• Journal of Broadcast Engineering
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• v.27 no.3
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• pp.308-317
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• 2022

Researches are underway to efficiently reduce the size of video data transmitted and stored in the image analysis process using deep learning-based machine vision technology. MPEG (Moving Picture Expert Group) has newly established a standardization project called VCM (Video Coding for Machine) and is conducting research on video encoding for machines rather than video encoding for humans. We are researching a multitask that performs various tasks with one image input. The proposed pipeline does not perform all object detection of each task that should precede object detection, but precedes it only once and uses the result as an input for each task. In this paper, we propose a pipeline for efficient multitasking and perform comparative experiments on compression efficiency, execution time, and result accuracy of the input image to check the efficiency. As a result of the experiment, the capacity of the input image decreased by more than 97.5%, while the accuracy of the result decreased slightly, confirming the possibility of efficient multitasking.

• Journal of KIISE:Computer Systems and Theory
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• v.35 no.9_10
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• pp.429-440
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• 2008

As embedded system becomes more complex, software development becomes more important in the entire design process. Most embedded applications consist of multi -tasks, that are executed in parallel. So, dataflow model that expresses concurrency naturally is preferred than sequential programming language to develop multitask software. For the execution of multitasking codes, operating system is essential to schedule multi-tasks and to deal with the communication between tasks. But, it is needed to execute multitasking code without as when the target hardware platform cannot execute as or target platforms are candidates of design space exploration, because it is very costly to port as for all candidate platforms of DSE. For this reason, we propose the serialized multitasking code generation technique from dataflow specification. In the proposed technique, a task is specified with dataflow model, and generated as a C code. Code generation consists of two steps: First, a block in a task is generated as a separate function. Second, generated functions are scheduled by a multitasking scheduler that is also generated automatically. To make it easy to write customized scheduler manually, the data structure and information of each task are defined. With the preliminary experiment of DivX player, it is confirmed that the generated code from the proposed framework is efficiently and correctly executed on the target system.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.4
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• pp.71-81
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• 2010

In grid system, Task scheduling based on list scheduling models has showed low complexity and high efficiency in fully connected processor set environment. However, earlier schemes did not consider sufficiently the communication cost among tasks and the composition process of lightpath for communication in optical gird environment. In this thesis, we propose LSOG (Leveling Selection in Optical Grid) which sets task priority after forming a hierarchical directed acyclic graph (DAG) that is optimized in optical grid environment. To determine priorities of task assignment in the same level, proposed algorithm executes the task with biggest communication cost between itself and its predecessor. Then, it considers the shortest route for communication between tasks. This process improves communication cost in scheduling process through optimizing link resource usage in optical grid environment. We compared LSOG algorithm with conventional ELSA (Extended List Scheduling Algorithm) and SCP (Scheduled Critical Path) algorithm. We could see the enhancement in overall scheduling performance through increment in CCR value and smoothing network environment.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.9
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• pp.263-272
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• 2023

Industrial Internet of Things (IIoT) is an important factor in increasing production efficiency in industrial sectors, along with data collection, exchange and analysis through large-scale connectivity. However, as traffic increases explosively due to the recent spread of IIoT, an allocation method that can efficiently process traffic is required. In this thesis, I propose a two-stage task offloading decision method to increase successful task throughput in an IIoT environment. In addition, I consider a hybrid offloading system that can offload compute-intensive tasks to a mobile edge computing server via a cellular link or to a nearby IIoT device via a Device to Device (D2D) link. The first stage is to design an incentive mechanism to prevent devices participating in task offloading from acting selfishly and giving difficulties in improving task throughput. Among the mechanism design, McAfee's mechanism is used to control the selfish behavior of the devices that process the task and to increase the overall system throughput. After that, in stage 2, I propose a multi-armed bandit (MAB)-based task offloading decision method in a non-stationary environment by considering the irregular movement of the IIoT device. Experimental results show that the proposed method can obtain better performance in terms of overall system throughput, communication failure rate and regret compared to other existing methods.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.11
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• pp.2426-2432
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• 2011

In this study, we evaluated web usability for hospital web sites in Korea and analyzed the evaluation results of web usability. Estimators investigated twelve hospital web sites and answered a questionnaire. They also performed predefined tasks which were frequently used services in hospital web sites. We had an interview with the estimator for finding what happened in process of evaluating usability. The evaluation results showed that university hospital provided comparatively better web usability for users. But ambiguous and complicated user interface caused confusion among users. The simplifications of service processes and interfaces were necessary to improve web usability. Some hospitals did not offer primary web services and their services related to the tasks were not systematic.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.7
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• pp.505-509
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• 2009

It is the most important object of real-time computing to make real-time tasks keep their given time conditions. In this paper, we implemented BCC(Basic Concurrency Constraint) scheduler which is provided as an essential element of TMO(Time-triggered Message-triggered Object) model, and TMO Supporting Library that supports object-oriented design for TMO. BCC scheduler is a means to design timeliness-guaranteed computing, and it predicts the start of SpMs first, and then it makes the execution of SvMs deferred when it is predicted that any SpM begins to run currently. In this way, BCC is able to prevent collisions between SpM and SvM, and it gives higher priority to SpMs than SvMs.

