• Journal of Information Processing Systems
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• v.12 no.3
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• pp.511-524
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• 2016

The Virtual Local Area Network (VLAN) has been used for a long time in campus and enterprise networks as the most popular network virtualization solution. Due to the benefits and advantages achieved by using VLAN, network operators and administrators have been using it for constructing their networks up until now and have even extended it to manage the networking in a cloud computing system. However, their configuration is a complex, tedious, time-consuming, and error-prone process. Since Software Defined Networking (SDN) features the centralized network management and network programmability, it is a promising solution for handling the aforementioned challenges in VLAN management. In this paper, we first introduce a new architecture for campus and enterprise networks by leveraging SDN and OpenFlow. Next, we have designed and implemented an application for easily managing and flexibly troubleshooting the VLANs in this architecture. This application supports both static VLAN and dynamic VLAN configurations. In addition, we discuss the hybrid-mode operation where the packet processing is involved by both the OpenFlow control plane and the traditional control plane. By deploying a real test-bed prototype, we illustrate how our system works and then evaluate the network latency in dynamic VLAN operation.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.10
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• pp.1368-1375
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• 2013

The Smart Grid, which can monitor or diagnose the power grid in real time to operate efficiently, has been pushed ahead systematically as one of alternatives to solve these issues by combining the advanced Information Communication Technology and the electrical network. Hence, the electric company which introduces smart grid technology can read remotely the electrical meter readings by means of two-way communication between the meter and the central system. This enabled the customer and the utility to take part in reasonable electrical energy utilization. AMI became one of the core foundations in realizing the Smart Grid. It is hard to test the entire process of AMI system before the full deployment because it covers the broad objects from the customer to the utility operation system and requires mass data handling and management. Therefore, we design an efficient AMI network model and a simulator for performance evaluation required to simulate the network model similar to the real environment. This tool supports to evaluate the efficiency of the AMI network equipments and deployment. Additionally, it estimates the appropriate number of deployments and the proper capabilities.

• Journal of information and communication convergence engineering
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• v.7 no.2
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• pp.119-124
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• 2009

In this paper, we propose a novel approach to estimating the real-time moving trajectory of an object is proposed in this paper. The object's position is obtained from the image data of a CCD camera, while a state estimator predicts the linear and angular velocities of the moving object. To overcome the uncertainties and noises residing in the input data, a Extended Kalman Filter(EKF) and neural networks are utilized cooperatively. Since the EKF needs to approximate a nonlinear system into a linear model in order to estimate the states, there still exist errors as well as uncertainties. To resolve this problem, in this approach the Kohonen networks, which have a high adaptability to the memory of the input-output relationship, are utilized for the nonlinear region. In addition to this, the Kohonen network, as a sort of neural network, can effectively adapt to the dynamic variations and become robust against noises. This approach is derived from the observation that the Kohonen network is a type of self-organized map and is spatially oriented, which makes it suitable for determining the trajectories of moving objects. The superiority of the proposed algorithm compared with the EKF is demonstrated through real experiments.

• Tribology and Lubricants
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• v.30 no.6
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• pp.356-363
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• 2014

Marine diesel engines operate in environments in which damage easily occurs from corrosion. Recently, damage to cylinder liners has increased from corrosion wear caused by increased engine power. This damage can cause serious problems in the economy. Thus, many researchers have treated and studied damaged cylinder liners. However, a method is necessary for real-time monitoring of damage to cylinder liners during operation of the engine, before serious damage can occur. This study carries out reciprocating friction and wear tests on a cast iron specimen under various corrosion atmospheres and verifies the variations of friction coefficient and friction surface. Additionally, the friction coefficient and friction status are predicted by using a neural network that learns the vibration and frequency spectrum data from an acceleration sensor. According to our conclusions, amplitude is distributed highly at high frequencies, and values of standard deviation and kurtosis are high when damage to the friction surface is serious. The accuracy rate of the friction coefficient predicted by the neural network is over 80% of the real measured value without NaCl, and application of the neural network is very effective for diagnosing the friction condition and damage to the cylinder liner.

• Journal of Korean Society of Transportation
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• v.20 no.4
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• pp.135-150
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• 2002

The basic assumption of analytical Dynamic Traffic Assignment models is that traffic demand and network conditions are known as a priori and unchanging during the whole planning horizon. This assumption may not be realistic in the practical traffic situation because traffic demand and network conditions nay vary from time to time. The rolling horizon implementation recognizes a fact : The Prediction of origin-destination(OD) matrices and network conditions is usually more accurate in a short period of time, while further into the whole horizon there exists a substantial uncertainty. In the rolling horizon implementation, therefore, rather than assuming time-dependent OD matrices and network conditions are known at the beginning of the horizon, it is assumed that the deterministic information of OD and traffic conditions for a short period are possessed, whereas information beyond this short period will not be available until the time rolls forward. This paper introduces rolling horizon implementation to enable a multi-class analytical DTA model to respond operationally to dynamic variations of both traffic demand and network conditions. In the paper, implementation procedure is discussed in detail, and practical solutions for some raised issues of 1) unfinished trips and 2) rerouting strategy of these trips, are proposed. Computational examples and results are presented and analyzed.

