Resource Allocation in Cloud–Edge–End Cooperation Networks

Dear Colleagues,

With the explosion in global mobile traffic, the improvement of network quality of service and the quality of end-user experience, by effectively allocating heterogeneous network resources, is a key issue that urgently requires a solution in future wireless networks. The collaborative allocation of cloud–edge–end resources can be studied to effectively overcome problems such as high latency and traffic load caused by cloud computing. Meanwhile, it can successfully avoid the problems caused by edge computing in terms of constrained, heterogeneous and dynamical resources, so as to satisfy the differentiated service requirements of massive Internet applications, and improve content distribution and resources utilization. However, realizing the collaborative allocation and intelligent optimization of cloud–edge–end resources in practical communication scenarios is challenging, and there are still many important open research problems. This Special Issue seeks to explore collaborative allocation and the intelligent optimization of cloud–edge–end resources and invites novel contributions from researchers and practitioners.

This Special Issue aims to provide a forum for the latest research, innovations, and applications of resource allocation in cloud–edge–end cooperation envrionments, in order to bridge the gap between theory and applications. We are seeking high-quality original research papers on topics including, but not limited to:

• Survey on the collaborative allocation and intelligent optimization of cloud–edge–end resources;
• Resource allocation and mobility management of cloud–edge–end cooperation;
• Machine learning and big-data-aided cloud–edge–end cooperation;
• Cloud–edge–end cooperation for integrated terrestrial and aerial 6G networks;
• Service-aware resource allocation for cloud–edge–end cooperation;
• Cloud–edge–end cooperation for ultra-reliable low-latency communication;
• QoS/QoE-aware resource allocation for cloud–edge–end cooperation;
• Mobility-aware content caching for cloud–edge–end cooperation;
• Cross-layer design, optimization and performance analysis for cloud–edge–end cooperation;
• Cross-domain collaborative allocation for cloud–edge–end resources;
• Advanced spatio-temporal prediction for content popularity;
• Coordinated and complementary transformation of heterogeneous cloud–edge–end resources.

Prof. Dr. Chao Fang
Prof. Dr. Zhuwei Wang
Dr. Na Li
Guest Editors

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