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Dr. Youn-Hee Han
School of Computer Science and Engineering, Korea University of Technology and Education, Chungnam, Korea

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Research Keywords & Expertise

0 Reinforcement Learning
0 Smart Cities
0 Sensor and actuator networks
0 Mobile sensor networks
0 Intelligent IoT and CPS systems

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Reinforcement Learning
Mobile sensor networks

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Journal article
Published: 12 June 2021 in Future Generation Computer Systems
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The patient’s heterogeneous data in IoT-based healthcare system are gathered using various sensor nodes. the existing healthcare and monitoring systems are mostly based on ontology or type-1 fuzzy logic which is insufficient due to inconsistency and uncertainty in the sensed data. in this paper a novel data fusion scheme is proposed which is based on type-2 fuzzy logic (T2FL) incorporated with Dempster–Shafer theory (DST) to extract precise information and correctly infer the result. in the proposed scheme the membership values of the patient data are effectively decided by type-2 fuzzy logic, and the evidence obtained from the membership values are properly fused and processed by the DST in the decision-making system. extensive computer simulation with heart disease and diabetes dataset reveals that the proposed scheme considerably outperforms the existing schemes based on ontology and type-1 fuzzy logic with respect to the decision accuracy.

ACS Style

Ihsan Ullah; Hee Yong Youn; Youn-Hee Han. Integration of type-2 fuzzy logic and Dempster-Shafer Theory for accurate inference of IoT-based health-care system. Future Generation Computer Systems 2021, 124, 369 -380.

AMA Style

Ihsan Ullah, Hee Yong Youn, Youn-Hee Han. Integration of type-2 fuzzy logic and Dempster-Shafer Theory for accurate inference of IoT-based health-care system. Future Generation Computer Systems. 2021; 124 ():369-380.

Chicago/Turabian Style

Ihsan Ullah; Hee Yong Youn; Youn-Hee Han. 2021. "Integration of type-2 fuzzy logic and Dempster-Shafer Theory for accurate inference of IoT-based health-care system." Future Generation Computer Systems 124, no. : 369-380.

Journal article
Published: 25 May 2021 in IEEE Access
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Nowadays, Reinforcement Learning (RL) is applied to various real-world tasks and attracts much attention in the fields of games, robotics, and autonomous driving. It is very challenging and devices overwhelming to directly apply RL to real-world environments. Due to the reality gap simulated environment does not match perfectly to the real-world scenario and additional learning cannot be performed. Therefore, an efficient approach is required for RL to find an optimal control policy and get better learning efficacy. In this paper, we propose federated reinforcement learning based on multi agent environment which applying a new federation policy. The new federation policy allows multi agents to perform learning and share their learning experiences with each other e.g., gradient and model parameters to increase their learning level. The Actor-Critic PPO algorithm is used with four types of RL simulation environments, OpenAI Gym’s CartPole, MoutainCar, Acrobot, and Pendulum. In addition, we did real experiments with multiple Rotary Inverted Pendulum (RIP) to evaluate and compare the learning efficiency of the proposed scheme with both environments.

ACS Style

Hyun-Kyo Lim; Ju-Bong Kim; Ihsan Ullah; Joo-Seong Heo; Youn-Hee Han. Federated Reinforcement Learning Acceleration Method for Precise Control of Multiple Devices. IEEE Access 2021, 9, 76296 -76306.

AMA Style

Hyun-Kyo Lim, Ju-Bong Kim, Ihsan Ullah, Joo-Seong Heo, Youn-Hee Han. Federated Reinforcement Learning Acceleration Method for Precise Control of Multiple Devices. IEEE Access. 2021; 9 ():76296-76306.

Chicago/Turabian Style

Hyun-Kyo Lim; Ju-Bong Kim; Ihsan Ullah; Joo-Seong Heo; Youn-Hee Han. 2021. "Federated Reinforcement Learning Acceleration Method for Precise Control of Multiple Devices." IEEE Access 9, no. : 76296-76306.

