Multiuser computation offloading for edge-cloud collaboration using submodular optimization

Abstract

A computation offloading scheme based on edge-cloud computing was proposed to improve the system utility of multiuser computation offloading. This scheme improved the system utility while considering the optimization of edge-cloud resources. In order to tackle the problems of computation offloading mode selection and edge-cloud resource allocation, a greedy algorithm based on submodular theory was developed by fully exploiting the computing and commu- nication resources of cloud and edge. The simulation results demonstrate that the proposed scheme effectively reduces the delay and energy consumption of computing tasks. Additionally, when computing tasks are offloaded to edge and cloud from devices, the proposed scheme still maintains stable system utilities under ultra-limited resources.

Bing Liang

Researcher

My research interests include multimedia communication and networking, video transmission, edge computing, optimization theory and machine learning.