State-of-the-Art in Wireless Edge Networks

Dear Colleagues,

As edge servers and devices evolve in storage, computing, and processing capabilities, the paradigm of centralized networks is shifting to decentralized ones. In decentralized or distributed wireless networks, various wireless edge technologies have been largely developed to reduce service delays and excessive data traffic on the core network by efficiently utilizing improved resources and capabilities of storage, computing, and processing at the wireless edge. Representatively, with the development of memory and non-memory semiconductors, wireless caching and edge computing technologies have been extensively researched. Also, improved deep learning algorithms allow distributed learning, in which edge devices can train the deep neural network by themselves to contribute the global model training. Incorporating these recent wireless edge technologies, a novel wireless edge network is expected to control tradeoffs among various performance indicators and to optimize multiple tasks, such as communications, caching, computing, and learning. For this goal, this Special Issue aims to bring together researchers, industry practitioners, and individuals working on these related areas to share their new ideas, latest findings, and state-of-the-art results.

This Special Issue includes fundamental analyses and proposals of state-of-the-arts in wireless edge technologies, such as edge computing, wireless caching, and distributed learning, for a variety of application scenarios, such as cellular networks, Internet-of-Things, content delivery networks, vehicle-to-everything (V2X), distributed smart grids, etc.

You may choose our Joint Special Issue in Network.   

Dr. Minseok Choi
Dr. Joongheon Kim 
Guest Editors

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