Journal article
Published: 02 March 2021 in IEEE Access
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Multisensor data fusion is extensively used to merge data from heterogeneous sensors in a smart environment. However, sensors provide noisy and uncertain information which is a big challenge for researchers. Since uncertainty in the data is a central constraint for data fusion and decision-making systems. Dempster-Shafer’s evidence theory is an appropriate method for modeling and fusing uncertain information. In this paper, a novel data fusion scheme is proposed based on the modified belief entropy of the basic probability assignments (BPAs) to quantify the uncertainty in the information and fused them by Dempster-Shafer evidence theory. The proposed DFUDS (data fusion based on measuring uncertainty in Dempster-Shafer) scheme considers the available redundant information in the body of evidence (BoEs). The BoEs obtained from the sensor data are processed by proposed belief entropy, and fuse all pieces of evidence by Dempster’s rule of combination to transfer the conflicting data into decision-making results. Extensive computer simulation results show that the proposed scheme outperforms in terms of the degree of uncertainty, evidence, reasoning, and decision accuracy under active contexts of the smart environment.

ACS Style

Ihsan Ullah; Joosang Youn; Youn-Hee Han. Multisensor Data Fusion Based on Modified Belief Entropy in Dempster–Shafer Theory for Smart Environment. IEEE Access 2021, 9, 37813 -37822.

AMA Style

Ihsan Ullah, Joosang Youn, Youn-Hee Han. Multisensor Data Fusion Based on Modified Belief Entropy in Dempster–Shafer Theory for Smart Environment. IEEE Access. 2021; 9 ():37813-37822.

Chicago/Turabian Style

Ihsan Ullah; Joosang Youn; Youn-Hee Han. 2021. "Multisensor Data Fusion Based on Modified Belief Entropy in Dempster–Shafer Theory for Smart Environment." IEEE Access 9, no. : 37813-37822.

Original research
Published: 08 January 2021 in Journal of Ambient Intelligence and Humanized Computing
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Wireless sensor network (WSN) is used for data collection and transmission in IoT environment. Since it consists of a large number of sensor nodes, a significant amount of redundant data and outliers are generated which substantially deteriorate the network performance. Data aggregation is needed to reduce energy consumption and prolong the lifetime of WSN. In this paper a novel data aggregation scheme is proposed which is based on modified radial basis function neural network to classify the collected data at cluster head and eliminate the redundant data and outliers. Additionally, cosine similarity is used to cluster the nodes having the most similar data. The radial basis function (RBF) is adapted by Mahalanobis distance to support the outlier’s detection and analysis in the multivariate data. The data collected from the sensor node at the cluster head are processed by mahalanbis distance-based radial basis function neural network (MDRBF-NN) before transferred to the based station. Extensive computer simulation with real datasets shows that the proposed scheme consistently outperforms the existing representative data aggregation schemes in terms of data classification, outlier detection, and energy efficiency.

ACS Style

Ihsan Ullah; Hee Yong Youn; Youn-Hee Han. An efficient data aggregation and outlier detection scheme based on radial basis function neural network for WSN. Journal of Ambient Intelligence and Humanized Computing 2021, 1 -17.

AMA Style

Ihsan Ullah, Hee Yong Youn, Youn-Hee Han. An efficient data aggregation and outlier detection scheme based on radial basis function neural network for WSN. Journal of Ambient Intelligence and Humanized Computing. 2021; ():1-17.

Chicago/Turabian Style

Ihsan Ullah; Hee Yong Youn; Youn-Hee Han. 2021. "An efficient data aggregation and outlier detection scheme based on radial basis function neural network for WSN." Journal of Ambient Intelligence and Humanized Computing , no. : 1-17.

Journal article
Published: 27 August 2020 in Sensors
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With the exponential growth of Cyber-Physical Systems (CPSs) technologies, the Internet of Things (IoT) infrastructure has evolved from built-in static infrastructure to a flexible structure applicable to various mobile environments. In this Internet of Mobile Things (IoMT) environment, each IoT device could operate simultaneously as a provider and consumer of information, and could provide new services through the exchange of such information. Named Data Networking (NDN), which could request data by content name rather than location (IP address), is suitable for such mobile IoT environments. However, in the current Named Data Networking (NDN) specification, producer mobility is one of the major problems in need of remedy. Previously proposed schemes for producer mobility use an anchor to hide the producer’s movement from consumers. As a result, they require a special anchor node and a signaling procedure to track the current locations of contents. A few anchorless schemes have also been proposed, but they still require mobility signaling and all NDN routers on the signaling path must understand the meaning of the signaling. We therefore propose an anchorless producer mobility scheme for the NDN. This scheme uses a dual-connectivity strategy that can be expressed as a soft handover. Whenever a producer changes its NDN Access Router (NAR), the new mobility link service located on the mobile producer’s old NDN face repairs the old link so that the connectivity with the pNAR can be maintained for a while. The old NDN face is removed after the new location information on the contents of the producer is disseminated over the NDN network by the Named-data Link State Routing Protocol (NLSR) routing protocol at the nNAR. The new mobility link service decouples connection and transaction to hide the collapse of the link. Therefore, the NDN’s mobility procedure could be simplified as the handover is defined as transaction completion as opposed to a breakdown of links. The proposed scheme prevents the routing information from being abruptly outdated due to producer mobility. Our simulation results show seamless handover when the producer changes its default access router.

