推播服務為網際網路一項重要服務，Google的免費推播服務Google Cloud Messaging就是一項推播服務標準介面，另外，一些社群網路軟體，也提供推播的服務，例如：LINE、Facebook messager、Microsoft Skype。然而上述這些服務，並非適合所有的應用，特別是API (Application Programming Interface)常常不符合需要，或者傳遞訊息的長度或型式(如：只允許文字訊息)。所以開發新的推播服務，是有其需求，本論文就是研究如何設計與建置一個推播服務系統。
本論文採用Apache kafka開放軟體做為訊息儲存系統，考慮以web-programming為基礎的API，以達到跨平台的目的。網頁是基於瀏覽器去讀取，所以平台的差異自然是由瀏覽器去處理，加上HTML5轉apk和ipa的工具，無論是要使用瀏覽器、Android或者iOS的App，都是同樣的程式去執行，充分展現跨平台的優點。因此本論文將以Node.js為主軸，連接Apache Kafka和HTML5，完成一個跨平台的即時推播系統介面。

Push service is an important Internet service, which has a big capacity buffering system to keep all messages, push engine to forward messages to their receiver, and API (Application Programming Interface) to provide service interface to users. Google GCM (Google Cloud Messaging) is a well-known free push service. The other social network applications, e.g., LINE, Facebook messager, Microsoft skype, have similar push service. However, not all these service can meet requirements of all applications because of constraints in these services, for example, message length and type (multimedia or text only), API, etc.
It may be required to design and implement a customized push service. In this thesis, we develop a push system, which contains a buffering subsystem, push engine and API. With web-based design, it is platform-independent and can run over different operating systems. It guarantees reliability, allows multimedia message, and is real-time. HTML5, Apache Kafka and Node.js are the main tools used in our system. Finally, there are performance comparison illustrated in the experiment report in the thesis.

論文審定書 i
誌謝 ii
摘要 iii
Abstract iv
目錄 v
圖次 viii
表次 ix
第一章 緒論 1
1.1. 研究動機與目的 1
1.2. 論文架構 2
第二章 研究背景 3
2.1. Google Cloud Messaging 3
2.2. HTML5 4
2.3. JavaScript 5
2.4. Node.js 6
2.4.1. NPM 7
2.4.2. Kafka-node 7
2.5. WebSocket 7
2.5.1. HTTP/1.1 v.s. WebSocket 7
2.5.2. polling v.s. WebSocket 9
2.6. Apache ZooKeeper 11
2.7. Apache Kafka 12
2.7.1. Kafka簡介 12
2.7.2. Kafka架構 13
2.7.3. Kafka特色 14
2.8. JSON 14
第三章 系統設計及架構 15
3.1. 系統需求 15
3.1.1. Server端需求 15
3.1.2. Client需求 15
3.2. 系統架構 17
第四章 系統實作 18
4.1. Producer端 18
4.1.1. Kafka broker開啟刪除權限 18
4.1.2. 增加傳輸上限 19
4.1.3. 列出當前已存在topic 19
4.1.4. 即時動態建立/刪除topic 21
4.1.5. 刪除topic 22
4.1.6. 建立資料格式 22
4.1.7. Socket.io 24
4.2. Consumer端 25
4.2.1. 自動化增加topic 25
4.2.2. 自動化刪除topic 28
4.2.3. 訂閱/取消訂閱 29
第五章 系統成果展示 31
5.1. API應用呈現 31
5.2. 效能比較 37
第六章 結論與未來展望 38
參考文獻 39
附錄A 42
Kafka環境建置與操作 42
Node.js環境建置 43

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