Emerging networking paradigms, including Information-Centric Networking (ICN), Software-Defined Networking (SDN), Mobile Satellite Communication Networks (MSCN) and Internet of Vehicles (IoV), have faced some severe challenges. For example, the dynamic network environment makes it very hard to optimise resource allocation. In addition, these networking paradigms usually have heterogeneous features, making it difficult to schedule traffic among different kinds of networks. These challenges can be addressed by the adaptive learning of Artificial Intelligence (AI) and the edge caching of edge computing.
AI can also help to establish a relatively optimal routing strategy, and perform congestion control by learning the dynamic network status. Just like AI, edge computing can help to provide users with a fast response, and deploying edge servers with strong computing and storage capabilities can greatly improve the performance of 4K/8K and VR/AR. However, despite their ability to improve network performance, many challenges remain. For example, the integrated architectures and frameworks are not clearly identified and the related protocols are not defined well.
For this special issue, we are seeking high-quality submissions that will help to advance the theoretical and practical frontiers of these emerging networking paradigms, so that we can gain a deeper understanding from both the academic and industrial viewpoints.
- New network architectures/protocols based on emerging networking paradigms and technologies
- Technologies integration: AI, edge computing with big data, 5G/6G, cloud computing, Network Function Virtualisation (NFV), etc.
- Intelligent routing, resource allocation and traffic scheduling in the emerging networking paradigms
- AI and edge computing for future Internet, such as ICN and SDN
- AI and edge computing for mobile Internet, such as MSCN, Mobile Social Network (MSN), Mobile Computing Network (MCN) and Vehicle Area Network (VAN)
- AI and edge computing for Knowledge Defined Networking (KDN)
- AI and edge computing for Data Center Network (DCN)
- AI and edge computing for Industry 4.0, smart cities, Internet of Things (IoT), e-health and AR/VR services
- AI and edge computing for video transmission optimisation
- AI for the heterogeneous edge computing-enabled networks
- New AI algorithms
- AI and edge computing for connectivity, intercommunication and integration between the Internet and SCN.
- Submission deadline: 31 May 2021
- Acceptance deadline: 30 November 2021
- Publication date: 31 January 2022
- Managing Guest Editor, Jianhui Lv, Tsinghua University, China. Email: email@example.com
- Yuhui Shi, Southern University of Science and Technology, China. Email: firstname.lastname@example.org
- Hui Cheng, University of Hertfordshire, UK. Email: H.Cheng@ljmu.ac.uk
- Zhiwei Lin, Queen's University Belfast, UK. Email: Z.Lin@qub.ac.uk
- Lianbo Ma, Northeastern University, China. Email: email@example.com