Monitoring Big Data Streams Using Data Stream Management Systems: Industrial Needs, Challenges, and Improvements

Real-time monitoring systems are important for industry since they allow for avoiding unplanned system stops and keeping system availability high. The technical requirements for such systems include being both scalable and online, as the amount of generated data is increasing with time. Therefore, m...

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Bibliographic Details
Published in:Advances in Operations Research Vol. 2023; pp. 1 - 12
Main Author: Alzghoul, Ahmad
Format: Journal Article
Language:English
Published: New York Hindawi 27.06.2023
John Wiley & Sons, Inc
Subjects:
Big Data
Collaboration
Construction equipment
Data analysis
Data search
Data transmission
Fault detection
Internet of Things
Literature reviews
Management systems
Monitoring
Monitoring systems
Operations research
Query formulation
Real time
Research methodology
Germany
ISSN:1687-9147, 1687-9155
Online Access:Get full text
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Summary:Real-time monitoring systems are important for industry since they allow for avoiding unplanned system stops and keeping system availability high. The technical requirements for such systems include being both scalable and online, as the amount of generated data is increasing with time. Therefore, monitoring systems must integrate tools that can manage and analyze the data streams. The data stream management system is a stream processing tool that has the ability to manage and support operations on data streams in real-time. Several researchers have proposed and tested real-time monitoring systems which have the ability to search big data streams. In this paper, the research works that discuss the analysis of online data streams for fault detection in industry are reviewed. Based on the literature analysis, the industrial needs and challenges of monitoring big data streams are presented. Furthermore, feasible suggestions for improving the real-time monitoring system are proposed.
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ISSN:1687-9147
1687-9155
DOI:10.1155/2023/2596069