• Journal of the Institute of Electronics Engineers of Korea TC
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• v.41 no.7
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• pp.63-73
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• 2004

This paper proposes an efficient centralized sin91e buffer management algorithm to arbitrate access contention mon processors on the multi-processor system for high-speed Packet filtering and proves that the algorithm provides reasonable performance by implementing it and applying it to a real multi-processor system. The multi-processor system for parallel packet filtering is modeled based on a network processor to distribute the packet filtering rules throughout the processors to speed up the filtering. In this paper we changed the number of processors and the processing time of the filtering rules as variables and measured the packet transfer rates to investigate the performance of the proposed algorithm.

• Korean Management Science Review
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• v.27 no.1
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• pp.17-31
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• 2010

Patients entering an emergency care center in a hospital usually visit medical processes in different orders depending on the urgency level and the medical treatments required. We formulate the patient flows among diverse processes in an emergency care center using the Jackson network, which is one of the queueing networks, in order to evaluate the system performances such as the expected queue length and the expected waiting time. We present a case study based on actual data collected from an emergency care center in a hospital, in order to prove the validity of applying the Jackson network model in practice. After assessing the current system performances, we provide operational strategies to reduce waiting at the bottleneck processes and evaluate the impact of those strategies on the entire system.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.1-25
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• 2020

In this paper, we suggest an application system architecture which provides accurate, fast and efficient automatic gasometer reading function. The system captures gasometer image using mobile device camera, transmits the image to a cloud server on top of private LTE network, and analyzes the image to extract character information of device ID and gas usage amount by selective optical character recognition based on deep learning technology. In general, there are many types of character in an image and optical character recognition technology extracts all character information in an image. But some applications need to ignore non-of-interest types of character and only have to focus on some specific types of characters. For an example of the application, automatic gasometer reading system only need to extract device ID and gas usage amount character information from gasometer images to send bill to users. Non-of-interest character strings, such as device type, manufacturer, manufacturing date, specification and etc., are not valuable information to the application. Thus, the application have to analyze point of interest region and specific types of characters to extract valuable information only. We adopted CNN (Convolutional Neural Network) based object detection and CRNN (Convolutional Recurrent Neural Network) technology for selective optical character recognition which only analyze point of interest region for selective character information extraction. We build up 3 neural networks for the application system. The first is a convolutional neural network which detects point of interest region of gas usage amount and device ID information character strings, the second is another convolutional neural network which transforms spatial information of point of interest region to spatial sequential feature vectors, and the third is bi-directional long short term memory network which converts spatial sequential information to character strings using time-series analysis mapping from feature vectors to character strings. In this research, point of interest character strings are device ID and gas usage amount. Device ID consists of 12 arabic character strings and gas usage amount consists of 4 ~ 5 arabic character strings. All system components are implemented in Amazon Web Service Cloud with Intel Zeon E5-2686 v4 CPU and NVidia TESLA V100 GPU. The system architecture adopts master-lave processing structure for efficient and fast parallel processing coping with about 700,000 requests per day. Mobile device captures gasometer image and transmits to master process in AWS cloud. Master process runs on Intel Zeon CPU and pushes reading request from mobile device to an input queue with FIFO (First In First Out) structure. Slave process consists of 3 types of deep neural networks which conduct character recognition process and runs on NVidia GPU module. Slave process is always polling the input queue to get recognition request. If there are some requests from master process in the input queue, slave process converts the image in the input queue to device ID character string, gas usage amount character string and position information of the strings, returns the information to output queue, and switch to idle mode to poll the input queue. Master process gets final information form the output queue and delivers the information to the mobile device. We used total 27,120 gasometer images for training, validation and testing of 3 types of deep neural network. 22,985 images were used for training and validation, 4,135 images were used for testing. We randomly splitted 22,985 images with 8:2 ratio for training and validation respectively for each training epoch. 4,135 test image were categorized into 5 types (Normal, noise, reflex, scale and slant). Normal data is clean image data, noise means image with noise signal, relfex means image with light reflection in gasometer region, scale means images with small object size due to long-distance capturing and slant means images which is not horizontally flat. Final character string recognition accuracies for device ID and gas usage amount of normal data are 0.960 and 0.864 respectively.

• Journal of KIISE:Computing Practices and Letters
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• v.6 no.1
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• pp.103-112
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• 2000

As today's market share of Intelligent Network (IN) service and wireless tele-communication is growing rapidly, the increment in service requests of wireless IN service subscribers and users has to be taken into account for implementing advanced IN services. In this paper, we design Global Service Logic for IN Freephone service, which is one of the commercially most interesting IN services, applied call queuing service feature with mass call processing to enhance call completion rate by considering the mobility of wireless service subscribers with mobile terminals as well as existing wireline service subscribers. Due to the location management of each IN subscribers 'mobile terminals, we design the structure and operation mechanism of Queue Manager which adjusts dynamically service subscribers groups according to their mobility. We optimize the queue size according to the call attempt rate and drop rate, and present the appropriate waiting time in the queue.

