• Management Science and Financial Engineering
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• v.12 no.2
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• pp.37-62
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• 2006

This paper considers the problem of designing logical tunnels in virtual private networks considering QoS guarantee which restricts the number of tunnel hops for each traffic routing. The previous researches focused on the design of logical tunnel itself and Steiner-tree based solution algorithms were proposed. However, we show that for some objective settings it is not sufficient and is necessary to consider both physical and logical connectivity at the same time. Thereupon, the concept of the layered network is applied to the logical tunnel design problem in virtual private networks. The layered network approach considers the design of logical tunnel as well as its physical routing and we propose a modified branch-and-price algorithm which is known to solve layered network design problems effectively. To show the performance of the proposed algorithm, computational experiments have been done and the results show that the proposed algorithm solves the given problem efficiently and effectively.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.27 no.1
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• pp.124-130
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• 2023

In this paper, we intend to improve the network lifetime by improving the energy efficiency of sensor nodes in a wireless sensor network by utilizing machine learning using K-means clustering algorithm. A wireless sensor network is a wireless network composed of physical devices including batteries as physical sensors. Due to the characteristics of sensor nodes, all resources must be efficiently used to minimize energy consumption to maximize network lifetime. A cluster based approach is used to manage groups of relatively large numbers of nodes. In the proposed protocol, by improving the existing LEACH algorithm, we propose a clustering algorithm that selects a cluster head using a cluster based approach and a location based approach. The performance results to be improved were measured using Matlab simulation. Through the experimental results, K-means clustering was applied to the energy efficiency part. By utilizing K-means, it is confirmed that energy efficiency is improved and the lifetime of the entire network is extended.

• Journal of Internet Computing and Services
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• v.8 no.5
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• pp.21-33
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• 2007

An overlay network is a virtual network which is constructed on top of a physical computer network. A node in the overlay network is connected through virtual or logical links, where each link corresponds to a path of the links in the underlying physical network. Overlay networks are suitable for sharing heterogeneous resources in distributed environments, However, overlay networks are limited for achieving reliable communication that failure detection in overlay networks is a very important issue. In this paper, we review conditions of conventional failure detection and propose a new approach to failure detection and resilience which can be applied to HRing (Hierarchical Ring) overlay networks. The proposed method consists of the failure detection and the failure resilience phases. Because it utilizes the characteristics of the HRing overlay network for failure detection, it can reduce unnecessary network traffic and provide better scalability and flexibility. We also analyzed and evaluated the performance of the proposed approach through simulations.

• Journal of KIISE
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• v.44 no.7
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• pp.719-725
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• 2017

To reduce management costs and improve performance, the European Telecommunication Standards Institute (ETSI) introduced the concept of network function virtualization (NFV), which can implement network functions (NFs) on cloud/datacenters. Within the NFV architecture, NFs can share physical resources by hosting NFs on physical nodes (commodity servers). For network service providers who support NFV architectures, an efficient resource allocation method finds utility in being able to reduce operating expenses (OPEX) and capital expenses (CAPEX). Thus, in this paper, we analyzed the network service chain embedding problem via an optimization formulation and found a close-optimal solution based on the Markov approximation framework. Our simulation results show that our approach could increases on average CPU utilization by up to 73% and link utilization up to 53%.

• Journal of Korean Public Health Nursing
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• v.29 no.3
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• pp.488-502
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• 2015

Purpose: This study was conducted to determine the neighborhood environmental factors associated with physical activity among adults living in rural communities. Methods: A cross-sectional descriptive survey was conducted with a convenience sample of 201 adults living in three Ri in Y-city, Gyeonggi-do. Data were collected from face-to-face interview by trained interviewers and were analyzed using a zero-inflated negative binominal regression model. Results: Participants reported engaged in moderate or vigorous physical activity was 76.1%; 10.5% of participants reported that they met moderate physical activity recommendations and 14.5% of participants reported that they met vigorous physical activity recommendations. Zero-inflated negative binominal regression analysis showed association of increasing days of physical activity with social cohesion (${\beta}=.130$, p=.005), social network (${\beta}=-.096$, p=.003), and safety for crime (${\beta}=-.151$, p=.036), and no days of physical activity was associated with no attainment of education and marginally associated with increasing BMI. Conclusion: Neighborhood environmental factors including social cohesion, social network, and crime for safety were significantly associated with physical activity of rural adults. Community health nurses should expand an approach for individual behavior change to incorporate rural adults' specific neighborhood environmental factors into physical activity interventions.

