• Title/Summary/Keyword: 소사이어티 5.0

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A Privacy Approach Model for Multi-Access to IoT Users based on Society 5.0 (소사이어티 5.0 기반 IoT 사용자에 대한 다중 접근방식의 프라이버시 접근 모델)

  • Jeong, Yoon-Su;Yon, Yong-Ho
    • Journal of Convergence for Information Technology
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    • v.10 no.4
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    • pp.18-24
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    • 2020
  • Recently, research on Society 5.0 has been actively carried out in Japan. The Society 5.0 is used in various areas using IoT sensors. This paper proposes a privacy approach model of multiple approaches to IoT users based on Society 5.0. The proposed model used multiple methods of synchronizing important information of IoT devices with one another in the virtual environment. The proposed model improved the efficiency of IoT information by accumulating the weight of IoT information on a probability-based basis. Further, it improves the accuracy of IoT information by segmenting it so that attribute information is linked to IoT information. As a result of the performance evaluation, the efficiency of IoT devices has improved by an average of 5.6 percent, depending on the number of IoT devices and the number of IoT hub devices. Accuracy has improved by an average of 15.9% depending on information collection and processing.

Improving application startup time by automatic profiling (Automatic Usage Profiling을 통한 초기 앱 실행 속도 개선 방법)

  • Chae, Hyangseok;Baik, Jongmoon
    • Journal of Software Engineering Society
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    • v.28 no.1
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    • pp.1-6
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    • 2019
  • Google released an initial version of Android that runs Dex(Dalvik Executable) through the Dalvik Runtime. Since Dalvik Runtime is based on interpreter, JIT(Just-in-time) compilation has been applied to improve performance. After Lollipop(Android 5.0) Dalvik Runtime has replaced with ART Runtime which support AOT (Ahead-of-time) compilation of Dex into Native Code. The late st Android has a problem that the application execution speed is slow until the AOT compilation is completed according to the actual usage record after the installation of the app. To improve the problem we have investigate the characteristics of profile that can improve the execution speed of the application and generate the profile automatically. Finally we propose a method that can optimize the application at install time. With the proposed method we can optimize selectively at install time and can help improving the execution speed of the app from the initial execution.