Resource Allocation in Multi-access Edge Computing for 5G-and-beyond networks

Innovative services with strict requirements are expected in the fifth generation (5G) of mobile networks and beyond. For example, the Ultra-Reliable Low-Latency Communication (URLLC) requires up to 1 ms latency, end-to-end security, and reliability of up to 99.999%. The Multi-access Edge Computing (MEC) promises to support the delivery of URLLC services by providing computing and storage resources in the proximity of user equipment. The data which previously needed to be processed and stored in the cloud systems can be kept at the edge network, decreasing the total latency and increasing the context-awareness, security, and dependability. Vastly available resources, which are available from cloud to edge, must be appropriately allocated to deliver a service efficiently. The resource allocation problem in MEC for 5G-and-beyond networks can be formulated differently, depending on the nature of the problem. This survey outlines the resource allocation problem as a proper problem formulation, which can be addressed by target, resource type, resource issue, and the considered assumptions. Moreover, this paper also describes the open issues and future directions for MEC resource allocation based on the state of the art on this research topic.

Automated summary

The fifth generation (5G) and beyond mobile networks require innovative services with strict requirements. For example, Ultra-Reliable Low-Latency Communication (URLLC) demands 1 ms latency, end-to-end security, and reliability up to 99.999%. Multi-access Edge Computing (MEC) supports URLLC by providing computing and storage resources near user equipment. It reduces latency, enhances context-awareness, security, and dependability by processing and storing data at the edge network instead of the cloud.