• Proceedings of the Korean Information Science Society Conference
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• 2011.06b
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• pp.409-412
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• 2011

본 논문에서는 Xen-ARM 기반의 가상화 환경에서 실시간 게스트 운영체제의 I/O를 지원하기 위한 방법을 제안한다. Xen-ARM 하이퍼바이저는 서버 환경에서 주로 사용되는 Xen 가상화 기법을 모바일 구조인 ARM에서 구현한 것으로, 분할 드라이버 모델과 크레딧 스케줄러를 지원한다. 하지만, 이러한 두 가지 특성은 I/O 처리 지연의 주요 원인이 된다. 특히, 장치 드라이버와 사용자 태스크의 실행 중에 하이퍼바이저의 도메인 간 스위칭이 필요하므로, 특정 시간으로 I/O 처리 지연을 제한하기 대단히 어렵다. 본 논문에서는 게스트 운영체제의 수정을 통해 I/O 처리 지연을 제한하는 기법을 제안한다. 게스트 운영체제는 현재 실행되는 태스크의 특성을 Xen-ARM 하이퍼바이저에게 간접적으로 전달하여, 전체 시스템의 모든 태스크에 대하여 우선순위를 부여하며, 하이퍼바이저의 스케줄러에서 인터럽트 처리를 위해 가장 응급한 태스크 실행을 스케줄링 할 수 있도록 한다. 제안하는 기법은 실험을 통해, I/O를 처리하는 도메인의 1ms 이상의 처리시간이 84%에서 99%까지 줄어들 수 있음을 보인다.

• Journal of KIISE
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• v.44 no.8
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• pp.822-831
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• 2017

In this paper, we propose a Korean dependency parsing model using multi-task learning based pointer networks. Multi-task learning is a method that can be used to improve the performance by learning two or more problems at the same time. In this paper, we perform dependency parsing by using pointer networks based on this method and simultaneously obtaining the dependency relation and dependency label information of the words. We define five input criteria to perform pointer networks based on multi-task learning of morpheme in dependency parsing of a word. We apply a fine-tuning method to further improve the performance of the dependency parsing proposed in this paper. The results of our experiment show that the proposed model has better UAS 91.79% and LAS 89.48% than conventional Korean dependency parsing.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06d
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• pp.21-23
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• 2012

최근 안드로이드 플랫폼을 탑재한 스마트폰이 널리 보급되면서 안드로이드 플랫폼에 대한 관심은 더욱 커지고 있다. 하지만 안드로이든 스마트폰은 종종 양질의 사용자 응답성을 제공하지 못하는 것으로 알려져 있다. 이는 안드로이드 상에서 대화형 태스크가 다른 태스크와 구별되지 않고 동일한 우선순위로 스케줄링 되기 때문에 사용자 입력을 처리하는 동안 여러 번의 선점을 당해 긴 응답시간을 초래할 수 있기 때문이다. 이 논문은 안드로이드 스마트폰의 사용자 응답성 향상을 위해 프레임워크 지원 우선순위 부스트 기법을 제시한다. 제안된 기법은 프레임워크 레벨에서 대화형 태스크를 식별하고 이를 커널에게 전달하며, 커널 레벨에서는 식별된 태스크의 우선순위를 선별적으로 부스트 시킴으로써 선점 없이 사용자 입력을 처리할 만큼 충분한 시간을 보장해 준다. 실험 결과는 제안된 기법이 기존 시스템보다 최대 22% 단축된 응답 시간을 보여 제안된 기법의 효용성을 입증하였다.

• Proceedings of the Korean Information Science Society Conference
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• 2011.06a
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• pp.506-509
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• 2011

Android는 스마트폰 시스템에서 사용되는 소프트웨어 플랫폼으로 JVM(Java Virtual Machine)을 기반으로 한다. JVM은 실시간성 지원을 고려하지 않은 기술이며 이를 기반으로 한 Android 또한 실시간성을 지원하기 위한 어떠한 방법도 가지고 있지 않다. 스마트폰 시스템을 통해 QoS를 보장하면서 멀티미디어 서비스를 제공하기 위해서는 JVM 기반의 시스템을 위한 실시간성 향상 기술이 필요하다. 본 연구에서는 기존의 안드로이드 시스템에 리눅스에서 제공하는 실시간 보장기능을 적용할 수 있도록 지원하는 크로스 레이어 구조를 제안한다. 이 구조를 통해 우리는 리눅스 커널에 존재하는 실시간 스케줄러를 사용하여 태스크가 실시간으로 실행될 수 있도록 지원한다. 또한 다양한 목적을 가진 어플리케이션이 공존하는 스마트폰 시스템에서 실시간성을 요구하는 어플리케이션에 대해 차별적으로 실시간성을 보장할 수 있다. 소프트 리얼타임 특성을 가지는 멀티미디어 태스크를 실시간 태스크로 실행하고 실제 스마트폰에서 실행시켰을 때 시스템에 높은 부하가 걸릴 때에도 합리적인 실시간 보장성을 얻을 수 있다. 음악을 재생한 실험에서는 1200개의 프로세스가 백그라운드 태스크로 실행되는 상황에서도 끊김을 느낄 수 없을 정도로 QoS를 보장성이 높은것을 확인 하였다. 본 연구에서 제안하는 실시간성 지원을 위한 크로스 레이어를 통해 스마트폰은 낮은 비용으로 기존의 어플리케이션을 변경하지 않으면서 실시간 특성을 지원할 수 있다.