Energy-Optimal and Delay-Bounded Computation Offloading in Mobile Edge Computing with Heterogeneous Clouds

Mobile Edge Computing (MEC), computation-intensive tasks are offloaded from mobile devices to cloud servers, and thus the energy consumption of mobile devices can be notably reduced. We have proposed task offloading in multi-user MEC systems with heterogeneous clouds, including edge clouds and remote clouds. Tasks are forwarded from mobile devices to edge clouds via wireless channels, and they can be further forwarded to remote clouds via the Internet. 

Mobile Edge Computing (MEC) is an emerging technology to offload applications with stringent delay requirements. In MEC systems, cloud servers are deployed at the edge of networks (e.g., base stations). To reduce the complexity, we propose an approximation algorithm with energy discretization, and its total energy consumption is proved to be within a bounded gap from the optimum.

Keywords: Mobile edge computing, Heterogeneous clouds, Energy saving, Delay bounds, Dynamic programming.