Title page for etd-0817116-162149


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URN etd-0817116-162149
Author Mao-yao Li
Author's Email Address No Public.
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Department Computer Science and Engineering
Year 2016
Semester 1
Degree Master
Type of Document
Language zh-TW.Big5 Chinese
Title Study of Real-Time Streaming Processing for Fintech
Date of Defense 2016-08-26
Page Count 100
Keyword
  • Cloud Computing
  • Distributed Computing
  • Financial data
  • Apache Storm
  • Linux Container
  • Real-time Trading
  • Real-time Streaming
  • Fintech
  • Abstract Fintech is one of the most popular topics, along with the disruptive innovation raised and more and more applications need to use real-time computing, how to real-time processing large amounts of data computing becomes a significant issues, in this study will discuss in the program trading for Fintech.
    In regards of real-time computing system, Apache Storm is one of the famous distributed computing system, used by many company such as Twitter、Tahoo、Alibaba、Taobao…etc, Storm can be apply widly such as real-time analytics、online machine learning…etc. Therefore, in this paper, Storm will be used as a real-time computing system, for stocks that have sequential、non repeating、timeliness of these kinds of data type, research how to design Topology will have a better performance and experiment with qualitative research and quantitative research analysis Storm characteristics and configuration optimization, create an easy-to-use platform to monitor the resource and use.
    Advisory Committee
  • Wei-Kuang Lai - chair
  • Yaotsu Chang - co-chair
  • Jiunn-Ru Lai - co-chair
  • Shi-Huang Chen - co-chair
  • Chun-Hung Lin - advisor
  • Files
  • etd-0817116-162149.pdf
  • Indicate in-campus at 5 year and off-campus access at 5 year.
    Date of Submission 2016-09-17

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