• KIPS Transactions on Computer and Communication Systems
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• v.3 no.1
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• pp.7-14
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• 2014

The rapid increase of mobile devices such as smart phone and smart pad have raised the needs for seamless multimedia services during moving at anytime and anywhere. Current 4G mobile devices are equipped with both 4G (LTE) and WLAN (WiFi) interfaces, and mobile services operators provide wireless Internet services using 4G network with a wider coverage and WiFi zone. Generally users prefer to use the Internet services through WLAN rather than LTE in the coverage of WLAN. However, since WLAN has a long L2 handover latency, it is difficult to support seamless services during a handover. In this paper, we proposed an efficient handover scheme based on flow mobility for WLANs to support a seamless service during handovers by using the overlaid 4G network with a wider coverage. Also, we showed the outperformance of the proposed scheme on a testbed.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.3
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• pp.427-432
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• 2023

In this study, MEC (: Multi-access Edge Computing) proposes a cloud service network configuration for various tests of autonomous vehicles to which V2X (: Vehicle to Everything) is applied in Wave, LTE, and 5G networks and MEC App (: Application) applied V2X service function test verification of two domains (operator (KT, SKT, LG U+), network type (Wave, LTE (including 3G), 5G)) in a specific region. In 4G networks of domestic operators (SKT, KT, LG U+ and Wave), MEC summarized the improvement effects through V2X function blocks and traffic offloading for the purpose of bringing independent network functions. And with a high level of QoS value in the V2X VNF of the 5G network, the traffic steering function scenario was demonstrated on the destination-specific traffic path.

• Journal of Korea Multimedia Society
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• v.16 no.7
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• pp.897-904
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• 2013

The recursive circulant network G(N,d) can be widely used in the design and implementation of parallel processing architectures. It consists of N identical nodes, each node is connected through bidirectional, point-to-point communication channels to different neighbors by jumping $d^i$, where $0{\leq}i{\leq}{\lceil}{\log}_dN{\rceil}$ - 1. In this paper, we investigate the routing of a message on $G(2^m,4)$, a special kind of RCN, that is key to the performance of this network. On $G(2^m,4)$ we would like to transmit k packets from a source node to k destination nodes simultaneously along paths on this network, the $i^{th}$ packet will be transmitted along the $i^{th}$ path, where $1{\leq}k{\leq}m-1$, $0{{\leq}}i{{\leq}}m-1$. In order for all packets to arrive at a destination node quickly and securely, we present an $O(m^4)$ routing algorithm on $G(2^m,4)$ for generating a set of one-to-many node-disjoint and nearly shortest paths, where each path is either shortest or nearly shortest and the total length of these paths is nearly minimum since the path is mainly determined by employing the Hungarian method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.186-188
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• 2014

In recent years, domestic as well as LTE wireless network of Wi-Fi and most used. In addition, mobile-intensive services that used mainly in our society makes it easier, SNS, application (APP), and file downloads. As such, the amount of data requested, while living at the time of mobile users will want to be safe from the earliest. And the wireless network communications mortality (3G, 4G (LTE), LTE-A) and Wi-Fi (802.11 n-2.4 G H z z H a c-5, 802.11 G), and users are mainly used in the death 4G (LTE), communication Wi-Fi, 802.11 n-2.4 GHz are used most frequently. As above, use the wireless network in order to safely and quickly developed the technology of the Li-Fi. Li-Fi light (visible light) technology to communicate with, and Wi-Fi (802.11 n-2.4 G z H) 100 times faster, LTE-A 66 times faster. However, the current Li-Fi to commercialise the big issue exists. In this paper, there are a lot of existing problems in the commercialization of Li-Fi being used in Wi-Fi, and a comparative analysis.

• The Journal of Korea Robotics Society
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• v.17 no.2
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• pp.118-123
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• 2022

We implemented a real-time cloud robotics application by offloading robot navigation engine over to 5G Mobile Edge Computing (MEC) sever. We also ran a fleet management system (FMS) in the server and controlled the movements of multiple robots at the same time. The mobile robots under the test were connected to the server through 5G SA network. Public 5G network, which is already commercialized, has been temporarily modified to support this validation by the network operator. Robot engines are containerized based on micro-service architecture and have been deployed using Kubernetes - a container orchestration tool. We successfully demonstrated that mobile robots are able to avoid obstacles in real-time when the engines are remotely running in 5G MEC server. Test results are compared with 5G Public Cloud and 4G (LTE) Public Cloud as well.

