Big Data Analytics in Densely Crowded Environments Enables 5G

Dear Colleagues,

Aim and Scope

The convergence of fifth generation (5G) networks and big data analytics in today’s smart systems and devices is expected to disrupt the Information and Communications Technology (ICT) ecosystem. 5G wireless networks will be radically different from previous generations as it will provide ultra-reliable and low latency communications, support massive machine type communications, and introduce enhanced mobile broadband. These three goals stem from the diverse use cases and application domains envisioned for 5G, which include the sensed data, the Internet of Things (IoT), and connected vehicles, to name a few. The combined strong effect of these technologies will create many opportunities for systems to rely on data analytics and ultra-reliable and low latency communications. The challenge is the ability to digest the huge amounts of unstructured big data in densely crowded environments, such as stadiums and theaters, in an intelligent way to extract useful insights, drive automated feedback, and guide decision-making.

To meet these goals, 5G should deliver significantly high data rates, traffic capacity, connection density, energy efficiency, as well as improved user experience and significantly reduced latency. To achieve these deliverables, 5G will be required to leverage big data analytics to proactively allocate network resources. More specifically, the data aggregated by the different 5G devices and systems can be utilized, using elegant big data analytics techniques, in order to provide descriptive, predictive, and prescriptive functionalities.

The aim of this Special Issue is to bring together engineers, researchers, and practitioners interested in the advances and applications in the field of big data analytics in densely crowded environments and 5G. Participants are invited to submit and discuss recent developments and challenges in this field. This Special Issue focuses on innovative applications, tools, and frameworks in all technology areas related to big data in the context of densely crowded environments enabling 5G. Papers describing original and novel work, advanced prototypes, and systems and tools are encouraged.

Topics of Interest:

• Orchestration of big data analytics enabling 5G
• Congestion mitigation in densely crowded environments
• Big data for augmenting QoS and user’s QoE
• Application of AI and ML for big data analysis in 5G networks
• Big data analytics to improve QoS in 5G networks
• Big data processing in 5G
• Big data analytics in connected vehicles using 5G
• Big data analytics for service managements
• Big data analytics to maximize performance in 5G networks
• Big data analytics to minimize operational management in 5G
• Big data analytics to optimize 5G radio access networks
• Application of huge data delivery for fog, cloud, and MEC
• Big data representation and modeling in 5G
• Social media data analysis for 5G
• Neural networks and reinforcement learning for big data analysis

Prof. Hussein T. Mouftah
Dr. Moayad Aloqaily
Dr. Ala Abu Alkheir
Guest Editors

Manuscript Submission Information

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• big data analytics
• 5G
• Internet of Things
• QoS and QoE
• connected data analytics
• connected vehicles
• ML, AI, and neural networks