• Journal of Information Processing Systems
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• v.11 no.1
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• pp.39-56
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• 2015

Continuous multi-interval prediction (CMIP) is used to continuously predict the trend of a data stream based on various intervals simultaneously. The continuous integrated hierarchical temporal memory (CIHTM) network performs well in CMIP. However, it is not suitable for CMIP in real-time mode, especially when the number of prediction intervals is increased. In this paper, we propose a real-time integrated hierarchical temporal memory (RIHTM) network by introducing a new type of node, which is called a Zeta1FirstSpecializedQueueNode (ZFSQNode), for the real-time continuous multi-interval prediction (RCMIP) of data streams. The ZFSQNode is constructed by using a specialized circular queue (sQUEUE) together with the modules of original hierarchical temporal memory (HTM) nodes. By using a simple structure and the easy operation characteristics of the sQUEUE, entire prediction operations are integrated in the ZFSQNode. In particular, we employed only one ZFSQNode in each level of the RIHTM network during the prediction stage to generate different intervals of prediction results. The RIHTM network efficiently reduces the response time. Our performance evaluation showed that the RIHTM was satisfied to continuously predict the trend of data streams with multi-intervals in the real-time mode.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.6
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• pp.1104-1109
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• 2001

In this paper, we describe a method for real-time transmitting video streams based on RTP. In order to guarantee synchronous video streams, we propose a method to grasp network situations by analyzing end-to-end network traffic. In addition, we present an algorithm for satisfying QoS requirements of real-time multimedia transmission and maintaining continuity of transmission. It describes a buffering method for overcoming bandwidth limitations and an analyzing method based on RTCP for grasping network traffic situation to resolve the problem of real-time transmission of video streams.

• Journal of information and communication convergence engineering
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• v.14 no.2
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• pp.84-88
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• 2016

As good example of potential application-specific requirement, (m,k)-firm real-time streams have been recently introduced to deliver multimedia data efficiently in wireless sensor networks. In addition to stream model, communication protocols to meet specific (m,k)-firm real-time streams have been newly developed or extended from existing protocols. However, since the existing schemes for an (m,k)-firm stream have been proposed under typical flat architecture, the scalability problem remains unsolved when the number of real-time flows increases in the networks. To solve this problem, in this paper, we propose a new clustering scheme for an (m,k)-firm stream. The two different clustering algorithms are performed according to either the (m,k)-firm requirement or the deadline. Simulation results are presented to demonstrate the suitability of the proposed scheme under hierarchical architecture by showing that its performance is acceptable irrespective of the increase in the number of flows.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.4
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• pp.1841-1865
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• 2017

This paper proposes a new interference mitigation scheme for device-to-device (D2D) communications underlaying a cellular network. The object of the proposed scheme is to determine the number of data streams, a precoding matrix, and a decoding matrix of D2D networks so as to maximize the system capacity given the number of data streams of a cellular network while satisfying the constraint of the inter-system interference from D2D networks to the cellular network. Unlike existing interference mitigation schemes based on the interference alignment technique, the proposed scheme operates properly regardless of the number of data streams of a cellular network and moreover it does not require changing the precoding and decoding matrices of a cellular network. The simulation results demonstrate that the proposed scheme significantly increases the system capacity by mitigating the intra- and inter-system interference.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.10a
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• pp.169-172
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• 2001

In this paper, we describe a method for real-time transmitting video streams based on RTP In order to guarantee synchronous video streams, we propose a method to grasp network situations by analyzing end-to-end network traffic. In addition, we present an algorithm for satisfying QoS requirements of real-time multimedia transmission and maintaining continuity of transmission. It describes a buffering method for overcoming bandwidth limitations and an analyzing method based on RTCP for grasping network traffic situation to resolve the problem of real-time transmission of video streams.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.1252-1255
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• 2013

오늘날 급변하는 IT 환경에 신속하게 대응하기 위한 기업의 데이터 관리시스템의 중요성이 강조되고 있다. 특히, 최근에는 기업의 시스템이 복잡해지고 데이터의 규모가 점점 대형화 되면서 기업들은 데이터 관리를 위해 메타데이터 관리시스템의 활용이 증가하고 있다. 하지만 현재 도입되는 메타데이터 관리시스템은 테이블 이관 시 모델과 실제 데이터베이스 사이의 정합성을 유지하기 위해 불필요한 반복적인 프로세스를 수행해야 하는 문제점을 가진다. 따라서 본 논문에서는 이러한 문제점을 해결하기 위하여 이관관리 프로세스 개선을 위한 메타데이터 관리시스템을 구현하고 테스트 하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.1222-1225
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• 2013

오늘날 기업의 시스템은 훨씬 복잡해지고 다루는 데이터의 규모는 점점 대형화됨에 따라 환경 변화에 기업이 대응하기가 어려워지고 있다. IT 환경의 변화에 기업이 대응하기 위해서는 메타데이터 관리시스템의 기능을 개선할 필요가 있다. 본 논문에서는 데이터 모델링에 대한 새로운 요구사항을 신속히 반영하기 위해서 모델의 변경 이력을 참조하지 않고 이관해야 할 목표 데이터베이스의 테이블의 형상을 비교하여 이관 관리 프로세스를 향상시킨 알고리즘을 설계하였다. 본 논문서 설계한 알고리즘을 통해 모델의 변경 이력을 참조할 경우 발생하는 데이터베이스 변경의 처리 횟수를 줄임으로써 프로세스 개선의 효과를 기대할 수 있는 알고리즘을 제시하였다.

• Journal of Information Processing Systems
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• v.19 no.4
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• pp.439-449
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• 2023

This paper deals with a resource efficient artificial intelligence (AI) service architecture for multi-channel video streams. As an AI service, we consider the object detection model, which is the most representative for video applications. Since most object detection models are basically designed for a single channel video stream, the utilization of the additional resource for multi-channel video stream processing is inevitable. Therefore, we propose a resource efficient AI service framework, which can be associated with various AI service models. Our framework is designed based on the modular architecture, which consists of adaptive frame control (AFC) Manager, multiplexer (MUX), adaptive channel selector (ACS), and YOLO interface units. In order to run only a single YOLO process without regard to the number of channels, we propose a novel approach efficiently dealing with multi-channel input streams. Through the experiment, it is shown that the framework is capable of performing object detection service with minimum resource utilization even in the circumstance of multi-channel streams. In addition, each service can be guaranteed within a deadline.

• Proceedings of the IEEK Conference
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• 2003.07a
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• pp.477-480
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• 2003

Packet losses in the Internet can dramatically degrade quality of multimedia streams. Forward Error Correction (FEC) is one of the best methods that can protect data from packet erasures by means of sending additional redundant information. Proposed control algorithm provides the possibility of receiving real-time multimedia streams of given quality wifth minimal traffic overhead. The traffic optimization is reached by adjusting packet size as well as block code parameters. Calculations and simulation results show that for non-bursty network conditions traffic optimization can lead to more than 50% bandwidth reduction.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.04a
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• pp.71-74
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• 2009

The data-flow paradigm has been employed in various application areas. It is particularly useful where large data-streams must be processed, for example in video and audio processing, or for scientific visualization. A video-based 3D reconstruction system should process multiple synchronized video streams. The system exhibits many properties that can be targeted using a data-flow approach that is naturally divided into a sequence of processing tasks. In this paper we introduce our concept to apply the data-flow approach to a multi-video 3D reconstruction system.