Toward Real-Time High-Frequency Stock Monitoring System Using Node.js

  • Hao Qu
  • Kun Ma
  • Zhe Yang
  • Xuewei Niu
  • Ajith Abraham
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 614)

Abstract

Investing in stocks is a very popular financial management for modern people. Accurate data is aided for investor to make better decisions. But there are some challenges to design such a real-time system to present high-Frequent data. This paper introduced a solution toward real-time high-frequency stock monitoring system. The architecture, process and implementation of this system are presented respectively. This system is better in real-time monitoring, distributed services, high degree of concurrency, and interactive user experience using cache, load balancing, and CDN techniques. It is evaluated that Node.js performed well with advantages of its single thread event-driven mode and asynchronous I/O when it was in the environment of high concurrency.

Keywords

WebSocket High frequency Stock monitoring Node.js Socket.io 

Notes

Acknowledgments

This work was supported by the Teaching Research Project of University of Jinan (J1524), the Project of Cooperative Education of The Ministry of Education (201601018009), the School-Enterprise Cooperation Project of 2017 Tencent Education Reform of Innovation and Entrepreneurship, the Science and Technology Program of University of Jinan (XKY1734), the Open Project Joint Funding of Information Science and Engineering School of Linyi University and Discipline Team of Intelligent Logistics and Information Engineering (LDXX2017KF155), the Shandong Provincial Natural Science Foundation (ZR201702170261), the Shandong Provincial Key R&D Program (2015GGX106007 & 2016ZDJS01A12), and the Project of Shandong Province Higher Educational Science and Technology Program (J16LN13).

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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Hao Qu
    • 1
  • Kun Ma
    • 1
    • 2
  • Zhe Yang
    • 1
    • 3
  • Xuewei Niu
    • 1
  • Ajith Abraham
    • 4
  1. 1.School of Information Science and EngineeringUniversity of JinanJinanChina
  2. 2.Shandong Provincial Key Laboratory of Network Based Intelligent ComputingUniversity of JinanJinanChina
  3. 3.School of Computer Science and TechnologyShandong UniversityJinanChina
  4. 4.Machines Intelligence Research Labs (MIR Labs), Scientific Network for Innovation and Research ExcellenceAuburnUSA

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