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    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/83820

    Title: 應用 k-means 建立邊緣運算資源及結合模糊理論調整卸載之研究;The Study of Using k-means to Establish Edge Computing Resources and Adjusting offloading with Fuzzy Theory
    Authors: 吳重震;Wu, Zhong-Zhen
    Contributors: 通訊工程學系
    Keywords: 邊緣計算;模糊理論
    Date: 2020-07-23
    Issue Date: 2020-09-02 17:10:10 (UTC+8)
    Publisher: 國立中央大學
    Abstract: 隨著即將進入 5G 的時代,物聯網即將成為下一個會大幅度改變社
    更為完善。為此,本篇論文即是研究利用 K-means 配合終端設備位置
    到優化延遲的結果。;As the 5G era is coming, IoT is about to become the next technology that will greatly change the society, and there will be a great amount of data flow that needs to be processed.
    However, cloud computing service is to centrally transmit the data that terminal device required to the cloud server, and then transmit it back to the terminal device. When a large amount of data flows is being transmitted, centralized cloud computing cannot meet certain terminal devices with specific needs.
    For example, Internet of Vehicles(IoV) requires low-latency services to deal with emergencies in real time; or the smart city also needs low-latency services to achieve real-time public safety maintenance. Therefore, edge computing can solve this problem of cloud computing. Edge computing brings computing resources closer to terminal devices, enabling the IoT architecture to quickly process data, and to be more completed by processing the data with low latency.
    In this thesis, we use the K-means based on the location of terminal equipment to deploy edge computing resources in the geographical environment. Then, we use fuzzy inference system to efficiently offload the data of the terminal device to the nearby edge servers, which improves the latency of terminal equipment.
    At last, we add handoff system to deal with the problem of the overloaded edge servers, and to improve the latency of the mobile device.
    Appears in Collections:[通訊工程研究所] 博碩士論文

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