• Journal of Advanced Navigation Technology
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• v.15 no.1
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• pp.54-60
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• 2011

The development of wireless sensor networks (WSN) can be motivated by several types of applications. However, these applications demand an energy-efficient WSN that can prolong the network lifetime and can provide high throughput, low latency and delay. Designing wireless sensor networks with the capability of prolonging network lifetime catch the attention of many researchers in wireless system and network field. Contrasts with Mobile Ad Hoc Network system, Wireless Sensor Networks designs focused more on survivability of each node in the network instead of maximizing data throughput or minimizing end-to-end delay. In this paper, we will study part of data link layer in Open Systems Interconnection (OSI) model, called medium access control (MAC) layer. Since the MAC development of energy aware MAC Protocol for wireless sensor layer controls the physical radio part, it has a large impact on the overall energy consumption and the lifetime of a node. This paper proposes a analytical approach that tries to reduce idle energy consumption, and shows the increasement of network end-to-end arrival rate due to efficiency in energy consumption from time slot management.

• Journal of the Korea Society of Computer and Information
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• v.18 no.12
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• pp.113-121
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• 2013

In this paper, we design and implement a network weather map system, which provides a macroscopic view on the whole network topology as well as the network link status and utilization. The proposed system also provides distributed NetFlow-based database facility and Web-based query interface, through which network operators can check the detailed network router or link status as well as submit predefined queries to easily find out and locate heavy hitters and/or their usage. We believe that our develop system will be a useful tool for small-to-mid-scale ISPs or network operators, in managing their own networks in a cost-effective way.

• Journal of Convergence for Information Technology
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• v.10 no.6
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• pp.41-48
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• 2020

The sensor nodes in underwater IoT networks have practical limitations in power supply. Thus, the reduction of power consumption is one of the most important issues in underwater environments. In this regard, AMC(Adaptive Modulation and Coding) techniques are used by using the relation between SNR and BER. However, according to our hands-on experience, we observed that the relation between SNR and BER is not that tight in underwater environments. Therefore, we propose a deep learning based MLP classification model to reflect multiple underwater channel parameters at the same time. It correctly predicts BER with a high accuracy of 85.2%. The proposed model can choose the best parameters to have the highest throughput. Simulation results show that the throughput can be enhanced by 4.4 times higher than the conventionally measured results.

• Journal of Internet Computing and Services
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• v.8 no.5
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• pp.133-140
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• 2007

Currently, as the requirement for high quality Internet access from anywhere at anytime is consistently increasing, the interconnection of pure ad hoc networks to fixed IP networks becomes increasingly important. Such integrated network, referred to as hybrid ad hoc networks, can be extended to many applications, including Sensor Networks, Home Networks, Telematics, and so on. We focus on some data communication problems of hybrid ad hoc networks, such as broadcasting and routing. In particular. power failure of mobile terminals is the most important factor since it affects the overall network lifetime. We propose an energy-efficient routing protocol based on clustering for hybrid ad hoc networks. By applying the index-based data broadcasting and selective tuning methods, the infra system performs the major operations related to clustering and routing on behalf of ad hoc nodes. The proposed scheme reduces power consumption as well as the cost of path discovery and maintenance, and the delay required to configure the route.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.11 no.2
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• pp.137-145
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• 1986

The contention resolution algorithm with the limited packet delay time as well stable distribution as the packet delay time is proposed and implementes for improving the mean packet delay time in the network employing CSMA/CD as the access method. The implementation of node controller is based on IEEE 802.2 standard logical link control(LLC) and IEEE 802.3 standard medium access control(MAC). Some portion of IEEE 802.3 Standard MAC, and the Binary Exponential Back-off(BEB) algorithm is replaced by the proposed algorithm. From the view of normalized mean packet transmission delay time, the controller implemented here can be applicable to the office-automation system, and the factory-and laboratory-automation environment where the limited time criterion is very significant.

