Open AccessEnergy‐efficient computation offloading in 5G cellular networks with edge computing and D2D communications
Author(s) -
Jia Qingmin,
Xie Renchao,
Tang Qinqin,
Li Xiaolu,
Huang Tao,
Liu Jiang,
Liu Yunjie
Publication year - 2019
Publication title -
iet communications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.355
H-Index - 62
eISSN - 1751-8636
pISSN - 1751-8628
DOI - 10.1049/iet-com.2018.5934
Subject(s) - computation offloading , mobile edge computing , computer science , server , edge computing , energy consumption , distributed computing , lyapunov optimization , computation , efficient energy use , cellular network , enhanced data rates for gsm evolution , mobile device , computer network , telecommunications , algorithm , lyapunov redesign , ecology , lyapunov exponent , artificial intelligence , chaotic , electrical engineering , biology , engineering , operating system
Computation offloading has been considered as one of the key research issues in edge computing fields. In order to reduce the energy consumption of the mobile terminal, the energy efficiency issue of computation offloading has attracted a lot of attention from academia and industry. In this study, the authors propose an energy‐efficient computation offloading scheme in 5G cellular networks with edge computing and device‐to‐device (D2D) communications. They consider the computation offloading to fog computing devices via D2D communications and mobile edge computing (MEC) servers via cellular networks. And thus the computation task execution model can be composed of local execution, fog computing device execution and MEC server execution. Then, they formulate the computation offloading issue as stochastic optimisation problem, and use the Lyapunov optimisation technology framework to solve this problem. Finally, extensive simulation results are presented to illustrate the effectiveness of the proposed scheme.