 2016

This paper discusses how to effectively guarantee the coverage and connectivity quality of wireless sensor networks when joint perception model is used for the nodes whose communication ranges are multi-level adjustable in the absence of position information. A Connect Coverage Algorithm Based on Joint Sensing model (CCAJS) is proposed, with which least working nodes are chosen based on probability model ensuring the coverage quality of the network. The algorithm can balance the position distribution of selected working nodes as far as possible, as well as reduce the overall energy consumption of the whole network. The simulation results show that, less working nodes are needed to ensure the coverage quality of networks using joint perception model than using the binary perception model. CCAJS can not only satisfy expected coverage quality and connectivity, but also decrease the energy consumption, thereby prolonging the network lifetime.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.8
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• pp.1032-1038
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• 2021

Rate of penetration(ROP) is one of the important variables for maximizing the drilling performance. In order to maximize drilling efficiency, it is necessary to increase the drilling speed, and real-time ROP prediction is important so that the driller can identify problems during drilling. The ROP has a high correlation with the drillstring rotational speed, weight on bit, and flow rate. In this paper, the ROP was predicted using a data-driven supervised learning model trained from the drilling efficiency parameters. As a result of comparison through the performance evaluation metrics of the regression model, the root mean square error(RMSE) of the RF model was 4.20 and the mean absolute percentage error(MAPE) was 9.08%, confirming the best predictive performance. The proposed method can be used as a base model for ROP prediction when constructing a real-time drilling operation guide system.

• Journal of the Korean Data and Information Science Society
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• v.24 no.3
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• pp.585-592
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• 2013

As the needs for alternative energy and renewable energy increase, there has been a lot of investment in developing wind energy, which does not cause air pollution nor the greenhouse gas effect. Wind energy is an environment friendly energy that is unlimited in its resources and is possible to be produced wherever the wind blows. However, since wind energy heavily relies on wind that has unreliable characteristics, it may be difficult to have efficient energy transmissions. For this reason, an important factor in wind energy forecasting is the estimation of available wind power. In this study, Gunsan wind farm data was used to compare ARMA model to neural network model to analyze for more accurate prediction of wind power generation. As a result, the neural network model was better than the ARMA model in the accuracy of the wind power predictions.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.2
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• pp.477-485
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• 2015

Most existing simulators for wireless sensor networks(WSNs) are modeling battery-based sensors and providing MAC and routing protocols designed for battery-based WSNs. However, recently, as energy harvesting sensor systems have been studied more extensively, there is an increasing need for appropriate simulators, but few related studies have employed such simulators. Unlike existing simulators, simulators for energy harvesting WSNs require a new energy model that is integrated with the energy-harvesting model, rechargeable battery model, and energy-consuming model. Additionally, it should enable the applications of the well-known MAC and routing protocols designed for energy-harvesting WSNs, as well as a user-friendly interface for convenience. In this work, we design and implement a user-friendly simulator for solar energy-harvesting WSNs.

• 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 Information Systems
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• v.28 no.1
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• pp.133-153
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• 2019

Purpose The purpose of this study is to design a regional electricity planning model rather than the existing single region ones and verify its usefulness. The regional electricity planning model is to determine both electricity distribution among regions and power plant planning at the same time satisfying regional demands and distribution networks. Design/methodology/approach This study made a regional electricity planning model by integrating power plant planning and electricity distribution among regions. The regional electricity planning model is formulated into a linear programming problem, and coded and run using the OSeMOSYS, one of open source energy systems. Findings According to the empirical analysis result, this study confirmed that the regional electricity planning model proposed in this study deducts the unfairness among regions in view of electricity and green house gas. In addition, the model is expected to be used in evaluating and developing the national policies concerning fine dust and/or green house gas.

• Journal of Satellite, Information and Communications
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• v.11 no.2
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• pp.60-64
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• 2016

In this paper, we propose a scheme for MIMO beamforming for the backscatter communication using a multi-tag to improve the efficiency of energy harvesting and the BER of received signals. We obtain a normal channel information through a communication between the H-AP and multi-tag. The H-AP sets parameters for the transmission scenario of the spatial channel model (SCM) using the obtained channel information and generates a SCM channel information. Then, the H-AP transmits signals that have optimal transmission power to increase the signal-to-interference-plus-noise ratio (SINR) to each of tags. Tags perform a backscatter communication with signals. The receiver performs a time switching technique of energy harvesting using backscatter signals from the multi-tag. Simulation results demonstrate effectiveness of the proposed scheme, and the harvesting efficiency and BER at the receiver is greatly improved.