• The Journal of the Korea Contents Association
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• v.9 no.4
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• pp.364-371
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• 2009

We analyzed romance of the three kingdoms written by Luo Guanzhong by using complex network to compare its properties with those of social network. The three kingdom network has a scale free and hierarchical network properties. Human-human interaction networks are dramatically changing in response to time and space. Due to lack of the dynamic interacting data, the researches only focus to analysis for properties of the statical networks. The romance of the three kingdoms is a Chinese historical novel based upon events from the end of the Han Dynasty, the Three Kingdoms era of China, and the reunification of the land. There are over a thousand characters, over a three thousand human-human interactions, and the dynamic changed in human-human interactions in the historical novel. Here, we introduce that a possible method for analyzing about dynamic changing of the complex network.

• Journal of Digital Contents Society
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• v.15 no.6
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• pp.663-673
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• 2014

The WBAN technology means a short distance wireless network which provides each device interactive communication by connecting devices inside and outside of body. Standardization on the physical layer, data link layer, network layer and application layer is in progress by IEEE 802.15.6 TG BAN. Wireless body area network is usually configured in energy efficient using sensor and zigbee device due to the power limitation and the characteristics of human body. Wireless sensor network consist of sensor field and sink node. Sensor field are composed a lot of sensor node and sink node collect sensing data. Wireless sensor network has capacity of the self constitution by protocol where placed in large area without fixed position. In this paper, we proposed the efficient addressing scheme for improving the performance of routing algorithm by using ZigBee in WBAN environment. A distributed address allocation scheme used an existing algorithm that has wasted in address space. Therefore proposing x, y and z coordinate axes from divided address space of 16 bit to solve this problems. Each node was reduced not only bitwise but also multi hop using the coordinate axes while routing than Cskip algorithm. I compared the performance between the standard and the proposed mechanism through the numerical analysis. Simulation verified performance about decrease averaging multi hop count that compare proposing algorithm and another. The numerical analysis results show that proposed algorithm reduced the multi hop better than ZigBee distributed address assignment

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.2
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• pp.39-57
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• 2018

The purpose of this study was to construct an artificial intelligence model that learns and estimates the relationship between vehicle queue length and link travel time in urban areas. The vehicle queue length estimation model is modeled by three models. First of all, classify whether vehicle queue is a link overflow and estimate the vehicle queue length in the link overflow and non-overflow situations. Deep learning model is implemented as Tensorflow. All models are based DNN structure, and network structure which shows minimum error after learning and testing is selected by diversifying hidden layer and node number. The accuracy of the vehicle queue link overflow classification model was 98%, and the error of the vehicle queue estimation model in case of non-overflow and overflow situation was less than 15% and less than 5%, respectively. The average error per link was about 12%. Compared with the detecting data-based method, the error was reduced by about 39%.

• The Journal of Korean Association of Computer Education
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• v.17 no.6
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• pp.103-113
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• 2014

This study designed and implemented a query model for consecutive analyses of dynamic multivariate graph data. First, the query model consists of two procedures; setting the discriminant function, and determining an alteration method. Second, the query model was implemented as a query system that consists of a query panel, a graph visualization panel, and a property panel. A Node-Link Diagram and the Force-Directed Graph Drawing algorithm were used for the visualization of the graph. The results of the queries are visually presented through the graph visualization panel. Finally, this study used the data of worldwide import & export data of small arms to verify our model. The significance of this research is in the fact that, through the model which is able to conduct consecutive analyses on dynamic graph data, it helps overcome the limitations of previous models which can only perform discrete analysis on dynamic data. This research is expected to contribute to future studies such as online decision making and complex network analysis, that use dynamic graph models.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.6
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• pp.1153-1160
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• 2021

This paper proposes a routing algorithm that determines the optimal path using deep reinforcement learning in software-defined networks. The deep reinforcement learning model for learning is based on DQN, the inputs are the current network state, source, and destination nodes, and the output returns a list of routes from source to destination. The routing task is defined as a discrete control problem, and the quality of service parameters for routing consider delay, bandwidth, and loss rate. The routing agent classifies the appropriate service class according to the user's quality of service profile, and converts the service class that can be provided for each link from the current network state collected from the SDN. Based on this converted information, it learns to select a route that satisfies the required service level from the source to the destination. The simulation results indicated that if the proposed algorithm proceeds with a certain episode, the correct path is selected and the learning is successfully performed.