Abstract

Liberalization has enhanced the global access to telecommunication and networking services. This could imply the need for advanced technologies to handle the growing telecom data demands. The exponential growth of mobile internet in telecommunication is adopting the big data platform for the data acquisition, storage and analysis to provide the value-added services. The main objective of this research paper is to demonstrate the use of Apache Hadoop ecosystem in Telecommunication Big data Analytics. Hadoop is an open-source and well known for distributed large dataset storage and processing mechanism with core modules HDFS, YARN, Hadoop Common and MapReduce. The study explores the use cases for Apache Hadoop ecosystem in the telecommunication sector and demonstrates the versatility of Hadoop in addressing different aspects of telecommunication data such as analysis of telecom network traffic logs, location-based services, call detail records (CDR), telecom user churn prediction, and anomaly detection. Finally, 77 research papers which implemented the Apache Hadoop in telecommunication big data processing efficiently retrieved from IEEE Xplore are reviewed and analysed. Scoping review and scientometrics analysis methodology have been used. The results of the study interpret the implications of Apache Hadoop in telecommunication big data analytics, offering insights into their use across various decision-making domains to enhance the potential impact of big data analytics in improving telecommunication services.

Authors

Arti Sawale, Paramjeet Kaur Walia
University of Delhi, India

Keywords

Telecommunication, Big data, Hadoop, Scientometrics, IEEE