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Big data analytics in telecommunications: Literature review and architecture recommendations

journal contribution
posted on 2024-10-30, 01:19 authored by H Zahid, T Mahmood, Md MorshedMd Morshed, T Sellis
This paper focuses on facilitating state-of-The-Art applications of big data analytics BDA architectures and infrastructures to telecommunications telecom industrial sector. Telecom companies are dealing with terabytes to petabytes of data on a daily basis. IoT applications in telecom are further contributing to this data deluge. Recent advances in BDA have exposed new opportunities to get actionable insights from telecom big data. These benefits and the fast-changing BDA technology landscape make it important to investigate existing BDA applications to telecom sector. For this, we initially determine published research on BDA applications to telecom through a systematic literature review through which we filter 38 articles and categorize them in frameworks, use cases, literature reviews, white papers and experimental validations. We also discuss the benefits and challenges mentioned in these articles. We find that experiments are all proof of concepts POC on a severely limited BDA technology stack as compared to the available technology stack , i.e., we did not find any work focusing on full-fledged BDA implementation in an operational telecom environment. To facilitate these applications at research-level, we propose a state-of-The-Art lambda architecture for BDA pipeline implementation called LambdaTel based completely on open source BDA technologies and the standard Python language, along with relevant guidelines. We discovered only one research paper which presented a relatively-limited lambda architecture using the proprietary AWS cloud infrastructure. We believe LambdaTel presents a clear roadmap for telecom industry practitioners to implement and enhance BDA applications in their enterprises.

History

Volume

7

Issue

1

Start Page

18

End Page

38

Number of Pages

21

eISSN

2329-9274

ISSN

2329-9266

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Peer Reviewed

  • Yes

Open Access

  • No

Acceptance Date

2019-09-26

External Author Affiliations

Institute of Business Administration, Pakistan

Era Eligible

  • Yes

Journal

IEEE/CAA Journal of Automatica Sinica