• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.1
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• pp.99-106
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• 2017

In the WSN environment, the sensor node is selected as the cluster header and consumes a lot of energy. Therefore, we proposed a method to automatically select a cluster algorithm using the sensor field environment that can improve the reliability of the whole network by applying an energy efficient clustering algorithm based on already deployed sensor field. Experimental results show that FDN is extended about 3 times by using the proposed algorithm. In addition, the network energy is extended by up to 30% compared to the conventional method, thereby improving the reliability of the sensor network.

• Journal of Environmental Science International
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• v.21 no.5
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• pp.545-553
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• 2012

Eco-efficiency considers both environmental impacts and economic values. It is a useful tool for communicating with stakeholders for business decision making. This study evaluated the eco-efficiency factor (EEF) for the energy network of a dyeing company that supplies surplus heat to a neighboring apartment during the night. This symbiosis network is one of the eco-industrial park (EIP) projects in Korea and aims to benefit local residents and the industrial complex by utilizing surplus heat. In this study, two categories were annualized. The first quantified environmental burden based on $CO_2$ emissions and quantified product value in terms of steam sales. The second used a variety of environmental factors, such as fossil fuel, water and waste, to quantify environmental burden and used steam sales to quantify value. The EEF of the symbiosis network was 1.6, using the global warming impact, and determined using the multiple variable, was 1.33. This study shows that the EEF depends on variable details of environmental burden but the values of this project were very high contrast to other business or EIP project.

• Journal of Communications and Networks
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• v.14 no.1
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• pp.75-90
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• 2012

Thin client computing trades local processing for network bandwidth consumption by offloading application logic to remote servers. User input and display updates are exchanged between client and server through a thin client protocol. On wireless devices, the thin client protocol traffic can lead to a significantly higher power consumption of the radio interface. In this article, a cross-layer framework is presented that transitions the wireless network interface card (WNIC) to the energy-conserving sleep mode when no traffic from the server is expected. The approach is validated for different wireless channel conditions, such as path loss and available bandwidth, as well as for different network roundtrip time values. Using this cross-layer algorithm for sample scenario with a remote text editor, and through experiments based on actual user traces, a reduction of the WNIC energy consumption of up to 36.82% is obtained, without degrading the application's reactivity.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.4
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• pp.793-797
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• 2004

Wireless sensor networks use battery-operated computing and sensing devices. And It can be expected to be deployed in an ad hoc networs. MAC is different from traditional wireless MACs such as IEEE 802.11 in almost every way. so self-configuration and power saving in sensor network are very important goals, while per-node fairness and latency are less important. In this paper, so we use a given prototype for efficient energy conservation to reduce power consumtion that is one of the important character in sensor network and compare energy consumption and collision with IEEE 802.11 MAC. finally we conclude the paper and analyze it.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2004.05b
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• pp.182-185
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• 2004

Wireless sensor networks use battery-operated computing and sensing devices. And It can be expected to be deployed in an ad hoc networs. MAC is different from traditional wireless MACs such as IEEE 802.11 in almost every way. so self-configuration and power saving in sensor network are very important goals, while per-node fairness and latency are less important. In this paper, so we use a given prototype for efficient energy conservation to reduce power consumtion that is one of the important character in sensor network and compare energy consumption and collision with IEEE 802.11 MAC. Finally we conclude the paper and analyze it.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.8
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• pp.1511-1518
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• 2008

Wireless sensor network is a network that consists of small wireless sensor nodes. Sensor nodes transfer the sensed data about the objects or environment to the sink through wireless channel. The energy dissipation by wireless transmission is the primary factor of energy dissipation in the sensor node. To utilize the limitted resource at the sensor node, it is required to reduce the number of wireless transmission. In the paper, we proposes a new energy efficient method, NRMC, to reduce the energy dissipation by using the compression technique - DPCM, Wavlet, Quantization, RLC. With NTRC, the life time of sensor network could be increased.

