• International Journal of Computer Science & Network Security
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• v.23 no.8
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• pp.121-136
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• 2023

Wireless Sensor Networks (WSNs) have many potential applications and unique challenges. Some problems of WSNs are: severe resources' constraints, low reliability and fault tolerant, low throughput, low scalability, low Quality of Service (QoS) and insecure operational environments. One significant solution against mentioned problems is hierarchical and clustering-based multipath routing. But, existent algorithms have many weaknesses such as: high overhead, security vulnerabilities, address-centric, low-scalability, permanent usage of optimal paths and severe resources' consumption. As a result, this paper is proposed an energy-aware, congestion-aware, location-based, data-centric, scalable, hierarchical and clustering-based multipath routing algorithm based on Numerical Taxonomy technique for homogenous WSNs. Finally, performance of the proposed algorithm has been compared with performance of LEACH routing algorithm; results of simulations and statistical-mathematical analysis are showing the proposed algorithm has been improved in terms of parameters like balanced resources' consumption such as energy and bandwidth, throughput, reliability and fault tolerant, accuracy, QoS such as average rate of packet delivery and WSNs' lifetime.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.2
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• pp.27-37
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• 2009

Sensor nodes forming a sensor network have limited energy capacity such as small batteries and when these nodes are placed in a specific field, it is important to research minimizing sensor nodes' energy consumption because of difficulty in supplying additional energy for the sensor nodes. Clustering has been in the limelight as one of efficient techniques to reduce sensor nodes' energy consumption in sensor networks. However, energy saving results can vary greatly depending on election of cluster heads, the number and size of clusters and the distance among the sensor nodes. /This research has an aim to find the optimal set of clusters which can reduce sensor nodes' energy consumption. We use a Genetic Algorithm(GA), a stochastic search technique used in computing, to find optimal solutions. GA performs searching through evolution processes to find optimal clusters in terms of energy efficiency. Our results show that GA is more efficient than LEACH which is a clustering algorithm without evolution processes. The two-dimensional GA (2D-GA) proposed in this research can perform more efficient gene evolution than one-dimensional GA(1D-GA)by giving unique location information to each node existing in chromosomes. As a result, the 2D-GA can find rapidly and effectively optimal clusters to maximize lifetime of the sensor networks.

• The KIPS Transactions:PartC
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• v.15C no.4
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• pp.273-280
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• 2008

In WSN(Wireless Sensor Network) many routing algorithms such as LEACH, PEGASIS and PEDEP consisting of sensor nodes with limited energy have been proposed to extend WSN lifetime. Under the assumption of perfect fusion, these algorithms used convergecast that periodically collects sensed data from all sensor nodes to a base station. But because these schemes studied less energy consumption for a convergecast as well as fairly energy consumption altogether, the minimum energy consumption for a convergecast was not focused enough nor how topology influences to energy consumption. This paper deals with routing topology and energy consumption for a single convergecast in the following ways. We chose major WSN topology as MSC(Minimum Spanning Chain)s, MSTs, PEGASIS chains and proposed LECSEN chains. We solved the MSC length by Linear Programming(LP) and propose the LECSEN chain to compete with MST and MSC. As a result of simulation by Monte Carlo method for calculation of the topology length and standard deviation of link length, we learned that LECSEN is competitive with MST in terms of total energy consumption and shows the best with the view of even energy consumption at the sensor nodes. Thus, we concluded LECSEN is a very useful routing topology in WSN.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.4
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• pp.252-258
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• 2013

As WSN is energy constraint so energy efficiency of nodes is important. Because avoiding long distance communication, clustering operating in rounds is an efficient algorithm for prolonging the lifetime of WSN and its performance depends on duration of a round. A short round time leads to frequent re-clustering while a long round time increases energy consume of cluster heads more. So existing clustering schemes determine proper round time, based on the parameters of initial WSN. But it is not appropriate to apply the round time according to initial value throughout the whole network time because WSN is very dynamic networks nodes can be added or vanished. In this paper we propose a new algorithm which calculates the round time relying on the alive node number to adapt the dynamic WSN. Simulation results validate the proposed algorithm has better performance in terms of energy consumption of nodes and loss rate of data.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.2
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• pp.495-502
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• 2013

In the mobile Ad hoc Network(MANET), improving technique for management and control of topology is recognized as an important part of the next generation network. In this paper, we proposed an efficient node life time management of ATICC(Adaptive Time Interval Clustering Control) in Ad-hoc Networks. Ad-hoc Network is a self-configuration network or wireless multi-hop network based on inference topology. This is a method of path routing management node for increasing the network life time through the periodical route alternation. The proposed ATICC algorithm is time interval control technique depended on the use of the battery energy while node management considering the attribute of node and network routing. This can reduce the network traffic of nodes consume energy cost effectively. As a result, it could be improving the network life time by using timing control method in ad-hoc networks.