• Journal of Broadcast Engineering
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• v.13 no.1
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• pp.25-33
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• 2008

Video telephony is a representative service in 3G mobile network. And there have been efforts to improve quality of video telephony service in different fields. In Korea, the leading mobile service provider SKTelecom and KTF service the WCDMA network as 3G mobile network. Now, more than a million people is using the network. In this paper, we study about video telephony over WCDMA network. and propose error minimizing algorithm using cross-layer adaptation between physical layer and video codec. We simulated 3G-324M protocol with MPEG-4 video codec, and simulation results show suggested algorithm improve packet transmission rate for improving quality of video telephony service.

• Journal of IKEEE
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• v.27 no.4
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• pp.617-623
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• 2023

With the evolution of communication networks, there is a growing demand for stable high-speed data connections to support services relying on large-capacity data. The increasing volume of packet data aggregated from user devices underscores the significance of quality diagnostics for the backhaul network, an intermediate link transmitting data to the core network. This paper conducts empirical research on techniques to diagnose issues within the backhaul network through practical case studies, through diagnosing various factors such as circuit bandwidth, speed disparities within switches, network segment-specific buffer sizes, routing policies, among other factors that could potentially cause RTT (Round Trip Time) delays and performance degradation.

• Journal of Convergence for Information Technology
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• v.10 no.7
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• pp.1-6
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• 2020

A new resource management algorithm is proposed for 5G networks which have a coordinated network architecture. By sharing the contol information among multiple neighbor cells and managing in centralized structure, the propsed algorithm fully utilizes the benefits of network coordination to increase fairness and throughput at the same time. This optimization of network performance is achieved while operating within a tolerable amount of signaling overhead and computational complexity. Simulation results confirm that the proposed scheme improve the network capacity up to 40% for cell edge users and provide network-wise fairness as much as 23% in terms of the well-knwon Jain's Fainess Index.

• ETRI Journal
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• v.46 no.2
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• pp.205-217
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• 2024

We propose a bandwidth prediction approach based on deep learning. The approach is intended to accurately predict the bandwidth of various types of mobile networks. We first use a machine learning technique, namely, the gradient boosting algorithm, to recognize the connected mobile network. Second, we apply a handover detection algorithm based on network recognition to account for vertical handover that causes the bandwidth variance. Third, as the communication performance offered by 3G, 4G, and 5G networks varies, we suggest a bidirectional long short-term memory model with time distribution for bandwidth prediction per network. To increase the prediction accuracy, pretraining and fine-tuning are applied for each type of network. We use a dataset collected at University College Cork for network recognition, handover detection, and bandwidth prediction. The performance evaluation indicates that the handover detection algorithm achieves 88.5% accuracy, and the bandwidth prediction model achieves a high accuracy, with a root-mean-square error of only 2.12%.

• Smart Media Journal
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• v.13 no.4
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• pp.33-48
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• 2024

With the advent of 5G, characterized by Enhanced Mobile Broadband (eMBB), Ultra-Reliable Low Latency Communications (URLLC), and Massive Machine Type Communications (mMTC), efficient network management and service provision are becoming increasingly critical. This paper proposes a novel approach to address key challenges of 5G networks, namely ultra-high speed, ultra-low latency, and ultra-reliability, while dynamically optimizing network slicing and resource allocation using machine learning (ML) and deep learning (DL) techniques. The proposed methodology utilizes prediction models for network traffic and resource allocation, and employs Federated Learning (FL) techniques to simultaneously optimize network bandwidth, latency, and enhance privacy and security. Specifically, this paper extensively covers the implementation methods of various algorithms and models such as Random Forest and LSTM, thereby presenting methodologies for the automation and intelligence of 5G network operations. Finally, the performance enhancement effects achievable by applying ML and DL to 5G networks are validated through performance evaluation and analysis, and solutions for network slicing and resource management optimization are proposed for various industrial applications.