ACS Style

Ju-Ho Choi; Jung-Hwan Cha; Youn-Hee Han; Sung-Gi Min. A Dual-Connectivity Mobility Link Service for Producer Mobility in the Named Data Networking. Sensors 2020, 20, 4859 .

AMA Style

Ju-Ho Choi, Jung-Hwan Cha, Youn-Hee Han, Sung-Gi Min. A Dual-Connectivity Mobility Link Service for Producer Mobility in the Named Data Networking. Sensors. 2020; 20 (17):4859.

Chicago/Turabian Style

Ju-Ho Choi; Jung-Hwan Cha; Youn-Hee Han; Sung-Gi Min. 2020. "A Dual-Connectivity Mobility Link Service for Producer Mobility in the Named Data Networking." Sensors 20, no. 17: 4859.

Journal article
Published: 16 June 2020 in Sensors
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Intralogistics is a technology that optimizes, integrates, automates, and manages the logistics flow of goods within a logistics transportation and sortation center. As the demand for parcel transportation increases, many sortation systems have been developed. In general, the goal of sortation systems is to route (or sort) parcels correctly and quickly. We design an n-grid sortation system that can be flexibly deployed and used at intralogistics warehouse and develop a collaborative multi-agent reinforcement learning (RL) algorithm to control the behavior of emitters or sorters in the system. We present two types of RL agents, emission agents and routing agents, and they are trained to achieve the given sortation goals together. For the verification of the proposed system and algorithm, we implement them in a full-fledged cyber-physical system simulator and describe the RL agents’ learning performance. From the learning results, we present that the well-trained collaborative RL agents can optimize their performance effectively. In particular, the routing agents finally learn to route the parcels through their optimal paths, while the emission agents finally learn to balance the inflow and outflow of parcels.

ACS Style

Ju-Bong Kim; Ho-Bin Choi; Gyu-Young Hwang; Kwihoon Kim; Yong-Geun Hong; Youn-Hee Han. Sortation Control Using Multi-Agent Deep Reinforcement Learning in N-Grid Sortation System. Sensors 2020, 20, 3401 .

AMA Style

Ju-Bong Kim, Ho-Bin Choi, Gyu-Young Hwang, Kwihoon Kim, Yong-Geun Hong, Youn-Hee Han. Sortation Control Using Multi-Agent Deep Reinforcement Learning in N-Grid Sortation System. Sensors. 2020; 20 (12):3401.

Chicago/Turabian Style

Ju-Bong Kim; Ho-Bin Choi; Gyu-Young Hwang; Kwihoon Kim; Yong-Geun Hong; Youn-Hee Han. 2020. "Sortation Control Using Multi-Agent Deep Reinforcement Learning in N-Grid Sortation System." Sensors 20, no. 12: 3401.

Journal article
Published: 02 March 2020 in Sensors
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Reinforcement learning has recently been studied in various fields and also used to optimally control IoT devices supporting the expansion of Internet connection beyond the usual standard devices. In this paper, we try to allow multiple reinforcement learning agents to learn optimal control policy on their own IoT devices of the same type but with slightly different dynamics. For such multiple IoT devices, there is no guarantee that an agent who interacts only with one IoT device and learns the optimal control policy will also control another IoT device well. Therefore, we may need to apply independent reinforcement learning to each IoT device individually, which requires a costly or time-consuming effort. To solve this problem, we propose a new federated reinforcement learning architecture where each agent working on its independent IoT device shares their learning experience (i.e., the gradient of loss function) with each other, and transfers a mature policy model parameters into other agents. They accelerate its learning process by using mature parameters. We incorporate the actor–critic proximal policy optimization (Actor–Critic PPO) algorithm into each agent in the proposed collaborative architecture and propose an efficient procedure for the gradient sharing and the model transfer. Using multiple rotary inverted pendulum devices interconnected via a network switch, we demonstrate that the proposed federated reinforcement learning scheme can effectively facilitate the learning process for multiple IoT devices and that the learning speed can be faster if more agents are involved.

