|Authors||K. Zhang, Y. Mao, S. Leng, Q. Zhao, L. Li, X. Peng, L. Pan, G. Zhang, S. Maharjan and Y. Zhang|
|Title||Energy-efficient Offloading for Mobile Edge Computing in 5G Heterogeneous Networks|
|Project(s)||The Center for Resilient Networks and Applications|
|Publication Type||Journal Article|
|Year of Publication||2016|
Mobile Edge Computing (MEC) is a promising paradigm to provide cloud-computing capabilities in close proximity to mobile devices in fifth-generation (5G) networks. In this paper, we study energy-efficient computation offloading mechanisms for MEC in 5G heterogenous networks. We formulate an optimization problem to minimize the energy consumption of the offloading system, where the energy cost of both task computing and file transmission are taken into consideration. Incorporating the multi-access characteristics of the 5G heterogenous network, we then design an Energy-Efficient Computation Offloading (EECO) scheme, which jointly optimizes offloading and radio resource allocation to obtain the minimal energy consumption under the latency constraints. Numerical results demonstrate energy efficiency improvement of our proposed EECO scheme.