Edge-Cloud Resource Trade Collaboration scheme in Mobile Edge Computing

Owing to the ability to provide better services for latency-intensive tasks than the cloud paradigm, Mobile Edge Computing (MEC) has attracted increasing attention recently. However, due to limited resources, MEC cannot handle large amount of computation tasks as the cloud paradigm. Most of the existing works design offload strategies for MEC by sharing the responsibility of total computation tasks with the cloud to provide more services, but neglecting the fact that the profit can be shared when sharing responsibility, which decreases the profit. To address this issue, we propose a trade collaboration framework for the MEC and the cloud paradigm, where the MEC can purchase resources from the cloud paradigm to process computation tasks under latency constraints. Without accurate information about required resources, this paper has designed an efficient resource trade scheme for the MEC to achieve their optimal purchased resources, such that the expected profit of the MEC can be maximized. Simulation results show that the proposed scheme can maximize the profit of the MEC and guarantee latency requirements.