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研究生： 林弘恆
Lin, Hong-Hen
論文名稱： 基於Lambda架構之語義物聯網開發及實現
The development and implementation of Lambda architecture based Semantic Web of Things
指導教授： 楊中平
Young, Chung-Ping
學位類別： 碩士
Master
系所名稱： 電機資訊學院 - 資訊工程學系
Department of Computer Science and Information Engineering
論文出版年： 2019
畢業學年度： 107
語文別： 英文
論文頁數： 59
中文關鍵詞： 物聯網 、物聯網網路 、語意物聯網 、Lambda架構
外文關鍵詞： IoT (Internet of Things), WoT(Web of Things), SWoT(Semantic Web of Things), Lambda architecture
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    • 物聯網於現今的技術中日漸趨於成熟，在各領域上有明顯的進展，網路的進步也驅使資料的傳輸上更加地快速。然而在使用者和服務端對於即時性資料及非即時資料的傳輸上沒有明確地訊息傳輸，讓雙方可以互相地去明白彼此的意思。因此需要將現實生活上的知識結構轉化為雙方可了解資訊。本文利用Lambda架構的即時性，使資料能夠更明確地分流處理。我們建立Lambda物聯網語意平台，使得物聯網裝置再透過各自的物聯網語意，讓使用者明白傳遞之資訊，並且透過即時資訊和非即時資料分歧傳送增加了傳送資訊的效率。

    Internet of Things is becoming more and more mature in current technology, and there are obvious progress in every fields. The progress of the network has also driven the transmission of data more quickly. However, there is no clear message transmission between the user and the server for the transmission of the instantaneous data and the non- real-time data, so that both sections can understand each other's meanings. Therefore, it is necessary to transform the knowledge structure in real life into information that both sections can understand. This paper uses Lambda architecture to establish the Lambda SWoT platform, which enables the IoT devices to communicate their information through Internet of Things, so that users can understand the information transmitted and increase the efficiency of transmitting information through real-time messaging and non-real-time data divergence.

    Abstract I 摘要 II Acknowledgement III List of Figures VI List of Tables VII Abbreviation VIII Chapter 1. Introduction 1 1.1 Overview 1 1.2 Motivation 1 1.3 Thesis Organization 3 Chapter 2. Related Work 4 2.1 Web of things 4 2.2 Semantic web 6 2.3 Data processing schema 8 2.4 Other works 10 2.4.1 Iotivity 10 2.4.2 MQTT 11 2.4.3 Ontology 11 Chapter 3. System architecture 13 3.1 Physical phase 14 3.2 Allocation phase 15 3.3 Processing phase 17 3.4 Semantic phase 19 3.5 Application phase 21 3.6 Data type and data storage 22 Chapter 4. Implementation 26 4.1 Overall Configuration 26 4.2 Data Flow Design 28 4.3 Physical stage 30 4.3.1 Output control data flow 30 4.3.2 Input non-real-time data flow 31 4.3.3 Input real-time data flow 32 4.4 Allocation stage 33 4.5 Processing stage 34 4.5.1 Topology 34 4.5.2 Contents of spouts and bolts 35 4.6 Semantic stage 37 4.7 Application stage 38 Chapter 5. Experiment results 40 5.1 Experimental data collection 40 5.2 Transaction successful rate 40 5.3 Transaction latency time comparison 41 5.3.1 At 2 bytes 42 5.3.2 At 4 bytes 42 5.3.3 At 8 bytes 43 5.3.4 At 16 bytes 43 5.3.5 At 32 bytes 44 5.3.6 At 64 bytes 44 5.3.7 At 128 bytes 45 5.3.8 At 256 bytes 45 5.3.9 At 512 bytes 46 5.3.10 At 1k bytes 46 5.3.11 At 2k bytes 47 5.3.12 At 4k bytes 47 5.3.13 At 8k bytes 48 5.3.14 At 16k bytes 48 5.3.15 At 32k bytes 49 5.3.16 At 64k bytes 49 5.3.17 At 128k bytes 50 5.3.18 At 256k bytes 50 5.3.19 At 512k bytes 51 5.3.20 At 1m bytes 51 5.4 Overall discussion 52 Chapter 6. Conclusion 53 6.1 Conclusion 53 6.2 Future work 54 Reference 55

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