پژوهشنامه پردازش و مدیریت اطلاعات

پژوهشنامه پردازش و مدیریت اطلاعات

Optimizing Telecommunications Network Performance through Big Data Analytics: A Comprehensive Evaluation

نوع مقاله : مقاله پژوهشی

نویسندگان
Leena Sameer Baddour 1
Faisal Ghazi Abdiwi 2
Moldoiarov Ularbek Duishobekovich 3
Mahmood Jawad Abu-AlShaeer 4
Ghanim Magbol Alwan 5
1 Al-Turath University, Baghdad 10013, Iraq
2 Al-Mansour University College, Baghdad 10067, Iraq
3 Osh State University, Osh City 723500, Kyrgyzstan
4 Al-Rafidain University College Baghdad 10064, Iraq
5 Madenat Alelem University College, Baghdad 10006, Iraq
10.22034/jipm.2025.728401
چکیده
ABSTRACT
Background: The telecommunication industry is currently witnessing an unparalleled growth in traffic data with a concomitant growth in the complexity of networks. As operators seek to achieve high availability of the networks, it is almost compulsory to employ the BDA for improved quality of service and increased operational performance.
Objective: The study aims to provide a systematic review of the deployment of BDA in enhancing the primary characteristic indicators of telecommunications networks, to include availability of upgraded latency and throughput levels and network dependability.
Methods: The research method used was summed up by quantitative analyses of the key performance parameters of the networks, along with the qualitative results of case studies conducted with major telecommunications operators. Information was collected from multiple networks as well as analyzed with the use of machine learning to be able to predict possible performance issues.
Results: The study demonstrates that there is the possibility for reducing latency utilizing BDA with enhancements of up to 40%. In addition, the throughput has been raised by an average of 30% and the predictable analytics lead to 25% reducing in network downtime to improve the reliability and satisfaction of the user experience.
Conclusion: The information provided in this study highlights the importance of Big Data Analytics for the telecommunication industry, proving that the proper integration can bring tangible improvements to the existing networks. One future development that constitutes the need for innovative analytical technologies is the rise in data traffic and sophisticated network requirements.
کلیدواژه‌ها
KEYWORDS: Big Data Analytics
Telecommunications
Network Performance
Latency
Throughput
Reliability
Predictive Analytics
Machine Learning
Data Traffic
Optimization

عنوان مقاله English

Optimizing Telecommunications Network Performance through Big Data Analytics: A Comprehensive Evaluation

نویسندگان English

Leena Sameer Baddour 1
Faisal Ghazi Abdiwi 2
Moldoiarov Ularbek Duishobekovich 3
Mahmood Jawad Abu-AlShaeer 4
Ghanim Magbol Alwan 5
1 Al-Turath University, Baghdad 10013, Iraq
2 Al-Mansour University College, Baghdad 10067, Iraq
3 Osh State University, Osh City 723500, Kyrgyzstan
4 Al-Rafidain University College Baghdad 10064, Iraq
5 Madenat Alelem University College, Baghdad 10006, Iraq
چکیده English

ABSTRACT
Background: The telecommunication industry is currently witnessing an unparalleled growth in traffic data with a concomitant growth in the complexity of networks. As operators seek to achieve high availability of the networks, it is almost compulsory to employ the BDA for improved quality of service and increased operational performance.
Objective: The study aims to provide a systematic review of the deployment of BDA in enhancing the primary characteristic indicators of telecommunications networks, to include availability of upgraded latency and throughput levels and network dependability.
Methods: The research method used was summed up by quantitative analyses of the key performance parameters of the networks, along with the qualitative results of case studies conducted with major telecommunications operators. Information was collected from multiple networks as well as analyzed with the use of machine learning to be able to predict possible performance issues.
Results: The study demonstrates that there is the possibility for reducing latency utilizing BDA with enhancements of up to 40%. In addition, the throughput has been raised by an average of 30% and the predictable analytics lead to 25% reducing in network downtime to improve the reliability and satisfaction of the user experience.
Conclusion: The information provided in this study highlights the importance of Big Data Analytics for the telecommunication industry, proving that the proper integration can bring tangible improvements to the existing networks. One future development that constitutes the need for innovative analytical technologies is the rise in data traffic and sophisticated network requirements.

کلیدواژه‌ها English

KEYWORDS: Big Data Analytics
Telecommunications
Network Performance
Latency
Throughput
Reliability
Predictive Analytics
Machine Learning
Data Traffic
Optimization

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  • تاریخ دریافت 25 مرداد 1404