ACS Style

Hyun-Kyo Lim; Ju-Bong Kim; Joo-Seong Heo; Youn-Hee Han. Federated Reinforcement Learning for Training Control Policies on Multiple IoT Devices. Sensors 2020, 20, 1359 .

AMA Style

Hyun-Kyo Lim, Ju-Bong Kim, Joo-Seong Heo, Youn-Hee Han. Federated Reinforcement Learning for Training Control Policies on Multiple IoT Devices. Sensors. 2020; 20 (5):1359.

Chicago/Turabian Style

Hyun-Kyo Lim; Ju-Bong Kim; Joo-Seong Heo; Youn-Hee Han. 2020. "Federated Reinforcement Learning for Training Control Policies on Multiple IoT Devices." Sensors 20, no. 5: 1359.

Journal article
Published: 21 June 2019 in Applied Sciences
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Recently, with the advent of various Internet of Things (IoT) applications, a massive amount of network traffic is being generated. A network operator must provide different quality of service, according to the service provided by each application. Toward this end, many studies have investigated how to classify various types of application network traffic accurately. Especially, since many applications use temporary or dynamic IP or Port numbers in the IoT environment, only payload-based network traffic classification technology is more suitable than the classification using the packet header information as well as payload. Furthermore, to automatically respond to various applications, it is necessary to classify traffic using deep learning without the network operator intervention. In this study, we propose a traffic classification scheme using a deep learning model in software defined networks. We generate flow-based payload datasets through our own network traffic pre-processing, and train two deep learning models: 1) the multi-layer long short-term memory (LSTM) model and 2) the combination of convolutional neural network and single-layer LSTM models, to perform network traffic classification. We also execute a model tuning procedure to find the optimal hyper-parameters of the two deep learning models. Lastly, we analyze the network traffic classification performance on the basis of the F1-score for the two deep learning models, and show the superiority of the multi-layer LSTM model for network packet classification.

ACS Style

Hyun-Kyo Lim; Ju-Bong Kim; Yong-Geun Hong; Youn-Hee Han. Payload-Based Traffic Classification Using Multi-Layer LSTM in Software Defined Networks. Applied Sciences 2019, 9, 2550 .

AMA Style

Hyun-Kyo Lim, Ju-Bong Kim, Yong-Geun Hong, Youn-Hee Han. Payload-Based Traffic Classification Using Multi-Layer LSTM in Software Defined Networks. Applied Sciences. 2019; 9 (12):2550.

Chicago/Turabian Style

Hyun-Kyo Lim; Ju-Bong Kim; Yong-Geun Hong; Youn-Hee Han. 2019. "Payload-Based Traffic Classification Using Multi-Layer LSTM in Software Defined Networks." Applied Sciences 9, no. 12: 2550.

Research article
Published: 10 July 2018 in Wireless Communications and Mobile Computing
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Named Data Networking (NDN) supports the consumer mobility service by letting a consumer reissue an interest. This method is straightforward, but it may cause several drawbacks, including unnecessary handover overhead and long handover delay. We concentrate on the NDN communication model in which the pair of an interest and a data packet is considered a single communication working set (i.e., transaction unit). In this respect, reissuing an interest means creating a new transaction due to the connection damaged by the movement of a consumer. It makes all states of the current transaction useless, and this is where the drawbacks arise. In order to enhance the consumer mobility service, we propose Mobility Link Service (MLS) operated in NDN face which is responsible for management of a connection for a transaction. MLS reuses the existing states of a transaction by establishing a connection for the transaction instead of creating a new one. In addition, MLS in NDN face makes consumer mobility service transparent to the NDN forwarding plane. Therefore, the consumer mobility service and the NDN architecture can evolve independently. The performance evaluation shows that MLS reduces the amount of retransmitted data and handover latency compared with the existing NDN mobility solution.

ACS Style

Jung-Hwan Cha; Ju-Ho Choi; Ji-Yong Kim; Youn-Hee Han; Sung-Gi Min. A Mobility Link Service for NDN Consumer Mobility. Wireless Communications and Mobile Computing 2018, 2018, 1 -8.

AMA Style

Jung-Hwan Cha, Ju-Ho Choi, Ji-Yong Kim, Youn-Hee Han, Sung-Gi Min. A Mobility Link Service for NDN Consumer Mobility. Wireless Communications and Mobile Computing. 2018; 2018 ():1-8.

