• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.10
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• pp.4902-4932
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• 2016

The popularity of network virtualization has recently regained considerable momentum because of the emergence of OpenFlow technology. It is essentially decouples a data plane from a control plane and promotes hardware programmability. Subsequently, OpenFlow facilitates the implementation of network virtualization. This study aims to provide an overview of different approaches to create a virtual network using OpenFlow technology. The paper also presents the OpenFlow components to compare conventional network architecture with OpenFlow network architecture, particularly in terms of the virtualization. A thematic OpenFlow network virtualization taxonomy is devised to categorize network virtualization approaches. Several testbeds that support OpenFlow network virtualization are discussed with case studies to show the capabilities of OpenFlow virtualization. Moreover, the advantages of popular OpenFlow controllers that are designed to enhance network virtualization is compared and analyzed. Finally, we present key research challenges that mainly focus on security, scalability, reliability, isolation, and monitoring in the OpenFlow virtual environment. Numerous potential directions to tackle the problems related to OpenFlow network virtualization are likewise discussed.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.10
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• pp.367-372
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• 2016

In a modern smart building, sensors can detect various physical conditions, such as temperature, humidity, sound, motion, and light, which can be used in medical services and security, and for energy savings. This paper presents an efficient elevator scheduling system that utilizes smart sensor technologies with radio-frequency identification, video, and floor sensors to detect the arrival of elevator users in advance. The detected information is then delivered to the elevator scheduling system via building networks. By using this information, the proposed system makes a reservation call for efficient control of the elevator's direction and time. Experiments under a spectrum of traffic conditions show that the proposed system performs better than a legacy system with respect to average wait time, maximum wait time, and energy consumption.

• Journal of Korea Multimedia Society
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• v.11 no.7
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• pp.977-985
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• 2008

This paper is concerned with automatic telemetering system which reads the consumed quantity of electricity, gas, and piped water. The existing metering method such that a meterman visits households and directly reads meters can cause several problems, including violation of privacy and the possibility of criminal accident, as well the inefficiency in viewpoint of system operation and rate notification. In this paper, we propose a new automatic telemetering and rate notification system, in which the system reads several meters at remote locations and notifies the rates to the customer's cellular phone with short message service(SMS). The proposed system has been developed by using CDMA mobile communication modules and personal computers. This system can operate only with cellular communication network even without wired-internet facilities. In particular, the developed system can provide home security and convenience as well as cost reduction, and thus be applied to intelligent home networks.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.6
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• pp.1026-1031
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• 2008

Nowdays, homes and small businesses rely more and more PON(Passive Optical Networks) for financial transactions, private communications and even telemedicine. Thus, encryption for these data transactions is very essential due to the multicast nature of the PON In this parer, we presented our implementation of a counter mode AES based on Virtex4 FPGA. Our design exploits three advanced features; 1) Composite field arithmetic SubByte, 2) efficient MixColumn transformation 3) and on-the-fly key-scheduling for fully pipelined architecture. By pipeling the composite field implementation of the S-box, the area cost is reduced to average 17 percent. By designing the on-the-fly key-scheduling, we implemented an efficient key-expander module which is specialized for a pipelined architecture.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.572-575
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• 2009

With the advent of integration environment of broadcasting and communication, IPTV has been widely used. It provides services such as information, movie contents and broadcasting through TV using super-high speed networks. Developments of Wireless LAN and IP network technology create various and fusional services such as IPTV, VoIP that are based on IP network. The development of Wireless LAN is very important in IPTV network field which requires the best quality of service on the security, QoS and bandwidth. In this Paper, We configure the experimental network in its RIP and OSPF environment to test the Video Quality of IPTV in Wireless LAN. We measure and evaluate broadcasting quality by using PSNR to show the corelation of Routing Protocols in Wireless LAN in which how they affect to the IPTV real-time Video Quality.

• Journal of the Korea Society of Computer and Information
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• v.18 no.11
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• pp.229-240
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• 2013

This study critically review the textbooks and the syllabus of computer network courses currently used at universities, and the specifications of the certifications concerned to provide the students with the competitive and optimized course contents. Considering the vitality of the practicum in the computer network courses, we also suggest a new learning-instruction case study that focuses on the practice by analyzing the computer network practice test simulators which are certified nationally and the internationally. The proposed learning-instruction case study for computer network courses includes the weekly core lessons and contents, study goals and key points, the practice theme, handy tools based on two track of lecture and practice. Therefore it is expected to be a quite resourceful and practical teaching plan for the teacher, and a highly achievement of learning outcomes through motivation which can facilitate CCNA certification enrolling in the field of network aspect for the learner.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.10
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• pp.3834-3857
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• 2021

