Big Data Analytics for Large Scale Wireless Networks: Challenges and Opportunities

TL;DR

This paper surveys big data analytics approaches for large scale wireless networks, highlighting challenges across data acquisition, preprocessing, storage, and analytics, and discussing future research directions.

Contribution

It categorizes the big data analytics life cycle for wireless networks and reviews technical solutions and open issues at each stage.

Findings

Identifies key challenges in big data management for wireless networks

Provides a comprehensive survey of existing technical solutions

Outlines future research directions in the field

Abstract

The wide proliferation of various wireless communication systems and wireless devices has led to the arrival of big data era in large scale wireless networks. Big data of large scale wireless networks has the key features of wide variety, high volume, real-time velocity and huge value leading to the unique research challenges that are different from existing computing systems. In this paper, we present a survey of the state-of-art big data analytics (BDA) approaches for large scale wireless networks. In particular, we categorize the life cycle of BDA into four consecutive stages: Data Acquisition, Data Preprocessing, Data Storage and Data Analytics. We then present a detailed survey of the technical solutions to the challenges in BDA for large scale wireless networks according to each stage in the life cycle of BDA. Moreover, we discuss the open research issues and outline the future directions in this promising area.