Joint Computation and Communication Cooperation for Mobile Edge Computing

This paper proposes a joint computation and communication cooperation approach in mobile edge computing (MEC) systems for improving the energy efficiency in mobile computing. In particular, we consider a basic three-node MEC system that consists of a user node, a helper node, and an access point (AP) node attached with an MEC server. We focus on the user's latency-constrained computation over a finite-length block and develop a four-slot protocol for implementing the joint computation and communication cooperation. Under this setup, we jointly optimize the task partition and time allocation, and the transmit power for offloading and central processing unit (CPU) frequencies of local computing at the user and the helper, so as to minimize their total energy consumption subject to the user's computation latency constraint. This problem is optimally solved via convex optimization techniques. Numerical results show that the proposed approach significantly improves the computation capacity and the energy efficiency for the user, as compared to other benchmark schemes without such a joint design.