Guest Editors
Pro. Sayed Chhattan Shah, Hankuk University of Foreign Studies, South Korea
Pro. Muhammad Bilal, Hankuk University of Foreign Studies, South Korea
Pro. Xiaolong Xu, Nanjing University of Information Science and Technology, China
Summary
Recent advances in mobile technologies have enabled a new class of smart city and fifth-generation (5G) network applications, such as merged reality and real-time situation analyses. These applications have diverse requirements, such as low latencies, high data rates, significant amounts of computing and storage resources, and access to sensors and actuators. To address the requirements of these applications, several edge computing systems, such as cloudlet computing, mobile edge computing, and fog computing, have been proposed. The deployment of edge computing systems requires the addition of new infrastructure or the updating of existing infrastructure. Edge computing systems also do not utilize the capabilities of end devices, such as smartphones, mobile robots, and smart vehicles, which are equipped with multicore central and graphical processing units, several sensors, or multiple wireless communication technologies.
To overcome the drawbacks of conventional edge computing systems, next-generation edge computing infrastructures such as a local or private edge cloud consisting of conventional and high-end devices such as robots and smartphones are required. This special issue invites contributions focusing on the design of intelligent edge computing architectures, middleware platforms, network protocols, and resource management algorithms leveraging for instance approaches based on machine learning, software-defined network, or container technologies to support the emerging smart city, IoT, and 5G network applications.
Keywords
Private micro data centers, Cloudlet computing systems, Edge clouds, Fog Computing, Multi-network management, Machine Learning based Network Protocols and algorithms
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