Chicago/Turabian Style

Jung-Hwan Cha; Ju-Ho Choi; Ji-Yong Kim; Youn-Hee Han; Sung-Gi Min. 2018. "A Mobility Link Service for NDN Consumer Mobility." Wireless Communications and Mobile Computing 2018, no. : 1-8.

Journal article
Published: 21 September 2017 in Sensors
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Many Internet of Things (IoT) services utilize an IoT access network to connect small devices with remote servers. They can share an access network with standard communication technology, such as IEEE 802.11ah. However, an authentication and key management (AKM) mechanism for resource constrained IoT devices using IEEE 802.11ah has not been proposed as yet. We therefore propose a new AKM mechanism for an IoT access network, which is based on IEEE 802.11 key management with the IEEE 802.1X authentication mechanism. The proposed AKM mechanism does not require any pre-configured security information between the access network domain and the IoT service domain. It considers the resource constraints of IoT devices, allowing IoT devices to delegate the burden of AKM processes to a powerful agent. The agent has sufficient power to support various authentication methods for the access point, and it performs cryptographic functions for the IoT devices. Performance analysis shows that the proposed mechanism greatly reduces computation costs, network costs, and memory usage of the resource-constrained IoT device as compared to the existing IEEE 802.11 Key Management with the IEEE 802.1X authentication mechanism.

ACS Style

Ki-Wook Kim; Youn-Hee Han; Sung-Gi Min. An Authentication and Key Management Mechanism for Resource Constrained Devices in IEEE 802.11-based IoT Access Networks. Sensors 2017, 17, 2170 .

AMA Style

Ki-Wook Kim, Youn-Hee Han, Sung-Gi Min. An Authentication and Key Management Mechanism for Resource Constrained Devices in IEEE 802.11-based IoT Access Networks. Sensors. 2017; 17 (10):2170.

Chicago/Turabian Style

Ki-Wook Kim; Youn-Hee Han; Sung-Gi Min. 2017. "An Authentication and Key Management Mechanism for Resource Constrained Devices in IEEE 802.11-based IoT Access Networks." Sensors 17, no. 10: 2170.

Conference paper
Published: 09 August 2017 in Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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A smart vehicle becomes a communication device with the advance of VANETs. In the WAVE standards, which is the well-known VANET standards, RSUs interconnect a VANETs to the Internet, and they act as default routers for the vehicles. However, the WAVE standards have eliminated the L2 portal function, which was included in the previous WAVE standards. Due to the short communication range of RSUs and vehicles’ high speed, a vehicle may have to change its point of attachment frequently. The change of the default router causes severe service interruption due to the standard IPv6 protocol’s functions such as the address auto-configuration, DAD and NUD. We propose a new seamless handover scheme with an L2 extension mechanism without any modification of the WAVE standards. It increases the coverage of an access router to multiple RSU coverage, while the frequency of the default router changes can be decreased. It also supports seamless packet delivery during the change of the points of attachment. By decoupling the RSU and the access router, the deployment of the WAVE can be more flexible. The proposed mechanism is simulated with ns-3 and its results show the effectiveness of the proposed scheme.

ACS Style

Ju-Ho Choi; Jung-Hwan Cha; Sung-Gi Min; Youn-Hee Han. A Network-Based Seamless Handover Scheme with an L2 Extension Mechanism in VANET. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2017, 199, 183 -192.

AMA Style

Ju-Ho Choi, Jung-Hwan Cha, Sung-Gi Min, Youn-Hee Han. A Network-Based Seamless Handover Scheme with an L2 Extension Mechanism in VANET. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering. 2017; 199 ():183-192.

Chicago/Turabian Style

Ju-Ho Choi; Jung-Hwan Cha; Sung-Gi Min; Youn-Hee Han. 2017. "A Network-Based Seamless Handover Scheme with an L2 Extension Mechanism in VANET." Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 199, no. : 183-192.

Conference paper
Published: 23 November 2016 in Lecture Notes in Electrical Engineering
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In order to find meaningful patterns of research trends in the computer science and engineering field, we crawl a significant amount of bibliographic information, 3 million or more scholarly papers published from 1956 to 2015. We also make a list of target key words and analyze their frequency rate over the past 60 years based on the terms extracted from the titles and abstracts of the papers. We apply k-means clustering analysis for the target key words, and present a meaningful chronological pattern of target key words in the computer science engineering field over the past 60 years.

