• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.6
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• pp.631-637
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• 2018

In 5G mobile communication, it is necessary to provide different mobility to user equipments(UE) that do not require mobility management or need limited mobility management. In this paper, we propose a two-layer mobility management system that classifies multiple MTC devices with similar mobility levels into c-MTC and m-MTC groups. In order to improve the energy efficiency and service life by reducing the number of control signals generated when TAU is performed, the group header typically performs a Tracking Area Update(TAU) request and adjusts the periodic TAU update period according to the mobility level. The TAU update period of the m-MTC is set to 54 minutes proposed by the 3GPP standard and the c-MTC is set to 12 minutes. Compared to when the UEs perform TAU individually, it is found that the number of control signals decreases by 33% when the MME is not changed and by 49% when the MME is not changed in the m-MTC or c-MTC group.

• Journal of the Korea Society for Simulation
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• v.10 no.2
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• pp.47-60
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• 2001

In mobile wireless network efficient location management for tracking and finding mobile users is a critical issue. The traffic for location update can be excessive, especially at the base stations that are near to the location area (LA) boundaries. In this paper we propose a new location update scheme which can significantly reduce the signaling traffic for location update. It is based on the virtual layer approach employing SubMSCs. The virtual layer is laid upon the original layer of LAs such that the mobile terminals moving around the boundary cells of adjacent LAs become to move within a virtual LA. As a result, the location update traffic is substantially reduced compared to overlapping scheme which is the most recent and efficient location update scheme.

• Korean Management Science Review
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• v.25 no.2
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• pp.73-80
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• 2008

The location area planning is to assign cells to the location areas of a wireless communication network in an optimum manner. The two important cost components are cost of location update and cost of paging that are of conflicting in nature; i.e., minimizing the registration cost might increase the search cost. Hence, it is important to find a compromise between the location update and paging operations such that the cost of mobile terminal location tracking cost is a minimum. The complete mobile network is divided into location areas. Each location area consists of a group of cells. In fact this is shown to be an NP-complete problem in an earlier study. In this paper, we use an ant colony optimization method to obtain the best/optimal group of cells for a given a network.

• Korean Management Science Review
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• v.29 no.1
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• pp.143-152
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• 2012

Location area planning (LAP) problem is to partition the cellular/mobile network into location areas with the objective of minimizing the total cost in location management. The minimum cost has two components namely location update cost and searching cost. Location update cost is incurred when the user changes itself from one location area to another in the network. The searching cost incurred when a call arrives, the search is done only in the location area to find the user. Hence, it is important to find a compromise between the location update and paging operations such that the cost of mobile terminal location tracking cost is a minimum. The complete mobile network is divided into location areas. Each location area consists of a group of cells. This partitioning problem is a difficult combinatorial optimization problem. In this paper, we use particle swarm optimization (PSO) to obtain the best/optimal group of cells for 16, 36, 49, and 64 cells network. Experimental studies illustrate that PSO is more efficient and surpasses those of precious studies for these benchmarking problems.

• Journal of Korea Multimedia Society
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• v.19 no.2
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• pp.418-427
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• 2016

A smart parking management requires to track a vehicle in a indoor parking lot and to detect the place where the vehicle is parked. An advanced parking system watches all space of the parking lot with CCTV cameras. We can use these cameras for vehicles tracking and detection. In order to cover a wide area with a camera, a fisheye lens is used. In this case the shape and size of an moving vehicle vary much with distance and angle to the camera. This makes vehicle detection and tracking difficult. In addition to the fisheye lens, the vehicle headlights also makes vehicle detection and tracking difficult. This paper describes a method of realtime vehicle detection and tracking robust to the harsh situation described above. In each image frame, we update the region of a vehicle and estimate the vehicle movement. First we approximate the shape of a car with a quadrangle and estimate the four sides of the car using multiple histograms of oriented gradient. Second we create a template by applying a distance transform to the car region and estimate the motion of the car with a template matching method.

