• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.6
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• pp.1728-1742
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• 2023

In this paper, we extended a hierarchical clustering technique, which is the most researched in the sensor network field, and studied a dynamic differential clustering technique to minimize energy consumption and ensure equal lifespan of all sensor nodes while considering the mobility of sinks. In a sensor network environment with mobile sinks, clusters close to the sinks tend to consume more forwarding energy. Therefore, clustering that considers forwarding energy consumption is desired. Since all clusters form a hierarchical tree, the number of levels of the tree must be considered based on the size of the cluster so that the cluster size is not growing abnormally, and the energy consumption is not concentrated within specific clusters. To verify that the proposed DDC protocol satisfies these requirements, a simulation using Matlab was performed. The FND (First Node Dead), LND (Last Node Dead), and residual energy characteristics of the proposed DDC protocol were compared with the popular clustering protocols such as LEACH and EEUC. As a result, it was shown that FND appears the latest and the point at which the dead node count increases is delayed in the DDC protocol. The proposed DDC protocol presents 66.3% improvement in FND and 13.8% improvement in LND compared to LEACH protocol. Furthermore, FND improved 79.9%, but LND declined 33.2% when compared to the EEUC. This verifies that the proposed DDC protocol can last for longer time with more number of surviving nodes.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2006.05a
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• pp.125-129
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• 2006

By advent of NNC(Neural Network Chip), it is possible that process in parallel and discern the importance of signal with learning oneself by experience in external signal. So, the design of general purpose operation unit using VHDL(VHSIC Hardware Description Language) on the existing FPGA(Field Programmable Gate Array) can replaced EN(Expert Network) and learning algorithm. Also, neural network operation unit is possible various operation using learning of NN(Neural Network). This paper present general purpose operation unit using hierarchical structure of EN. EN of presented structure learn from logical gate which constitute a operation unit, it relocated several layer. The overall structure is hierarchical using a module, it has generality more than FPGA operation unit.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.10a
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• pp.510-513
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• 2010

In hierarchical wireless sensor network, Sensor nodes forming a cluster with a hierarchy. And there are being study for balanced energy consumption between cluster nodes. When forming network routing path, if there are configured incorrectly then it can be wasting energy. In this paper to solve these problem, We propose that it can consider sensor's communication range to create minimum hop layer when cluster heads configure routing path.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.6
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• pp.26-36
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• 2009

ad-hoc network is self-constructed by mobile hosts without any infrastructure. And the hosts collaborate with each other for routing packet by means of multi-hop communication. But it is too hard to deploy ad hoc network at the large area because of the salability problem caused by low network throughput. network throughput decrease is due to contention on the air among the neighbor host and single interface limitation, and broadcast flooding through overall network. In this paper, to solve the ad hoc scalability problem, we propose mesh network based scalable hierarchical ad hoc architecture, and also propose the adaptation methods for inter-working with the host not including ad hoc functions and the legacy infra-network.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.8
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• pp.3641-3655
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• 2016

Wireless sensor networks (WSNs) provide a promising approach to monitor the physical environments, to prolong the network lifetime by exploiting the mutual correlation among sensor readings has become a research focus. In this paper, we design a hierarchical network framework which guarantees layered-compression. Meanwhile, a data sorting-based adaptive spatial compression scheme (DS-ASCS) is proposed to explore the spatial correlation among signals. The proposed scheme reduces the amount of data transmissions and alleviates the network congestion. It also obtains high compression performance by sorting original sensor readings and selectively discarding the small coefficients in transformed matrix. Moreover, the compression ratio of this scheme varies according to the correlation among signals and the value of adaptive threshold, so the proposed scheme is adaptive to various deploying environments. Finally, the simulation results show that the energy of sorted data is more concentrated than the unsorted data, and the proposed scheme achieves higher reconstruction precision and compression ratio as compared with other spatial compression schemes.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.10
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• pp.123-129
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• 1994

The segmentation of range image is essential to recognize the three dimensional object. Generally, surface curvature is well-known feature for segmentation and classification of the fange image, but it is sensitive to noies. In this paper, we propose the structure of hierarchical neural network using surface curvature for segmentation of range images. The hierarchical structure of neural networks is robust to noise and the result of segmentaion is better than conventional optimization method of single level.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.8
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• pp.1729-1735
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• 2009

The hierarchical routing could cause a lot of energy consumption for transferring data by assigning hierarchical routes although actual nodes could be located in physically near spots. Also, when Node Failure or Association Error occurs, the Hierarchical routing could waste more energy to deliver the control messages. This paper evaluate performance of SHP(Shortest Hop Routing) algorithm that suggests short-cut routing algorithm using NL(Neighbor List) and Redirect_ACK message to improve problem of hierarchical routing algorithm. We do a computer simulation by the size of network, deployment of sensor nodes, sink position and POS. As a result of simulation, SHP has better performance than Zigbee Hierarchical routing and HiLow.

• Journal of the Korea Society of Computer and Information
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• v.19 no.1
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• pp.77-84
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• 2014

In this paper, we propose the hierarchical network synchronization scheme that is backward compatible for the existing commercial system, efficient for total system performance, and whose hardware modification is minimized. This system performance is, the relationship among bandwidth efficiency, complexity and MODEM performance, and superiority of network system applicability. The proposed structure can remedy the high hardware complexity and the lower accuracy of network sychronization that the existing satellite communication terminal system in the star network based on TDM/MF-TDMA of DVB-S2/RCS standards has. Besides, It has high efficiency in view of cost and system performance if the system designed for satellite broadcast requires system upgrade. In the body section, its hardware complexity and system performance of the proposed algorithm is analysed theoretically and treated with the related parameters(symbol rate, spreading factor, etc.) and the BER performance of control channel through the computer simulation for its verification that it can be applied for communications system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38B no.7
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• pp.501-511
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• 2013

Recently, the visualization method of social network service have been only focusing on presentation of visualizing network data, which the methods do not consider an efficient processing speed and computational complexity for increasing at the ratio of arithmetical of a big data regarding social networks. This paper proposes a cloud based on visualization method to visualize a user focused hierarchy relationship between user's nodes on social network. The proposed method can intuitionally understand the user's social relationship since the method uses fuzzy to represent a hierarchical relationship of user nodes of social network. It also can easily identify a key role relationship of users on social network. In addition, the method uses hadoop and hive based on cloud for distributed parallel processing of visualization algorithm, which it can expedite the big data of social network.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.431-434
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• 2001

Knowledge discovery in databases(KDD) is the process for extracting valid, novel, potentially useful and understandable knowledge form real data. There are many academic and industrial activities with new technologies and application areas. Particularly, data mining is the core step in the KDD process, consisting of many algorithms to perform clustering, pattern recognition and rule induction functions. The main goal of these algorithms is prediction and description. Prediction means the assessment of unknown variables. Description is concerned with providing understandable results in a compatible format to human users. We introduce an efficient data mining algorithm considering predictive and descriptive capability. Reasonable pattern is derived from real world data by a revised neural network model and a proposed fuzzy rule extraction technique is applied to obtain understandable knowledge. The proposed neural network model is a hierarchical self-organizing system. The rule base is compatible to decision makers perception because the generated fuzzy rule set reflects the human information process. Results from real world application are analyzed to evaluate the system\`s performance.