Intelligent Provisioning and Management Technologies for IoT-Based Edge Networks

Dear Colleagues,

In recent years, the Internet of Things (IoT) has become very popular due to its ability to control real-world infrastructure. However, these devices generate a massive amount of data that can hardly be accommodated by resource-constrained IoT devices. Although cloud computing has proven successful in resolving the issue, it introduces other difficulties, such as delays due to the long distance between the cloud and IoT devices, for which we are witnessing edge computing gaining traction as a promising solution. For some years, the edge computing vision has kept the research community exploring the possibilities of key enabling technologies to deliver on its promise.

There have been some drastic developments in network virtualization, software defined networking, artificial intelligence, and cloud/distributed computing technologies. SDN/NFV can dynamically control the underlying devices for resource allocation with the help of virtualization techniques. ML/DL can be helpful in intelligent and efficient decision-making for edge resource management and offloading decisions. Additionally, IoT data can be stored and processed across the network and blockchain technology is expected to provide viable solutions to the provenance problem of the data. This Special Issue focuses on the recent advancement in distributed/cloud computing for wireless and IoT networks. Theoretical and practical solutions for distributed computing systems related to the design, analysis, and implementation of edge computing and networking are highly desirable.

Topics discussed in this SI include, but are not limited to, the following:

• Resrouce allocation and task scheduling for edge devices/servers;
• Dynamic configuration of IoT edge networks using SDN/NFV;
• Blockchain-based management and orchestration for IoT networks;
• ML/DL support for ultra-low latency applications at the edge of the network;
• Resource management of edge devices using ML/DL;
• Blockchain technology in edge and cloud computing.

Prof. Dr. Choonhwa Lee
Prof. Dr. Eun-Sung Jung
Dr. Zohaib Latif
Guest Editors

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