• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.8
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• pp.1490-1494
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• 2006

Most network equipment is an embedded system designed to execute specific function. An embedded system is an electronic control system mixing hardware and software to execute only fixed function for the purpose of system, not confuter, performing diverse function for a wide use. Early embedded system executed only simple function, combining specific function with optimization, a micro size, and low power, but it has developed to meet complex and diverse system. The purpose of this study is to realize DHCP server based on embedded system. To achieve this, embedded Linux was ported in ez Bord-M01 mounted with Intel Strong ARM SA1110 processor, and ethernet-based network was constructed for network function. In this way, this study suggests embedded DHCP server where Window and Linux client hosts are dynamically configurated as network information by dynamically assigning network information in embedded board.

• The KIPS Transactions:PartB
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• v.18B no.5
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• pp.271-278
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• 2011

Storm and flood such as torrential rains and major typhoons has often caused damages on a large scale in Korea and damages from storm and flood have been increasing by climate change and warming. Therefore, it is an essential work to maneuver preemptively against risks and damages from storm and flood by predicting the possibility and scale of the disaster. Generally the research on numerical model based on statistical methods, the KDF model of TCDIS developed by NIDP, for analyzing and predicting disaster risks and damages has been mainstreamed. In this paper, we introduced the model for prediction of damage cost from storm and flood by the neural network algorithm which outstandingly implements the pattern recognition. Also, we compared the performance of the neural network model with that of KDF model of TCDIS. We come to the conclusion that the robustness and accuracy of prediction of damage cost on TCDIS will increase by adapting the neural network model rather than the KDF model.

• Journal of Korean Society of Transportation
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• v.31 no.4
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• pp.3-17
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• 2013

The purpose of this study is to develop a traffic assignment model where the variable of signal intersection delay is taken into account in assigning traffic in large-scale network settings. Indeed, despite the fact that the majority of the increase in travel time or cost involving congested urban network or interrupted flow are accounted for by stop delays or congested delays at signal intersections, the existing traffic assignment models did not reflect this. The traffic assignment model considering intersection delays presented in this study was built based on the existing traffic assignment models, which were added to by the analysis technique for the computation of intersection delay provided in Korea Highway Capacity Manual. We can conclude that a multiple variety of simulation tests prove that this model can be applied to real network settings. Accordingly, this model shows the possibility of utilizing a model considering intersection delay for traffic policy decisions through analysis of effects of changes in traffic facilities on large urban areas.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.4
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• pp.159-167
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• 2018

In this paper, we propose an algorithm to optimize energy efficiency in a multi-user decoupled RF energy harvesting network and experiment on the trend of energy efficiency change assuming users' various geographical distribution scenarios. In the RF energy harvesting network where both wireless data transmission and RF energy harvesting are simultaneously performed, the energy efficiency is a key indicator of network performance, and it is necessary to investigate how various factors can affect the energy efficiency. In order to increase energy efficiency effectively, we can confirm that users' distributions are important factors in the RF energy harvesting network from the simulation results.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2004.11a
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• pp.317-322
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• 2004

As a construction project in urban area tends to be high-rise and huge, the importance of the project's underground work, in terms of the cost and the schedule, is gradually increasing. It's extremely significant to choose a proper filing method, at the stage of underground work. However, in piling work many change orders have been occurred since a piling method is experientially selected based on uncertain information and many earth factors to consider. It has effects on the cost and the schedule of the project. In this study, we have suggested a decision model for piling method that can be used to determine and verify the suitable piling method in design and pre-construction phase of a project. Based on historical data, a neural network model has already proven to be efficient. The tests of the model for selecting a suitable piling method have progressed exactly with the data of 150 piling works which were done room 2000 to 2004 in Korea. The optimization or the developed neural network model has progressed with the data for teaming. The validity of the neural network model has been verified.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.44 no.3
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• pp.37-42
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• 2007

