Big Data Analytics for Wireless and Wired Network Design: A Survey
Mohammed S. Hadi, Ahmed Q. Lawey, Taisir E. H. El-Gorashi, and Jaafar, M. H. Elmirghani

TL;DR
This survey explores how big data analytics can enhance the design of wireless and wired networks by integrating advanced data processing techniques into network control and traffic management for improved performance.
Contribution
It provides the first comprehensive review of big data analytics applications in the design of diverse network types, covering concepts, frameworks, challenges, and future directions.
Findings
Big data analytics can significantly improve network performance and robustness.
Current efforts span academic and industrial sectors with diverse approaches.
Identified key challenges and future research opportunities in network design using big data.
Abstract
Currently, the world is witnessing a mounting avalanche of data due to the increasing number of mobile network subscribers, Internet websites, and online services. This trend is continuing to develop in a quick and diverse manner in the form of big data. Big data analytics can process large amounts of raw data and extract useful, smaller-sized information, which can be used by different parties to make reliable decisions. In this paper, we conduct a survey on the role that big data analytics can play in the design of data communication networks. Integrating the latest advances that employ big data analytics with the networks control/traffic layers might be the best way to build robust data communication networks with refined performance and intelligent features. First, the survey starts with the introduction of the big data basic concepts, framework, and characteristics. Second, we…
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