With the rapid development of mobile communications and the explosive usage of mobile devices (i.e., smart phones, laptops, tablets, etc.), the mobile Internet facilitates us with a pervasive and powerful platform to provide emerging applications. However, many mobile devices usually have limited computation capabilities and battery power. Migrating computational tasks from the distributed devices to the infrastructure-based cloud servers has the potential to address the aforementioned issues. Mobile Edge Computing (MEC) is an emerging paradigm, which aims to provide better services by moving infrastructure-based cloud resources (computation, storage, bandwidth, etc.) to the edge of the network. Different from the traditional cloud, MEC is close to the mobile users. This reduces the access delay and the cost of using the cloud service. MEC is rapidly becoming a key technology of 5G and beyond, achieving the key technical indicators of 5G business, such as ultra-low latency, ultra-high energy efficiency, and ultra-high reliability.

There are several challenges for scheduling the limited and heterogeneous MEC resources. First, how to implement a cross-layer optimization policy for MEC that jointly optimizes the application layer, network layer, data link layer, as well as the physical layer of the protocol stack using an application-oriented objective function while satisfying the different user service requirements (i.e., energy saving, reducing execution delay, reducing price, etc.). Second, a theoretical framework of cross-layer optimization to balance the efficiency and fairness of resource allocation of MEC, as well as maximizing the profit of MEC service providers, needs to be explored. Third, how to design cross-layer collaborative distributed resource management systems that meet the harsh requirements of MEC such as latency, scalability and mobility support also needs to be considered. In addition, it is also essential to jointly optimize the resource allocation of computation and communication of both the mobile users and the MEC service provider to minimize the total energy consumption subject to the users’ latency constraint.

We invite researchers from both academia and industry to contribute original papers providing their state-of-the-art technologies and ideas covering all aspects of Mobile Edge Computing and applications. The purpose of this Special Issue is to publish high-quality research papers as well as review articles addressing recent advances in MEC for 5G and beyond.

Potential topics include but are not limited to the following:

• Theoretical modelling and performance analysis of resource optimization for MEC
• Joint cross-layer resource allocation for MEC
• Energy aware ME planning for wireless networks and 5G
• New integration resource management architecture of cloud and MEC
• Cross-layer service discovery and service recommendations for MEC
• Multi-user computation offloading for MEC
• Multi-edge-server collaboration for MEC
• Delay minimization service provision for MEC
• Cross-layer collaborative distributed systems for MEC
• Software-defined MEC
• Software-defined offloading for MEC
• Mobility management for MEC
• Security, privacy, and trust of MEC
• Cross-layer collaborative MEC
• Applications such as smart city, smart grid, and Intelligent Transportation Systems