• The Journal of Society for e-Business Studies
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• v.4 no.1
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• pp.87-101
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• 1999

To operate the automatic devices of manufacturing process more effectively and to solve the needs of the resource sharing, network technology is applied to the control devices located in common manufacturing zone and operated by connecting them. In this paper, functional standard of the network layers are set as physical and data link layer of IEEE 802.2, 802.4, and VMD application layer and ISO-CIM reference model. Then, they are divided as minimized architecture, designed as group objects which perform group management and service objects which organizes and operates the group. For the stability in this network, this paper measures the variation of data packet length and node number and analyzes the variated value of the waiting time for the network operation. For the method of the analysis, non-exhausted service method are selected, and the arrival rates of the each data packet to the nodes that are assumed to form a Poission distribution. Then, queue model is set as M/G/1, and the analysis equation for waiting time is found. For the evalution of the performance, the length of the data packet varies from 10 bytes to 100 bytes in the operation of the group management network, the variation of the wating time is less than 10 msec. Since the waiting time in this case is less than 10 msec, response time is fast enough. Furthermore, to evaluate the real time processing of the group management network, it shows if the number of nodes is less than 40, and the average arrival time is less than 40 packet/sec, it can perform stable operation even taking the overhead such as software delay time, indicated packet service, and transmissin safety margin.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.9A
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• pp.762-771
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• 2005

In this paper, an efficient Adaptive quality-of-service (QoS) traffic control scheme with priority scheduling is proposed for the multimedia traffic transmission over wireless access networks. The objective of the proposed adaptive QoS control (AQC) scheme is to realize end-to-end QoS, to be scalable without the excess signaling process, and to adapt dynamically to the network traffic state according to traffic flow characteristics. Here, the reservation scheme can be used over the wireless access network in order to get the per-flow guarantees necessary for implementation of some kinds of multimedia applications. The AQC model is based on both differentiated service model with different lier hop behaviors and priority scheduling one. It consists of several various routers, access points, and bandwidth broker and adopts the IEEE 802.1 le wireless radio technique for wireless access interface. The AQC scheme includes queue management and packet scheduler to transmit class-based packets with different per hop behaviors (PHBs). Simulation results demonstrate effectiveness of the proposed AQC scheme.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.1
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• pp.129-137
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• 2016

Transmission Control Protocol as a transport layer protocol provides steady data transfer service. There are some serious concerns about the performance of TCP over diverse networks. The vital concern in TCP network environment is congestion which may occur due to quick transmission rates or because of large number of new connections entering the network at the same time. Size of queues in routers grows thus resulting in packet drops. Retransmission of the dropped packets, and reduced throughput can prove costly. Explicit Congestion Notification (ECN) in conjunction with Active Queue Management mechanisms (AQM) such as Random early detection (RED) is used for packet marking rather than dropping. In IP packet header ECN bits can be added as a sign of congestion thus avoiding needless packet drops. The proposed ECN and AQM mechanism can be implemented with help of ns2 simulator and the performance can be tested on different TCP variants.

• Proceedings of the Korea Society for Simulation Conference
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• 1994.10a
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• pp.32-32
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• 1994

In this example, a message passing based multicomputer system with general interdonnedtion network is considered. After multicomputer systems are developed with morm-hole routing network, topologies of interconecting network are not major considertion for process management and resource sharing. Tehre is an independeent operating system kernel oneach node. It communicates with other kernels using message passingmechanism. Based on this architecture, the problem is how mech does performance degradation will occur in the case of processor sharing on multicomputer systems. Processor sharing between application programs is veryimprotant decision on system performance. In almost cases, application programs running on massively parallel computer systems are not so much user-interactive. Thus, the main performance index is system throughput. Each application program has various communication patterns. and the sharing of processors causes serious performance degradation in hte worst case such that one processor is shared by two processes and another processes are waiting the messages from those processes. As a result, considering this problem is improtant since it gives the reason whether the system allows processor sharingor not. Input data has many parameters in this simulation . It contains the number of threads per task , communication patterns between threads, data generation and also defects in random inupt data. Many parallel aplication programs has its specific communication patterns, and there are computation and communication phases. Therefore, this phase informatin cannot be obtained random input data. If we get trace data from some real applications. we can simulate the problem more realistic . On the other hand, simualtion results will be waseteful unless sufficient trace data with varisous communication patterns is gathered. In this project , random input data are used for simulation . Only controllable data are the number of threads of each task and mapping strategy. First, each task runs independently. After that , each task shres one and more processors with other tasks. As more processors are shared , there will be performance degradation . Form this degradation rate , we can know the overhead of processor sharing . Process scheduling policy can affects the results of simulation . For process scheduling, priority queue and FIFO queue are implemented to support round-robin scheduling and priority scheduling.

• Journal of the Korea Institute of Military Science and Technology
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• v.13 no.5
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• pp.903-909
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• 2010

ADAS is the air defense control system performing air surveillance and identification of ROK and near air. This system is self-developed by Air Force, currently operated successfully as the alternative system of MCRC. ADAS processes converting and combining transferred the real time radar data detected by radars. additionally, it displays significant radar data as producing in tracks. Then, it uses the message queue for IPC(Inter Process Communication). the various tactical data processed in the server is ultimately send to the network management process through the message queue for transmitting to the weapon director console. the weapon director receives this transmitted tactical data through the console to execute air defense operations. However, there is a problem that data packet is delayed or lost since the weapon Director does not receive as the amount of tactical data from the server overflowed with air tracks and missions increased. This paper improved the algorism to display and transmit the various tactical data processed from ADAS server to numbers of the weapon director console in the real time without any delay or lost. Improved the algorism, established at exercise, the development server in the real operation network and the weapon director console, is proved by comparing the number of sending tactical data packets in the server and receiving packets in the weapon director.

• Journal of Digital Convergence
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• v.10 no.4
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• pp.217-222
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• 2012

Group communication on the Internet is exploding in popularity. Video conferencing, Enterprise IM, desktop sharing, and numerous forms of e-commerce are but a few examples of the ways in which the Internet is being used for business. The growing use of group communication has highlighted the need for advances in security. There are several approaches to securing user identities and other information transmitted over the Internet. One of the foundations of secure communication is key management, a building block for encryption, authentication, access control, and authorization.