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Research and review articles are invited for publication in September - October 2026 (Volume 18, Issue 1) Submit manuscript

Reviewing the application of big data analytics in satellite network management to optimize performance and enhance reliability, with implications for future technology developments

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  • Reviewing the application of big data analytics in satellite network management to optimize performance and enhance reliability, with implications for future technology developments

Nneka Adaobi Ochuba 1, *, David Olanrewaju Olutimehin 2, Olusegun Gbenga Odunaiya 3 and Oluwatobi Timothy Soyombo 3

1 Independent Researcher, UK.
2 Christfill Global Enterprises, Lagos Nigeria.
3 Havenhill Synergy Limited, Nigeria.
 
Review Article
Magna Scientia Advanced Research and Reviews, 2024, 10(02), 111-119
Article DOI: 10.30574/msarr.2024.10.2.0048
DOI url: https://doi.org/10.30574/msarr.2024.10.2.0048
Received on 06 February 2024; revised on 13 March 2024; accepted on 15 March 2024
The application of big data analytics in satellite network management has emerged as a transformative approach to optimize performance and enhance reliability in the satellite telecommunications industry. This paper reviews the current state of big data analytics in satellite network management, highlighting its key applications and benefits. By analyzing large volumes of data generated by satellite networks, big data analytics enables satellite telecommunications companies to gain valuable insights into network performance, identify potential issues, and take proactive measures to ensure optimal performance. One of the key applications of big data analytics in satellite network management is predictive maintenance. By analyzing historical data and equipment performance metrics, companies can predict when equipment is likely to fail and take preventive measures to avoid downtime. This not only improves network reliability but also reduces maintenance costs and improves overall operational efficiency. Another important application is network optimization. Big data analytics can analyze network traffic, weather conditions, and other factors to optimize satellite beam coverage, frequency allocation, and routing. This helps companies maximize bandwidth utilization, reduce interference, and improve service quality. The implications of big data analytics for future technology developments in satellite network management are significant. As the volume of data generated by satellite networks continues to grow, there is a need for advanced analytics tools and techniques to process and analyze this data efficiently. Future technology developments in areas such as AI, machine learning, and data visualization are expected to play a key role in enhancing the capabilities of big data analytics in satellite network management. In conclusion, the application of big data analytics in satellite network management offers significant benefits in terms of optimizing performance and enhancing reliability. By leveraging the insights provided by big data analytics, satellite telecommunications companies can improve operational efficiency, reduce costs, and deliver better services to their customers. Future technology developments will further enhance the capabilities of big data analytics, paving the way for more efficient and reliable satellite network management.
Big Data; Satellite Network; Performance; Reliability; Management
https://msarr.magnascientiapub.com/sites/default/files/fulltext_pdf/MSARR-2024-…

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Nneka Adaobi Ochuba, David Olanrewaju Olutimehin, Olusegun Gbenga Odunaiya and Oluwatobi Timothy Soyombo. Reviewing the application of big data analytics in satellite network management to optimize performance and enhance reliability, with implications for future technology developments. Magna Scientia Advanced Research and Reviews, 2024, 10(2), 111-119. Article DOI: https://doi.org/10.30574/msarr.2024.10.2.0048

Copyright © Author(s). All rights reserved. This article is published under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits use, sharing, adaptation, distribution, and reproduction in any medium or format, as long as appropriate credit is given to the original author(s) and source, a link to the license is provided, and any changes made are indicated.


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