Intelligent Edge-Cloud Collaboration for Internet of Things

Dear Colleagues,

Deep learning, especially Deep Neural Networks (DNNs), have been widely used in mobile applications. However, due to the ever-increasing growth of Internet of Things (IoT) devices with resource-hungry applications and the unprecedented demands of computing capabilities, edge servers with limited resources cannot efficiently satisfy the requirements of the IoT applications with DNN training and DNN inference. DNN-based applications can be partitioned, with some layers being calculated on the IoT side and others on the edge/cloud server. Deep learning driven approaches can facilitate offloading decision making, dynamic resource allocation and content caching, and benefit in coping with the growth in volumes of communication and computation for emerging IoT applications. However, how to customize intelligent techniques for edge-cloud collaboration in IoTs is still under discussion. Learning algorithms in edge computing and cloud computing are still immature and inefficient.

This Special Issue is devoted to the most recent developments of edge intelligence technologies for IoT applications. Topics of interest include, but are not limited to, those listed below:

• AI-assisted edge computing, fog computing, and cloud computing;
• Intelligent decision making for task offloading, resource allocation, profiling, modelling, content caching, cyber-security, and privacy in IoTs;
• AI-based theories, scenarios and architectures of application placement, computation offloading or data offloading in IoTs;
• Deep learning driven latency and energy consumption model in IoTs;
• Joint communication and computation optimization for emerging IoT applications;
• Intelligent resource management and task scheduling;
• DNN-based application partitioning in IoTs;
• IoT applications based on cloud-edge-end computing paradigms;
• Caching assisted application outsourcing and task offloading in IoTs;
• Volunteer computing related technologies for vehicular edge computing;
• 5G beyond networks for Internet of Vehicles.

Dr. Huaming Wu
Dr. Chaogang Tang
Prof. Dr. Xiaolong Xu
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.