• Journal of the Korea Society of Computer and Information
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• v.25 no.4
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• pp.97-103
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• 2020

Wireless sensor networks collect and analyze sensing data in a variety of environments without human intervention. The sensor network changes its lifetime depending on routing protocols initially installed. In addition, it is difficult to modify the routing path during operating the network because sensors must consume a lot of energy resource. It is important to measure the network performance through simulation before building the sensor network into the real field. This paper proposes a WSN model for a low-energy adaptive clustering hierarchy protocol using DEVS kernel models. The proposed model is implemented with the sub models (i.e. broadcast model and controlled model) of the kernel model. Experimental results indicate that the broadcast model based WSN model showed lower CPU resource usage and higher message delivery than the broadcast model.

• Journal of Korea Multimedia Society
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• v.12 no.11
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• pp.1609-1622
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• 2009

In wireless sensor networks, a clustering protocol is an efficient method to prolong network lifetime. In general, it results in more energy consumption at the cluster-head node. Hence, such a protocol must changes the cluster formation and cluster-head node in each round to prolong the network lifetime. But, this method also causes large amount of energy consumption during the set-up process of cluster formation. In order to improve energy efficiency, in this paper, we propose a new clustering algorithm. In this algorithm, we exclude duplicated data of adjacent nodes and transmits the threshold value. We define a group as the sensor nodes within close proximity of each other. In a group, a node senses and transmits data at a time on the round-robin basis. In a view of whole network, group is treated as one node. During the setup phase of a round, intra clusters are formed first and then they are re-clustered(network cluster) by choosing cluster-heads(group). In the group with a cluster-head, every member node plays the role of cluster-head on the round-robin basis. Hence, we can lengthen periodic round by a factor of group size. As a result of analysis and comparison, our scheme reduces energy consumption of nodes, and improve the efficiency of communications in sensor networks compared with current clustering methods.

• Journal of Environmental Health Sciences
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• v.39 no.5
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• pp.408-417
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• 2013

Objectives: Phthalates are used as plasticizers in polyvinyl chloride (PVC) plastics. As phthalate plasticizers are not chemically bound to the PVC, they can leach, migrate or evaporate into indoor air and atmosphere, foodstuffs, other materials, etc. Therefore, humans are exposed through ingestion, inhalation, and dermal exposure over their entire lifetime, including during intrauterine development. In particular, university students have a great number of opportunities to contact products including phthalates during campus life (food packaging, body care products, cosmetic, lotions, aftershave, perfume etc.). The purpose of this study was to examine levels of phthalate exposure as undergraduate students begin to use pharmaceuticals and personal care products including phthalates. Methods: Phthalate metabolites, mono-ethyl phthalate (MEP), mono-n-butyl phthalate (MnBP), mono-isobutyl phthalate (MiBP), mono-2- ethylhexyl phthalate (MEHP), {(mono-(2-ethyl-5-hydroxyhexyl) phthalate (MEHHP}, and mono-(2-ethlyl-5-oxohexyl) phthalate (MEOHP} were examined. 80 urine samples collected from university students were analyzed using LC/MS/MS(API 4000, Applied Bioscience) with on-line enrichment and columnswitching techniques. This study was carried out at Y university located in Gyonggi Province from 2008 to 2011. Results: The detection limit of phthalate metabolites were 0.03 ng/mL for MEP, 0.11 ng/mL for MnBP, 0.08 ng/mL for MiBP, 0.93 ng/mL for MEHP, 0.19 ng/mL for MEOHP and 0.16ng/mL for MEHHP. MnBP showed the highest urinary levels (median: 31.6 ug/L, 24.8 ug/g creatinine (cr)). Concentrations were also high for MEHHP (median: 24.1 ug/L, 19.0 ug/g cr), followed by MEOHP (median: 22.8 ug/L, 17.9 ug/g cr). In individual cases, the maximum level reached up to 348 ug/L, and 291 ug/g cr, respectively. The urinary and creatinine adjusted levels of MEP were lower than those for DBP and DEHP metabolites, but were higher in 95th percentiles. As a result, the mean daily DEP intake value was 2.3 ${\mu}g/kg$ bw/day, 3.5 ${\mu}g/kg$ bw/day for DEHP and 4.9 ${\mu}g/kg$ bw/day for DBP. Conclusion: These students' phthalate exposure levels were below the international safe level set by the EU, but higher than the 2012 KFDA survey of the age group from 3 to 18.