ACS Style

Joo-Seong Heo; Hyun-Kyo Lim; Kyong-Han Kim; Youn-Hee Han. Finding Meaningful Chronological Pattern of Key Words in Computer Science Bibliography. Lecture Notes in Electrical Engineering 2016, 849 -854.

AMA Style

Joo-Seong Heo, Hyun-Kyo Lim, Kyong-Han Kim, Youn-Hee Han. Finding Meaningful Chronological Pattern of Key Words in Computer Science Bibliography. Lecture Notes in Electrical Engineering. 2016; ():849-854.

Chicago/Turabian Style

Joo-Seong Heo; Hyun-Kyo Lim; Kyong-Han Kim; Youn-Hee Han. 2016. "Finding Meaningful Chronological Pattern of Key Words in Computer Science Bibliography." Lecture Notes in Electrical Engineering , no. : 849-854.

Conference paper
Published: 23 November 2016 in Lecture Notes in Electrical Engineering
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Utilization of the Constrained Application Protocol (CoAP) that is an important protocol of the Internet of Things (IoT) has increased. So the many associated libraries related with CoAP are also emerging. Among those libraries, CoAPthon, a representative Python-based CoAP library, has advantage in aspect of easy-to-use programming interface to exploit CoAP. However, the current version of CoAPthon has not been implemented correctly in terms of (1) the Block2 option of a block-wise transfer and (2) the transfer for resource observing. In this paper, we implement them and verify the functions in our experiment using the Raspberry PI 2.

ACS Style

Kyoung-Han Kim; Hyun-Kyo Lim; Joo-Seong Heo; Youn-Hee Han. Implementation of the Block2 Option Transfer for Resource Observing with the CoAPthon Library. Lecture Notes in Electrical Engineering 2016, 831 -836.

AMA Style

Kyoung-Han Kim, Hyun-Kyo Lim, Joo-Seong Heo, Youn-Hee Han. Implementation of the Block2 Option Transfer for Resource Observing with the CoAPthon Library. Lecture Notes in Electrical Engineering. 2016; ():831-836.

Chicago/Turabian Style

Kyoung-Han Kim; Hyun-Kyo Lim; Joo-Seong Heo; Youn-Hee Han. 2016. "Implementation of the Block2 Option Transfer for Resource Observing with the CoAPthon Library." Lecture Notes in Electrical Engineering , no. : 831-836.

Article
Published: 27 April 2016 in The Journal of Supercomputing
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As smart phones have rapidly proliferated over the past few years, LTE operators endeavor to cope with large mobile data traffic volumes. To solve such problems, we propose a new distributed LTE/EPC network architecture based on SDN, NFV, and cloud computing supporting distributed P-GWs and centralized control plane in LTE/EPC networks. It is designed considering the three requirements: (1) distributing P-GWs closer to the user equipments, (2) virtually centralizing control plane, and (3) control and data plane separation. Next, we present a new SDN-based distributed mobility management (SDMM) which confirms to the proposed architecture. Based on the SDMM, the location and handover management are then presented. For enhancing network performance more, we also propose a route optimization strategy for internal traffic exchanged between LTE UEs. The proposed solutions are compared with the conventional LTE/EPC network’s scheme in terms of the gateway data processing volume, handover latency, and the number of valid data sessions. The comparison results show that the proposed solutions can be an efficient way to enhance the scalability of LTE/EPC core networks.

ACS Style

Yong-Hwan Kim; Hyun-Kyo Lim; Kyoung-Han Kim; Youn-Hee Han. A SDN-based distributed mobility management in LTE/EPC network. The Journal of Supercomputing 2016, 73, 2919 -2933.

AMA Style

Yong-Hwan Kim, Hyun-Kyo Lim, Kyoung-Han Kim, Youn-Hee Han. A SDN-based distributed mobility management in LTE/EPC network. The Journal of Supercomputing. 2016; 73 (7):2919-2933.

Chicago/Turabian Style

Yong-Hwan Kim; Hyun-Kyo Lim; Kyoung-Han Kim; Youn-Hee Han. 2016. "A SDN-based distributed mobility management in LTE/EPC network." The Journal of Supercomputing 73, no. 7: 2919-2933.

