Knowledge-Defined Cloud-Native Networks: Applying AI and Cloud-Native Principles to Next-Generation Wireless Networks
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Intelligent Sensors".
Deadline for manuscript submissions: closed (18 December 2023) | Viewed by 3626
Special Issue Editors
Interests: wireless networks; edge computing; 5G and beyond networks; vehicular networks; network management; wireless communications
Interests: wireless networks; future internet/IoT; mobile networking; SDN/NFV; cloud/edge computing
Interests: network engineering; Internet security and privacy; telecommunications; software development; project management; life cycle costing; technical risk management
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
With the emergence of next-generation wireless technologies such as network slicing and multi-access edge computing (MEC), the role of artificial intelligence and cloud-native virtualization techniques becomes more critical, in particular for managing issues and challenges such as the inter-slice handover, network slice mobility, resource allocation and sharing among different MEC servers, UAV-based computational offloading, and MEC mobility management.
Conventional virtualization techniques using virtual machines are computationally intensive and unable to support the low latency requirements of 5G and beyond technologies and use cases, e.g., MEC-enabled vehicular networks and autonomous and connected vehicles. The conventional techniques do not provide the required scalability, portability, modularity, and flexibility. Advanced and lightweight virtualization techniques and the microservices architecture enabled by the cloud-native principles could support a new modular and scalable design with minimal hardware dependencies. This is achieved using a stateless and distributed model with loosely coupled network functions and services. The adaption of cloud-native principles and its application to wireless networks have the potential to support new and emerging services and address the open research issues and challenges that are faced in the effective realization of key 5G and beyond enabling technologies, e.g., network slicing and MEC. Integrating artificial intelligence with advanced cloud-native virtualization techniques could further enhance the existing capabilities of next-generation wireless networks and support new use cases, such as connected and autonomous vehicles.
The adaption of cloud-native virtualization techniques for wireless network functions using containerization technology such as Docker and the evaluation of AI-enabled microservices networking architecture for next-generation wireless networks, e.g., 5G and beyond, remains unexplored. In other words, minimal research is available. This Special Issue encourages authors from academics and industry to submit their novel contributions related to advancements made in using AI and cloud-native techniques for next-generation wireless technologies.
The topics of interest include but are not limited to:
- Integration of network slicing and MEC
- Application of AI to manage next-generation wireless networks
- Adaption of cloud-native principles for next-generation wireless networks
- Advanced virtualization techniques for wireless networks
- Novel networking architectures
- Cloud-native 5G core
- Application of containers in 5G and beyond wireless networks
- Al for the management of 5G network functions
- MEC services migration
- Network slice mobility
- Connected and autonomous vehicles
- Computational offloading
Dr. Syed Danial Ali Shah
Dr. Fontes Ramon Dos Reis
Dr. Mark Gregory
Guest Editors
Manuscript Submission Information
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Keywords
- software-defined networks
- connected and autonomous vehicles
- V2X
- SDN/NFV
- AI at the edge
- MEC
- beyond 5G networks
- network slicing
- Internet of Things
- vehicular networks
- resource allocation
- network mobility
- edge/cloud computing
- computational offloading
