Task Offloading Strategy in Cloud Collaborative Edge Computing

Wen-li Wang, Yanfeng Bai, Suzhen Wang

Abstract:

With the development of 5G and IOT technology, data processed by
intelligent mobile terminals grows explosively. Due to the limited computing
power of the intelligent terminal, which can not meet the requirements of low
task delay, an edge computing with cloud collaborative task offloading method
is proposed to solve the problem. This method applies to computing intensive
applications. In the cloud center, the resources are scheduled and terminal tasks
are offloaded to the edge nodes in using the method. At the same time, considering
the offloading needs of the terminal users and the load of the edge server,
the improved artificial bee colony algorithm is adopted to provide the offloading
scheme that meets the requirements of each task’s delay. The simulation results
show that the method can improve the load balance of the cluster, and reduce the
task processing delay compared with the random offloading method and the task
local processing method.