Energy-Efficient Task Offloading Based on Differential Evolution in Edge Computing System With Energy Harvesting | Zendy

Yingying Sun | Zendy; Chunhe Song | Zendy; Shimao Yu | Zendy; Yiyang Liu | Zendy; Hao Pan | Zendy; Peng Zeng | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

Energy-Efficient Task Offloading Based on Differential Evolution in Edge Computing System With Energy Harvesting

Author(s) -

Yingying Sun,

Chunhe Song,

Shimao Yu,

Yiyang Liu,

Hao Pan,

Peng Zeng

Publication year - 2021

Publication title -

ieee access

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.587

H-Index - 127

ISSN - 2169-3536

DOI - 10.1109/access.2021.3052901

Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation

To optimize the energy efficiency of edge computing system with energy harvesting, this paper proposes an energy-efficient task offloading method optimized by differential evolution. First, a wireless edge computing network model is established to analyze the energy harvesting, task offloading and task calculation of the system, as well as the total number of calculated bits and total energy consumption of the system. Second, according to the total number of calculated bits and total energy consumption of the system, an objective function is established to optimize the energy efficiency of system, and a differential evolution based optimization method is proposed, with which the optimal energy efficiency of system calculation, offloading time, calculation time and frequency are obtained. Experimental results show that the proposed method can not only achieve better convergence effect, but also can effectively solve the energy shortage problem of the micro-equipment and extend the service life of the equipment.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research