This paper reconsiders established power conservation models for ubiquitous sensor networks that use relay nodes instead of direct communication and proposes novel network power consumption model with consideration of the channel level and radio chip level simultaneously. We estimate the effect of minimum hop-count policy in terms of network power consumption through simulation of various situations for low power RF module CC2420. It is observed that maximum RF power and minimum hop-count results in lower energy consumption relatively. Also, in total network energy consumption, which is included re-transmission, minimum hop count policy presents decrease by 33.1% of energy consumption in compare with the conventional model.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37B no.12
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• pp.1102-1112
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• 2012

We propose a cell selection and resource allocation scheme that assigns users to nearby accessible cells in heterogeneous wireless networks consisting of macrocell, femtocells, and Wi-Fi access points, under overload situation. Given the current power level of all accessible cells nearby users, the proposed scheme finds all possible cell assignment mappings of which user should connect to which cell to maximize the number of users that the network can accommodate at the same time. We formulate the cell selection problem with heterogeneous cells into an optimization problem of binary integer programming, and compute the optimal solution. We evaluate the proposed algorithm in terms of network access failure compared to a local ad-hoc based cell selection scheme used in practical systems using network level simulations. We demonstrate that our cell selection algorithm dramatically reduces network access failure in overload situation by fully leveraging network resources evenly across heterogeneous networks. We also validate the practical feasibility in terms of computational complexity of our binary integer program by measuring the computation time with respect to the number of users.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.2 no.1
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• pp.23-35
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• 2008

Mobile IP (MIP) is the solution supporting the mobility of Mobile Nodes (MNs), however, it is known to lack the support for NEtwork MObility (NEMO). NEMO manages situations when an entire network, composed of one or more subnets, dynamically changes its point of attachment to the Internet. NEMO Basic Support (NBS) protocol ensures session continuity for all the nodes in a mobile network, however, there exists a serious pinball routing problem. To overcome this weakness, there are many Route Optimization (RO) solutions such as Bi-directional Tunneling (BT) mechanism, Aggregation and Surrogate (A&S) mechanism, Recursive Approach, etc. The A&S RO mechanism is known to outperform the other RO mechanisms, except for the Binding Update (BU) cost. Although Improved Prefix Delegation (IPD) reduces the cost problem of Prefix Delegation (PD), a well-known A&S protocol, the BU cost problem still presents, especially when a large number of Mobile Routers (MRs) and MNs exist in the environment such as train, bus, ship, or aircraft. In this paper, a solution to reduce the cost of delivering the BU messages is proposed using a multicast mechanism instead of unicasting such as the traditional BU of the RO. The performance of the proposed multicast-based BU scheme is examined with an analytical model which shows that the BU cost enhancement is up to 32.9% over IPDbased, hence, it is feasible to predict that the proposed scheme could benefit in other NEMO RO protocols.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.1
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• pp.1-8
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• 2018

Recently, the convolutional neural network shows high performance in many computer vision tasks. However, convolutional neural networks require enormous amount of operation, so it is difficult to adopt them in the embedded environments. To solve this problem, many studies are performed on the ASIC or FPGA implementation, where an efficient representation method is required. The fixed-point representation is adequate for the ASIC or FPGA implementation but causes a performance degradation. This paper proposes a separate optimization of representations for the convolutional layers and the batch normalization layers. With the proposed method, the required bit width for the convolutional layers is reduced from 16 bits to 10 bits for the ResNet-50 neural network. Since the computation amount of the convolutional layers occupies the most of the entire computation, the bit width reduction in the convolutional layers enables the efficient implementation of the convolutional neural networks.

• KIPS Transactions on Computer and Communication Systems
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• v.1 no.2
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• pp.99-102
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• 2012

The performance of P2P application services may be improved by reducing unnecessary inter-network traffic through intelligent peer selection. However, since a logical link between peers in a P2P overlay network is composed of a set of physical links in an underlay network, the traffic pattern determined by the sending rates of selected peers imposes loads on each underlay links. Thus, if the sending rates are not determined carefully, the loads between underlay links may not be balanced, which means some links are underloaded while the other links are congested. In this paper, we take an optimization approach to determine the sending rates of peers strategically to avoid the inefficient use of underlay links. The proposed scheme also guarantee the minimum receiving rates of peers while minimizing the maximum link utilization of underlay links, which is beneficial both to P2P applications and an underlay network.