Smart Internet of Things (IoT) can help provide people with a better quality of life by leveraging the advances in information and communication technology. With the explosive growth of smart IoT, a massive amount of raw data will be generated by different computation-intensive or latency-sensitive applications, such as connected cars, intelligent recognition, and health monitoring. Dealing with such massive data is a major challenge in smart IoT, leading to the emergence of mobile edge computing (MEC). At the same time, artificial intelligence technologies, such as statistical learning and deep recurrent neural networks, etc., are expected to construct the intelligent network for improving the quality of experience. Thus, intelligent MEC - a proactive, self-aware, self-adaptive, and predictive computing paradigm - has an important role to play in future smart IoT, smart mobile devices, and mobile-devices powered edge systems, such as smart homes, smart transport, weather systems, vehicular traffic, environmental pollution, surveillance systems, smart energy, and smart grids.

Although an enormous amount of effort has been made in intelligent MEC, there are still several vital and challenging problems to be solved. Taking vehicle networking as an example, many kinds of vehicles generate an extremely large amount of data simultaneously, and different types of data have diverse requirements in terms of latency, computation, reliability, and security, etc. How to enable intelligent MEC system architectures to realize the real-time communication, computation, management, and control in vehicle networking has not yet been completely addressed. In addition, although intelligent techniques have promoted the existing network performance to some extent, with the continuously growing diversity of services and complexity of mobile network architectures, learning-based methods need to be further analyzed and developed in network management, resource optimization, and in-depth knowledge discovery in complex environments.

This Special Issue aims to attract and disseminate high-quality research results and practical solutions from both academia and industry to advance the intelligent MEC for smart IoT and mobile-devices powered edge systems. We welcome both original research and review articles.

Potential topics include but are not limited to the following:

• Big data analytics and processing in intelligent MEC
• Mobile-devices powered edge computing systems
• System architecture scheme for intelligent MEC
• Deep learning-based content caching for MEC
• Slice-based resource allocation and scheduling for MEC
• Energy efficiency in intelligent MEC for smart IoT
• Utility-driven multi-queue admission control for MEC
• Privacy and security in intelligent MEC for smart health
• Resource allocation for vehicular communications in smart IoT
• Intelligent traffic forecasting and offloading in MEC for smart transportation
• Joint optimization of computation offloading and resource allocation in smart satellite
• Performance analysis, test bed and simulation tools in intelligent MEC for smart IoT