Book chapter
Published: 18 December 2015 in Lecture Notes in Electrical Engineering
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As smart phone has rapidly proliferated over the past few years, LTE operators endeavor to cope with large mobile data traffic volumes. To solve such problems, we propose a new SDN-based distributed mobility management supporting distributed P-GWs and centralized control plane in LTE/EPC networks. For enhancing network performance more, we also propose a route optimization strategy for internal traffic exchanged between LTE users. The proposed solutions’ performance is compared with the conventional LTE/EPC network’s scheme in terms of the P-GW data processing volume and the number of valid data sessions. The comparison results show that the proposed solution can be an efficient way to enhance the scalability of LTE/EPC core networks.

ACS Style

Yong-Hwan Kim; Hyun-Kyo Lim; Kyoung-Han Kim; Youn-Hee Han; Joosang Youn. A Distributed Mobility Support in SDN-Based LTE/EPC Architecture. Lecture Notes in Electrical Engineering 2015, 567 -573.

AMA Style

Yong-Hwan Kim, Hyun-Kyo Lim, Kyoung-Han Kim, Youn-Hee Han, Joosang Youn. A Distributed Mobility Support in SDN-Based LTE/EPC Architecture. Lecture Notes in Electrical Engineering. 2015; ():567-573.

Chicago/Turabian Style

Yong-Hwan Kim; Hyun-Kyo Lim; Kyoung-Han Kim; Youn-Hee Han; Joosang Youn. 2015. "A Distributed Mobility Support in SDN-Based LTE/EPC Architecture." Lecture Notes in Electrical Engineering , no. : 567-573.

Journal article
Published: 10 December 2015 in Mobile Networks and Applications
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In wireless networks, the betweenness of a node has been considered an indication of that node’s importance in efficiently and reliably delivering messages. In a large wireless network, however, the cost of computing the betweenness of every node is impractically high. In this paper, we introduce a new representation of a node’s vicinity, called the expanded ego network (shortly, x-ego network) of that node. We also propose an approach that calculates the x-ego betweenness of a node (i.e., the betweenness of that node in its x-ego network) and use it as an estimate of the true betweenness in the entire network. Furthermore, we develop an algorithm that quickly computes x-ego betweenness by exploiting structural properties of x-ego networks. Our evaluation results show the benefits and effectiveness of the above approach using trace data obtained from real-world wireless networks.

ACS Style

Chan-Myung Kim; Yong-Hwan Kim; Youn-Hee Han; Jeong-Hyon Hwang. Efficient Estimation of Betweenness Centrality in Wireless Networks. Mobile Networks and Applications 2015, 21, 469 -481.

AMA Style

Chan-Myung Kim, Yong-Hwan Kim, Youn-Hee Han, Jeong-Hyon Hwang. Efficient Estimation of Betweenness Centrality in Wireless Networks. Mobile Networks and Applications. 2015; 21 (3):469-481.

Chicago/Turabian Style

Chan-Myung Kim; Yong-Hwan Kim; Youn-Hee Han; Jeong-Hyon Hwang. 2015. "Efficient Estimation of Betweenness Centrality in Wireless Networks." Mobile Networks and Applications 21, no. 3: 469-481.

Journal article
Published: 02 April 2015 in Telecommunication Systems
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Mobile nodes (MNs) have multiple interfaces for accessing heterogeneous networks. The multiple interfaces enable the MNs to access diverse networks simultaneously, and allocate or redirect data flows dynamically across the networks. In this paper, we introduce scalable network-based mobility management architecture and propose flow mobility management scheme for the multi-connectivity management in the multi-access and multi-homing context. They are simulated using NS-3 simulator. The proposed flow mobility management scheme is verified by a complicate scenario, which includes as many cases of flow handover as possible.

ACS Style

Hyo-Beom Lee; Sung-Gi Min; Youn-Hee Han; Kyoung-Hee Lee; Hyun-Woo Lee; Won Ryu. IP flow mobility scheme in scalable network-based mobility management architecture. Telecommunication Systems 2015, 60, 315 -325.

AMA Style

Hyo-Beom Lee, Sung-Gi Min, Youn-Hee Han, Kyoung-Hee Lee, Hyun-Woo Lee, Won Ryu. IP flow mobility scheme in scalable network-based mobility management architecture. Telecommunication Systems. 2015; 60 (2):315-325.

Chicago/Turabian Style

Hyo-Beom Lee; Sung-Gi Min; Youn-Hee Han; Kyoung-Hee Lee; Hyun-Woo Lee; Won Ryu. 2015. "IP flow mobility scheme in scalable network-based mobility management architecture." Telecommunication Systems 60, no. 2: 315-325.

