• Journal of Korea Society of Industrial Information Systems
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• v.25 no.1
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• pp.1-11
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• 2020

Wireless sensor networks consist of a large number of tiny sensor nodes which have limited battery life. In order to maximize the network life span, we propose an optimal transmission radius, R, for control messages. We analyze the transmission radius as a function of the energy consumption of cluster head nodes and the energy consumption of member nodes to find the optimal value of R. In simulations we apply our proposed optimization of transmission range to LEACH-based single-hop and multi-hop networks to show that our proposed scheme outperforms other existing routing algorithms in terms of network life span.

• International Journal of Computer Science & Network Security
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• v.22 no.1
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• pp.139-148
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• 2022

Research into wireless sensor networks (WSNs) is a trendy issue with a wide range of applications. With hundreds to thousands of nodes, most wireless sensor networks interact with each other through radio waves. Limited computational power, storage, battery, and transmission bandwidth are some of the obstacles in designing WSNs. Clustering and routing procedures have been proposed to address these concerns. The wireless sensor network's most complex and vital duty is routing. With the Greedy Perimeter Stateless Routing method (GPSR), an efficient and responsive routing protocol is built. In packet forwarding, the nodes' locations are taken into account while making choices. In order to send a message, the GPSR always takes the shortest route between the source and destination nodes. Weighted directed graphs may be constructed utilising four distinct distance metrics, such as Euclidean, city block, cosine, and correlation distances, in this study. NS-2 has been used for a thorough simulation. Additionally, the GPSR's performance with various distance metrics is evaluated and verified. When compared to alternative distance measures, the proposed GPSR with correlation distance performs better in terms of packet delivery ratio, throughput, routing overhead and average stability time of the cluster head.

• Journal of The Korean Society of Agricultural Engineers
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• v.56 no.1
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• pp.11-20
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• 2014

Many classification studies for the community of densely-connected nodes are limited to the comprehensive analysis for detecting the communities in probabilistic networks with nodes and edge of the probabilistic distribution because of the difficulties of the probabilistic operation. This study aims to use convolution method for operating nodes and edge of probabilistic distribution. For the probabilistic hierarchy network with nodes and edges of the probabilistic distribution, the model of this study detects the communities of nodes to make the new probabilistic distribution with two distribution. The results of our model was verified through comparing with Monte-carlo Simulation and other community-detecting methods.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.99-100
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• 2006

One of the fundamental problems in sensor networks is the deployment of sensor nodes. The Fuzzy C-Means(FCM) clustering algorithm is proposed to determine the optimum location and minimum number of sensor nodes for the specific application space. We performed a simulation using two dimensional L shape model. The actual length of the L shape model is about 100m each. We found the minimum number of 15 nodes are sufficient for the complete coverage of modeled area. We also found the optimum location of each nodes. The real deploy experiment using 15 sensor nodes shows the 95.7%. error free communication rate.

• The KIPS Transactions:PartC
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• v.16C no.5
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• pp.629-636
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• 2009

Since all sensor nodes in wireless sensor networks work by their own embedded batteries, if a node runs out of its battery, the sensor network can not operate normally. In this situation we should employ the routing protocols which can consume the energy of nodes efficiently. Many protocols for energy efficient routing in sensor networks have been suggested but LEACH and PEGASIS are most well known protocols. However LEACH consumes energy heavily in the head nodes and the head nodes tend to die early and PEGASIS - which is known as a better energy efficient protocol - has a long transfer time from a source node to sink node and the nodes close to the sink node expend energy sharply since it makes a long hop of data forwarding. We proposed a new hybrid protocol of LEACH and PEGASIS, which uses the clustering mechanism of LEACH and the chaining mechanism of PEGASIS and it makes the life time of sensor networks longer than other protocols and we improved the performance 33% and 18% higher than LEACH-C and PEGASIS respectively.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.6
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• pp.15-21
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• 2009

The goal of wireless sensor networks is to collect sensing data on specific region over wireless communication. Sink node gathers all local sensing data, processes and transmits them to users who use sensor networks. Generally, senor nodes are low-cost, low power devices with limited sensing, computation and wireless communication capabilities. And sensor network applies to multi-hop communication on large-scale network. As neighboring sensor nodes have similar data, clustering is more effective technique for 'data-aggregation'. In cluster formation technique based on multi-hop, it is necessary that the number of cluster member nodes should be distributed equally because of the balance of cluster formation To achieve this, we propose a method to customize cluster member nodes for energy-efficiency in wireless sensor networks.

• Journal of Korea Multimedia Society
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• v.14 no.9
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• pp.1138-1151
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• 2011

Sensor network clustering scheme is an efficient method that prolongs network lifetime. However, when it is applied to an environment in which collected data of the sensor nodes easily overlap, sensor node unnecessarily consumes energy. Accordingly, we proposed a data prediction scheme that sensor node can predict current data to exclude redundant data transmission and to minimize data transmission among the cluster head node and member nodes. Our scheme excludes redundant data collection by neighbor nodes. Thus it is possible that energy efficient data transmission. Moreover, to alleviate unnecessary data transmission, we introduce data prediction graph whether transmit or not through analyze between prediction and current data. According to the result of performance analysis, our method consume less energy than the existing clustering method. Nevertheless, transmission efficiency and data accuracy is increased. Consequently, network lifetime is prolonged.

• IEIE Transactions on Smart Processing and Computing
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• v.5 no.2
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• pp.85-93
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• 2016

The existence of correlation characteristics brings significant potential advantages to the development of efficient routing protocols in wireless sensor networks. This research proposes a new simple method of clustering sensor nodes into correlation groups in multiple-correlation areas. At first, the evaluation of joint entropy for multiple-sensed data is considered. Based on the evaluation, the definition of correlation region, based on entropy theory, is proposed. Following that, a correlation clustering scheme with less computation is developed. The results are validated with a real data set.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.629-630
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• 2008

MANET is depended on the property as like variable energy, high degree of mobility, location environments of nodes etc. So, in this paper, we propose an algorithm techniques which is TICC (Time Interval Clustering Control) based on energy value in property of each node for solving cluster problem. It provides improving cluster energy efficiency how can being node manage to order each node's energy level. TICC is clustering method. It has shown that Node's energy efficiency and life time are improved in MANET.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.4
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• pp.1661-1678
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• 2016

Clustering is one of the key technologies in vehicular networks. Constructing and maintaining stable clusters is a challenging task in high mobility environments. DWCM (Distributed and Weighted Clustering based on Mobility Metrics) is proposed in this paper based on the d-hop dominating set of the network. Each vehicle is assigned a priority that describes the cluster relationship. The cluster structure is determined according to the d-hop dominating set, where the vehicles in the d-hop dominating set act as the cluster head nodes. In addition, cluster maintenance handles the cluster structure changes caused by node mobility. The rationality of the proposed algorithm is proven. Simulation results in the NS-2 and VanetMobiSim integrated environment demonstrate the performance advantages.