• Biotechnology and Bioprocess Engineering:BBE
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• v.11 no.1
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• pp.67-71
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• 2006

This paper compares regression and neural network modeling approaches to predict competitive biosorption equilibrium data. The regression approach is based on the fitting of modified Langmuir-type isotherm models to experimental data. Neural networks, on the other hand, are non-parametric statistical estimators capable of identifying patterns in data and correlations between input and output. Our results show that the neural network approach outperforms traditional regression-based modeling in correlating and predicting the simultaneous uptake of copper and cadmium by a microbial biosorbent. The neural network is capable of accurately predicting unseen data when provided with limited amounts of data for training. Because neural networks are purely data-driven models, they are more suitable for obtaining accurate predictions than for probing the physical nature of the biosorption process.

• Journal of the Korean Society of Systems Engineering
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• v.19 no.2
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• pp.18-31
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• 2023

Exploring artificial intelligence and machine learning for nuclear safety has witnessed increased interest in recent years. To contribute to this area of research, a machine learning model capable of accurately predicting nuclear power plant response with minimal computational cost is proposed. To develop a robust machine learning model, the Best Estimate Plus Uncertainty (BEPU) approach was used to generate a database to train three models and select the best of the three. The BEPU analysis was performed by coupling Dakota platform with the best estimate thermal hydraulics code RELAP/SCDAPSIM/MOD 3.4. The Code Scaling Applicability and Uncertainty approach was adopted, along with Wilks' theorem to obtain a statistically representative sample that satisfies the USNRC 95/95 rule with 95% probability and 95% confidence level. The generated database was used to train three models based on Recurrent Neural Networks; specifically, Long Short-Term Memory, Gated Recurrent Unit, and a hybrid model with Long Short-Term Memory coupled to Convolutional Neural Network. In this paper, the System Engineering approach was utilized to identify requirements, stakeholders, and functional and physical architecture to develop this project and ensure success in verification and validation activities necessary to ensure the efficient development of ML meta-models capable of predicting of the nuclear power plant response.

• Journal of Satellite, Information and Communications
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• v.12 no.3
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• pp.50-53
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• 2017

Satellite communications are vulnerable to malicious eavesdroppers and interceptors due to wide coverage and broadcasting applications. However, technologies for securing satellite networks have yet to be more articulated beyond high-layer packet encryption. As attempts for jamming and spoofing attacks spread out, it is extremely critical to invest on the development of physical layer security solutions. In this paper, we review current technologies for satellite communication network security both in high and physical layers. We also present recent research results on physical layer security in the fields of information theory and wireless networks. We suggest a future direction for satellite communication security, including a cross-layer approach.

• Information and Communications Magazine
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• v.24 no.2
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• pp.64-73
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• 2007

Recently, cross-layer design approach has been greatly attracting researchers' attention as an alternative for improving the performance of wireless data networks. The main reason why cross-layer approaches are particularly well suited for wireless networks is that there exists direct coupling between physical layer and upper layers. Therefore, with cross-layer approach, the protocol designers try to exploit the interaction between layers and promote adaptability at all layers, based on information exchange between layers. In this article we focus on the cross-layer engineering for high data-rate mobile Internet services through cellular networks. First, the general considerations in cross-layer engineering are outlined. Then, we discuss the common approach in literatures, which mainly deals with adaptability in physical and medium access control layer. Finally, we show that the cross-layer engineering taking account of all layers is more adequate for the mobile Internet services cellular network.

• Journal of Communications and Networks
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• v.14 no.6
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• pp.653-661
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• 2012

High-availability seamless redundancy (HSR) is a redundancy protocol for Ethernet networks that provides two frame copies for each frame sent. Each copy will pass through separate physical paths, pursuing zero fault recovery time. This means that even in the case of a node or a link failure, there is no stoppage of network operations whatsoever. HSR is a potential candidate for the communications of a smart grid, but its main drawback is the unnecessary traffic created due to the duplicated copies of each sent frame, which are generated and circulated inside the network. This downside will degrade network performance and might cause network congestion or even stoppage. In this paper, we present two approaches to solve the above-mentioned problem. The first approach is called quick removing (QR), and is suited to ring or connected ring topologies. The idea is to remove the duplicated frame copies from the network when all the nodes have received one copy of the sent frame and begin to receive the second copy. Therefore, the forwarding of those frame copies until they reach the source node, as occurs in standard HSR, is not needed in QR. Our example shows a traffic reduction of 37.5%compared to the standard HSR protocol. The second approach is called the virtual ring (VRing), which divides any closed-loop HSR network into several VRings. Each VRing will circulate the traffic of a corresponding group of nodes within it. Therefore, the traffic in that group will not affect any of the other network links or nodes, which results in an enhancement of traffic performance. For our sample network, the VRing approach shows a network traffic reduction in the range of 67.7 to 48.4%in a healthy network case and 89.7 to 44.8%in a faulty network case, compared to standard HSR.