Energy optimal resource allocation for mobile edge computation offloading in presence of computing access point
Nima Nouri, Aliakbar Tadaion · 2018
Mobile edge computing (MEC) is a promising approach and popular mobile technology which provides cloud-computing capabilities in vicinity to smart mobile devices (SMDs) in fifth-generation (5G) networks. With this framework, SMDs are able to offload their computationally heavy applications, to the MEC servers on the edge of the network, instead of utilizing the cloud servers in the core network. In this paper, We propose an environment with one Macrocell and small cell with computational capability, where SMDs demand for computation offloading to an MEC server by proposing the joint optimization of computing and communication resources and offloading decisions with the aim of minimizing the energy required for offloading across all SMDs under delay limitations at the application layer in 5G heterogeneous networks. After formulation, we oserve that the resulting minimization problem is non-convex (in the objective function and also the constraints). In order to tackle with this problem, we propose an iterative algorithm, known as inner convex approximation technique, converging to a local optimal solution of the original noncon-vex problem. The numerical results illustrate energy efficiency improvement in joint allocation of computing and communication resources.