The International Telecommunication Union (ITU) has identified three broad use cases: enhanced mobile broadband (eMBB), ultra-reliable and low-latency communication (uRLLC), and massive machine-type communications (mMTC). 5G networks are expected to allow the coexistence of these use cases over the same physical infrastructure. Due to diversified and stringent service requirements in different use cases, 5G and beyond-5G need an intelligent way of managing the various physical resources including computing, networking and storage resources. The resources allocated to each service should meet the requirement precisely while at the same time maximising the resource utilisation of the physical infrastructure.

5G not only involves radio part, but also core network, Internet and datacenter parts. Different from the existing works focusing on either radio part or core part, this special issue focuses on the end-to-end intelligent resource management, from radio access networks to core networks (and up to datacenter networks). That is because end-to-end performance needs to be guaranteed to provide satisfactory QoS for diversified services with different requirements in 5G and beyond. Reciprocal effects may exist among different services vertically, and also, for the same service, between radio access networks and core networks horizontally; this cannot be ignored and need to be learned and considered cognitively for resource allocation and scheduling in 5G and beyond.

In addition, from 3GPP Release 15 to Release 16, the control plane and user plane splitting has been planned for more functionalities in the core network to satisfy the stringent requirements of uRLLC use cases. The intelligent resource management for the involved functionalities of a service is an emerging challenge to be addressed by the network and Telcom research community.

Learning from massive network data to produce cognitive knowledge for the end-to-end resource management in 5G is still cumbersome; real-time network management is still far from mature for the services with stringent requirements in 5G and beyond. Many research challenges still need to be addressed to achieve a fully intelligent resource management for 5G and beyond networks.

This special issue is devoted to the most recent developments and research outcomes addressing the related theoretical and practical aspects on intelligent resource management for 5G and beyond, and it also aims to provide worldwide researchers and practitioners an ideal platform to innovate new solutions targeting at the corresponding key challenges. Topics of interest include, but are not limited to:

Architectures for end-to-end cognitive network/resource management for 5G and beyond
- Machine learning algorithms and solutions for end-to-end intelligent resource management
- Deep learning and data mining in end-to-end intelligent resource management
- Scalability of end-to-end intelligent resource management for 5G and beyond
- Autonomic monitoring and measurements in end-to-end intelligent resource management for 5G and beyond
- Autonomic analysis, autonomic and execution in end-to-end intelligent resource management for 5G and beyond
- Sustainability of end-to-end intelligent resource management for 5G and beyond
- End-to-end QoS/QoE/SLA guarantee in intelligent resource management for 5G and beyond
- Knowledge base for end-to-end intelligent resource management for 5G and beyond
- Intelligent network management for 5G and beyond
- Security, privacy and trust for end-to-end intelligent resource management for 5G and beyond

Submission Guidelines
Authors are invited to submit original and previously unpublished works. Submissions should follow the author guidelines of IEEE Transactions on Cognitive Communications and Networking. The complete instructions for prospective authors can be found on the IEEE TCCN Manuscript Central page. All submissions will undergo initial screening by the Guest Editors for fit to the theme of the Special Issue.

Important Date
Submission Deadline: 1 September 2019
First Reviews Complete: 1 November 2019
Revision Due: 15 December 2019
Final Review Decision: 15 January 2020
Final Papers to Publisher: 31 January 2020
Expected Publication: Second Quarter 2020

Guest Editors
Yulei Wu (Lead)
University of Exeter, United Kingdom

Dimitra Simeonidou
University of Bristol, United Kingdom

Cheng-Xiang Wang
Southeast University, China

Richard Yu
Carleton University, Canada

Sunghyun Choi
Seoul National University, Korea

Guoliang Xue
Arizona State University, USA

Adlen Ksentini
EUROCOM, France