Energy-Efficient Offloading for Mobile Edge Computing in 5G Heterogeneous Networks
University of Electronic Science and Technology of China · Hunan Institute of Science and Technology · +1 more institution
Abstract
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 (EECO) mechanisms for MEC in 5G heterogeneous 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 heterogeneous network, we then design an EECO scheme, which jointly optimizes offloading and radio resource allocation to obtain the minimal energy consumption under the latency…
Citation impact
- FWCI
- 92.13
- Percentile
- 100%
- References
- 44
Authors
9- KZKe ZhangCorresponding
University of Electronic Science and Technology of China
- YMYuming Mao
University of Electronic Science and Technology of China
- SLSupeng Leng
University of Electronic Science and Technology of China
- QZQuanxin Zhao
University of Electronic Science and Technology of China
- LLLongjiang Li
University of Electronic Science and Technology of China
Topics & keywords
- Computer science
- Mobile edge computing
- Computation offloading
- Energy consumption
- Distributed computing
- Cloud computing
- Efficient energy use
- Edge computing
- Affordable and clean energy