The design of cluster-based routing protocols is necessary for Wireless Sensor Networks (WSN). But, due to the lack of features, the traditional methods face issues, especially on unbalanced energy consumption of routing protocol. This work focuses on enhancing the security and energy efficiency of the system by proposing Energy Efficient Based Secure Routing Protocol (EESRP) which integrates trust management, optimization algorithm and key management. Initially, the locations of the deployed nodes are calculated along with their trust values. Here, packet transfer is maintained securely by compiling a Digital Signature Algorithm (DSA) and Elliptic Curve Cryptography (ECC) approach. Finally, trust, key, location and energy parameters are incorporated in Particle Swarm Optimization (PSO) and meta-heuristic based Harmony Search (HS) method to find the secure shortest path. Our results show that the energy consumption of the proposed approach is 1.06mJ during the transmission mode, and 8.69 mJ during the receive mode which is lower than the existing approaches. The average throughput and the average PDR for the attacks are also high with 72 and 62.5 respectively. The significance of the research is its ability to improve the performance metrics of existing work by combining the advantages of different approaches. After simulating the model, the results have been validated with conventional methods with respect to the number of live nodes, energy efficiency, network lifetime, packet loss rate, scalability, and energy consumption of routing protocol.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.8
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• pp.3917-3941
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• 2019

The recent interest in artificial intelligence and machine learning has partly contributed to an interest in the use of such approaches for hyperspectral remote sensing (HRS) imagery classification, as evidenced by the increasing number of deep framework with deep convolutional neural networks (CNN) structures proposed in the literature. In these approaches, the assumption of obtaining high quality deep features by using CNN is not always easy and efficient because of the complex data distribution and the limited sample size. In this paper, conventional handcrafted learning-based multi features based on expert knowledge are introduced as the input of a special designed CNN to improve the pixel description and classification performance of HRS imagery. The introduction of these handcrafted features can reduce the complexity of the original HRS data and reduce the sample requirements by eliminating redundant information and improving the starting point of deep feature training. It also provides some concise and effective features that are not readily available from direct training with CNN. Evaluations using three public HRS datasets demonstrate the utility of our proposed method in HRS classification.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.2
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• pp.751-770
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• 2019

Action recognition is an essential task in computer vision due to the variety of prospective applications, such as security surveillance, machine learning, and human-computer interaction. The availability of more video data than ever before and the lofty performance of deep convolutional neural networks also make it essential for action recognition in video. Unfortunately, limited crafted video features and the scarcity of benchmark datasets make it challenging to address the multi-person action recognition task in video data. In this work, we propose a deep convolutional neural network-based Effective Hybrid Learning (EHL) framework for two-person interaction classification in video data. Our approach exploits a pre-trained network model (the VGG16 from the University of Oxford Visual Geometry Group) and extends the Faster R-CNN (region-based convolutional neural network a state-of-the-art detector for image classification). We broaden a semi-supervised learning method combined with an active learning method to improve overall performance. Numerous types of two-person interactions exist in the real world, which makes this a challenging task. In our experiment, we consider a limited number of actions, such as hugging, fighting, linking arms, talking, and kidnapping in two environment such simple and complex. We show that our trained model with an active semi-supervised learning architecture gradually improves the performance. In a simple environment using an Intelligent Technology Laboratory (ITLab) dataset from Inha University, performance increased to 95.6% accuracy, and in a complex environment, performance reached 81% accuracy. Our method reduces data-labeling time, compared to supervised learning methods, for the ITLab dataset. We also conduct extensive experiment on Human Action Recognition benchmarks such as UT-Interaction dataset, HMDB51 dataset and obtain better performance than state-of-the-art approaches.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.7
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• pp.904-913
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• 2020

As the data volumes and complexity rapidly increase, data-intensive science handling large-scale scientific data needs to investigate new techniques for intelligent storage and data distribution over networks. Recently, Named Data Networking (NDN) and data-intensive science communities have inspired innovative changes in distribution and management for large-scale experimental data. In this article, analysis on NDN testbeds for large-scale scientific data such as climate science data and High Energy Physics (HEP) data is presented. This article is the first attempt to analyze existing NDN testbeds for large-scale scientific data. NDN testbeds for large-scale scientific data are described and discussed in terms of status, NDN-based application, and features, which are NDN testbed instance for climate science, NDN testbed instance for both climate science and HEP, and the NDN testbed in SANDIE project. Finally various issues to prevent pitfalls in NDN testbed establishment for large-scale scientific data are analyzed and discussed, which are drawn from the descriptions of NDN testbeds and features on them.