Research article
Published: 01 July 2014 in The Scientific World Journal
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In delay-tolerant networks, network topology changes dynamically and there is no guarantee of continuous connectivity between any two nodes. These features make DTN routing one of important research issues, and the application of social network metrics has led to the design of recent DTN routing schemes. In this paper, we propose an efficient routing scheme by using a node's local contact history and social network metrics. Each node first chooses a proper relay node based on the closeness to the destination node. A locally computed betweenness centrality is additionally utilized to enhance the routing efficiency. Through intensive simulation, we finally demonstrate that our algorithm performs efficiently compared to the existing epidemic or friendship routing scheme.

ACS Style

Chan-Myung Kim; Youn-Hee Han; Joo-Sang Youn; Young-Sik Jeong. A Socially Aware Routing Based on Local Contact Information in Delay-Tolerant Networks. The Scientific World Journal 2014, 2014, 1 -7.

AMA Style

Chan-Myung Kim, Youn-Hee Han, Joo-Sang Youn, Young-Sik Jeong. A Socially Aware Routing Based on Local Contact Information in Delay-Tolerant Networks. The Scientific World Journal. 2014; 2014 (1):1-7.

Chicago/Turabian Style

Chan-Myung Kim; Youn-Hee Han; Joo-Sang Youn; Young-Sik Jeong. 2014. "A Socially Aware Routing Based on Local Contact Information in Delay-Tolerant Networks." The Scientific World Journal 2014, no. 1: 1-7.

Book chapter
Published: 01 January 2014 in Lecture Notes in Electrical Engineering
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Community detection is a core problem in social network analysis. Strictly speaking, however, the communities does not exactly correspond to the real group, well-known as social circles. In this paper, we study on 1) how close relation between the ground-truth social circles and communities exists and 2) whether the social circles can be detected by the classical community detection algorithm or not. We use the SNAP facebook dataset to reveal the correlation between the social circles and the detected communities. We listed up the community’s modularity values and the balanced accuracy values with the ground-truth circles per each level in the iterative process of divisive clustering. We analyzed the Spearman’s rank correlation between the paired data. The experimental results show that there is a strong correlation between the ground-truth social circles and the communities detected by classical method.

ACS Style

Soo-Jin Shin; Yong-Jin Jeong; Chan-Myung Kim; Youn-Hee Han; Chan Yeol Park. Study on Relation between Social Circles and Communities in Facebook Ego Networks. Lecture Notes in Electrical Engineering 2014, 567 -572.

AMA Style

Soo-Jin Shin, Yong-Jin Jeong, Chan-Myung Kim, Youn-Hee Han, Chan Yeol Park. Study on Relation between Social Circles and Communities in Facebook Ego Networks. Lecture Notes in Electrical Engineering. 2014; ():567-572.

Chicago/Turabian Style

Soo-Jin Shin; Yong-Jin Jeong; Chan-Myung Kim; Youn-Hee Han; Chan Yeol Park. 2014. "Study on Relation between Social Circles and Communities in Facebook Ego Networks." Lecture Notes in Electrical Engineering , no. : 567-572.

Book chapter
Published: 01 January 2014 in Lecture Notes in Electrical Engineering
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In delay-tolerant network (DTN), the message forwarding and routing are important research issues, since the network topology changes dynamically and there is no guarantee of continuous connectivity between any two nodes. In this paper, we propose an efficient DTN routing scheme by using a node’s social relation where each node chooses a proper relay node based on its contact history. In order to enhance the routing efficiency, the expanded ego-network betweenness centrality is used when a relay node is selected. We have demonstrated that our algorithm performs efficiently compared to the existing epidemic and friendship routing schemes.

ACS Style

Chan-Myung Kim; In-Seok Kang; Youn-Hee Han; Young-Sik Jeong. An Efficient Routing Scheme Based on Social Relations in Delay-Tolerant Networks. Lecture Notes in Electrical Engineering 2014, 533 -540.

AMA Style

Chan-Myung Kim, In-Seok Kang, Youn-Hee Han, Young-Sik Jeong. An Efficient Routing Scheme Based on Social Relations in Delay-Tolerant Networks. Lecture Notes in Electrical Engineering. 2014; ():533-540.

Chicago/Turabian Style

Chan-Myung Kim; In-Seok Kang; Youn-Hee Han; Young-Sik Jeong. 2014. "An Efficient Routing Scheme Based on Social Relations in Delay-Tolerant Networks." Lecture Notes in Electrical Engineering , no. : 533-540.