Communication-Efficient Offloading for Mobile-Edge Computing in 5G Heterogeneous Networks

Abstract

The unified management of IoT devices with interoperability can be inspired by cloud computing. In addition, sinking the 5G core network to the edge brings chances for the deployment of end-to-end ultralow-latency services. However, the resource efficiency brought by heterogeneous computing devices in 5G spectrum multiplexing environments has encountered challenges. To discuss this issue from a comprehensive perspective, this article first proposes an ultralow-latency service deployment architecture in 5G heterogeneous networks, and three cognitive engines are the key components for efficient service communication across the terminal/edge/cloud computing structure. Then we give an analysis of application task model in the proposed architecture, and following the service response time models are established. In addition, it is efficient to deploy multiuser tasks with constraint resources when the differentiated user requirements are met. Finally, we conducted some experiments and the result statistics are up to our expectations. The first one is the system performance under two microcloud covered cells, and the second one is the performance comparison of the proposed solution with three single scenes of terminal computing, edge computing and cloud computing.