• Nuclear Engineering and Technology
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• v.54 no.1
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• pp.310-317
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• 2022

The mass attenuation coefficient is the primary physical parameter to model narrow beam gamma-ray attenuation. A new machine learning based approach is proposed to model gamma-ray shielding behavior of composites alternative to theoretical calculations. Two fuzzy logic algorithms and a neural network algorithm were trained and tested with different mixture ratios of vanadium slag/epoxy resin/antimony in the 0.05 MeV-2 MeV energy range. Two of the algorithms showed excellent agreement with testing data after optimizing adjustable parameters, with root mean squared error (RMSE) values down to 0.0001. Those results are remarkable because mass attenuation coefficients are often presented with four significant figures. Different training data sizes were tried to determine the least number of data points required to train sufficient models. Data set size more than 1000 is seen to be required to model in above 0.05 MeV energy. Below this energy, more data points with finer energy resolution might be required. Neuro-fuzzy models were three times faster to train than neural network models, while neural network models depicted low RMSE. Fuzzy logic algorithms are overlooked in complex function approximation, yet grid partitioned fuzzy algorithms showed excellent calculation efficiency and good convergence in predicting mass attenuation coefficient.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.11a
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• pp.547-548
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• 2009

The development of USN(Ubiquitous Sensor Network) technology is creating numerous application areas. Although a network configuration with fixed sensors was the norm in the past, the coexistence of mobile and fixed sensor nodes is a new trend. Fixed sensor networks focused on the energy efficiency of nodes, but the latest studies consider guaranteeing the mobility of nodes and maintaining their connectivity, while remaining energy efficient at the same time. This paper proposes a routing protocol for a mobile ad-hoc sensor network that improves the mobility, connectivity and energy efficiency of nodes while allowing for the management and maintenance of a large number of nodes even in a complex communication environment where mobile and fixed nodes coexist. An algorithm for multi-hop multi-paths, a technique for topology reconfiguration by node movement prediction and vibration sensors, path setting for a large number of nodes, and efficient data transfer technology have been introduced to implement the modified LEAHC-AOMDV protocol. Furthermore, the excellence of this protocol was verified through a comparative experiment with the conventional LEACH protocol.

• Korean Chemical Engineering Research
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• v.56 no.6
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• pp.841-855
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• 2018

The purpose of this study is to estimate the available potential heat source for heat pump in the district heating supply area in the city. Unused energy potentials were estimated and integrated based on open source based data. In particular, geographical spatial analysis of recoverable heat energy density and heat demand in the heat source area of large retailers and public sauna facilities in the DH network located in the southern part of the metropolitan area (Pyeongtaek-si) was conducted. As a result of the study, the DH network area had a total potential energy of 1,741.7 toe/year for the two heat sources of large retailers and public saunas. It is estimated that 1,006.9 toe/year, which is 57.8% of the total, can be linked to the district heating. The large retailers showed a positive correlation with the floor area and energy use of 0.4937. The recoverable energy intensity was estimated to be $0.0017toe/m^2$ per unit area and $0.0069tCO_2/m^2$ for greenhouse gas emissions. In addition, public saunas were analyzed by comparing the empirical case with the theoretical calculation, and it was estimated that energy conservation estimate of 80% was $0.0315toe/m^2$ per bath area and $0.1183tCO_2/m^2$ for greenhouse gas emissions. The total potential energy amount of this area was positively correlated with the heat demand of apartment house by administrative district, and it was confirmed that it had a relatively high potential energy especially in traffic and commercial center.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.7
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• pp.3494-3510
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• 2019

Wireless sensor networks encounter energy saving as a major issue as the sensor nodes having no rechargeable batteries and also the resources are limited. Clustering of sensors play a pivotal role in energy saving of the deployed sensor nodes. However, in the cluster based wireless sensor network, the cluster heads tend to consume more energy for additional functions such as reception of data, aggregation and transmission of the received data to the base station. So, careful selection of cluster head and formation of cluster plays vital role in energy conservation and enhancement of lifetime of the wireless sensor networks. This study proposes a new mutation chemical reaction optimization (MCRO) which is an algorithm based energy efficient clustering protocol termed as MCRO-ECP, for wireless sensor networks. The proposed protocol is extensively developed with effective methods such as potential energy function and molecular structure encoding for cluster head selection and cluster formation. While developing potential functions for energy conservation, the following parameters are taken into account: neighbor node distance, base station distance, ratio of energy, intra-cluster distance, and CH node degree to make the MCRO-ECP protocol to be potential energy conserver. The proposed protocol is studied extensively and tested elaborately on NS2.35 Simulator under various senarios like varying the number of sensor nodes and CHs. A comparative study between the simulation results derived from the proposed MCRO-ECP protocol and the results of the already existing protocol, shows that MCRO-ECP protocol produces significantly better results in energy conservation, increase network life time, packets received by the BS and the convergence rate.