• The Journal of the Korea Contents Association
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• v.18 no.4
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• pp.48-59
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• 2018

Recently, network technology has been used in various fields due to development of network technology. However, there has been an increase in the number of attacks targeting public institutions and companies by exploiting the evolving network technology. Meanwhile, the existing network intrusion detection system takes much time to process logs as the amount of network log increases. Therefore, in this paper, we propose a Spark-based network log analysis system that detects unstructured network attack pattern. by using Snort. The proposed system extracts and analyzes the elements required for network attack pattern detection from large amount of network log data. For the analysis, we propose a rule to detect network attack patterns for Port Scanning, Host Scanning, DDoS, and worm activity, and can detect real attack pattern well by applying it to real log data. Finally, we show from our performance evaluation that the proposed Spark-based log analysis system is more than two times better on log data processing performance than the Hadoop-based system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.3 no.1
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• pp.84-95
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• 2009

The ubiquitous smart home is the home of the future, which exploits context information from both the human and the home environment, providing an automatic home service for the human. Human location and motion are the most important contexts in the ubiquitous smart home. In this paper, we present a real-time human tracker that predicts human location and motion for the ubiquitous smart home. The system uses four network cameras for real-time human tracking. This paper explains the architecture of the real-time human tracker, and proposes an algorithm for predicting human location and motion. To detect human location, three kinds of images are used: $IMAGE_1$ - empty room image, $IMAGE_2$ - image of furniture and home appliances, $IMAGE_3$ - image of $IMAGE_2$ and the human. The real-time human tracker decides which specific furniture or home appliance the human is associated with, via analysis of three images, and predicts human motion using a support vector machine (SVM). The performance experiment of the human's location, which uses three images, lasted an average of 0.037 seconds. The SVM feature of human motion recognition is decided from the pixel number by the array line of the moving object. We evaluated each motion 1,000 times. The average accuracy of all types of motion was 86.5%.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.2
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• pp.236-247
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• 2002

We propose a cell－multiplexing scheme for the real－time communication service in ATM network and a new service discipline guarantee end-to-end delay based on pseudo-isochronous cell switching. The proposed scheme consists of two level frame hierarchy, upper and lower frame, which is used to assign the bandwidth and to guarantee the requested delay bound, respectively. Since the Proposed algorithm employs two level frame hierarchy, it can overcome the coupling problem which is inherent to the framing strategy It can be comparatively reduce the complexity, and still guarantee the diverse delay bounds of end-to-end. Besides, it consists of two components, traffic controller and scheduller, as the imput traffic description model and regulates the input traffic specification. The function of the traffic controller is to shape real -time traffic to have the same input pattern at every switch along the path. The end-to-end delay is bounded by the scheduller which can limit the delay variation without using per-session jitter controllers, and therefore it can decrease the required buffer size. The proposed algorithm can support the QoS's of non-real time traffic as well as those of real time traffic.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.39 no.7
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• pp.12-21
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• 2002

In this paper, we propose a new hybrid ARQ scheme to consider real-time and non real-time services in a wireless ATM network. Real-time and non-real-time services require different error control schemes according to each service characteristics. Therefore, in the next generation mobile communication environments where these service scenarios should be deployed, hybrid ARQ scheme using RCPC code with variable coding rate becomes one of the most suitable solutions. Because the variable coding rate is applied according to traits of transmitted frame and channel status, hybrid ARQ scheme using RCPC code can expect UEP effect. The UEP scheme does not apply equal error protection level to all information, but does high error protection level to more important information. In Our scheme, UEP of high error protection level is applied to real-time service, and UEP of low error protection and retransmission techniques are applied to non real-time service. We show that the proposed hybrid ARQ scheme improves channel utilization efficiency and yields high error correction behaviors.

• Journal of Advanced Navigation Technology
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• v.19 no.4
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• pp.305-310
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• 2015

A controlling system for airport refueling facilities is connected to sensors which collect various informations. Informations which are transmitted at a high speed in various sensors are processed by a dedicated software in the controlling system. The problems of system maintenance and network traffic caused by the use of dedicated software reduce the efficiency of the system operation. Therefore, a web-based system that can be accessed using the Internet environment is required. In this paper, we propose a system showing web-based real-time informations. To do this, we change the function of the communication by each sensor to a facade structure, and design a system for transferring web-based real-time informations. Also we propose data-driven infographics for displaying the real-time big data information at a high speed on the web. Finally, we compare and analyse the proposed system between the existing system and show that our system can effectively display the real-time information on the web.