• Journal of Broadcast Engineering
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• v.16 no.1
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• pp.178-181
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• 2011

With the development of mobile devices and intelligent surveillance system loaded with pan/tilt cameras, object tracking with non-stationary cameras has become a topic with increasing importancy. Since it is difficult to model a background image in a non-stationary camera environment, colors and texture are the most important features in the tracking algorithm. However, colors in the background similar to those in the target arise instability in the tracking. Recently, we proposed a robust color based tracking algorithm that uses an area weighted centroid shift. In this letter, we update the model such that it becomes more stable against background colors. The proposed algorithm also incorporates time filtering by adding an additional energy term to the energy functional.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37B no.12
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• pp.1119-1127
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• 2012

The one of features of M2M communications, which are recently attracted attention as a future business of mobile communications, is that there is a large number of devices compared with traditional communication services. Hence, the control signal that are generated by the M2M devices may cause a significant congestion in the network and in order to solve this problem, a standardization is progressing for reducing the redundant signaling by managing M2M devices as a group in 3GPP standardization. In this paper, we propose a method of group based mobility management by managing M2M devices that have the same mobility as a group. In the proposed method, M2M devices that have the same mobility are grouped by the Mobility Management Entity (MME) and the MME elects a group header among the M2M devices in the group. Then, the group header performs the Tracking Area Update (TAU) on behalf of the group members to reduce the signaling overhead of mobility management. With the proposed method, we can achieve 80% decrease of the signaling overhead of mobility management compared with the case where each M2M device individually performs its TAU procedure.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.2
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• pp.46-53
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• 2016

In mobile communication systems, location management deals with the location determination of users in a network. One of the strategies used in location management is to partition the network into location areas. Each location area consists of a group of cells. The goal of location management is to partition the network into a number of location areas such that the total paging cost and handoff (or update) cost is a minimum. Finding the optimal number of location areas and the corresponding configuration of the partitioned network is a difficult combinatorial optimization problem. This cell grouping problem is to find a compromise between the location update and paging operations such that the cost of mobile terminal location tracking is a minimum in location area wireless network. In fact, this is shown to be an NP-complete problem in an earlier study. In this paper, artificial bee colony (ABC) is developed and proposed to obtain the best/optimal group of cells for location area planning for location management system. The performance of the artificial bee colony (ABC) is better than or similar to those of other population-based algorithms with the advantage of employing fewer control parameters. The important control parameter of ABC is only 'Limit' which is the number of trials after which a food source is assumed to be abandoned. Simulation results for 16, 36, and 64 cell grouping problems in wireless network show that the performance of our ABC is better than those alternatives such as ant colony optimization (ACO) and particle swarm optimization (PSO).

• Journal of KIISE:Software and Applications
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• v.37 no.1
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• pp.29-38
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• 2010

We propose an interactive projection technique to display details of a large image in a high resolution and brightness by tracking a portable projector. A closed-loop based tracking method is presented to update the projected image while a user changes the position of the detail area by moving the portable projector. A marker is embedded in the large image to indicate the position to be occupied by the detail image projected by the portable projector. The marker is extracted in sequential images acquired by a camera attached to the portable projector. The marker position in the large display image is updated under a constraint that the center positions of marker and camera frame coincide in every camera frame. The image and projective transformation for warping are calculated using the marker position and shape in the camera frame. The marker's four corner points are determined by a four-step segmentation process which consists of camera image preprocessing based on HSI, edge extraction by Hough transformation, quadrangle test, and cross-ratio test. The interactive projection system implemented by the proposed method performs at about 24fps. In the user study, the overall feedback about the system usability was very high.

• Journal of KIISE:Information Networking
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• v.30 no.5
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• pp.581-594
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• 2003

Recently, a location management is being more important in mobile communication systems due to an explosive increase of mobile users. Current systems have used a concept of location area. Based on this concept, a mobile user performs a location update whenever it moves into a new location area. However, this scheme can not avoid unnecessary location updates when a mobile user moves around with high movement rate as compared to call arrival rate. That results in tremendous location management cost. To overcome this drawback, our proposal divides service areas into two sets: One is a set of areas that mobile users move with high speed and another is a set of areas that they move with low speed. After establishing these two sets, this paper employs different location tracking schemes for each sets. Generally, most mobile users with high speed have a low CMR and a regular direction until they arrive at their destination. Using such the moving behavior, systems can predict a mobile user's next location area in advance. When the mobile user moves into the predicted location, our proposal does not perform a location update. Thus, it can reduce overall location management cost. The Markov model is used to analyze the performance of our proposal. Using the model, this paper compares our proposal with IS-41 and TLA. The analytic results show that as CMR grows lower, an overall cost of our proposal becomes less, particularly if a mobile user frequently moves into the specific location are predicted by mobile systems. Also, our proposal has a better performance than other two schemes when the communication cost between HLR and VLR is high.