Edge cloud cooperation environment driven multi-level edge computing method for delay optimization

With the continuous and rapid development of the technology of the empowered Internet of Things (IoT), multi-service scenarios continue to appear, which poses a new challenge to the delay of large data services in IoT. Aiming at the cloud and edge cooperation for the IoT architecture, this work proposes a cloud and edge collaboration mechanism for the network delay optimization based on software-defined network, which tries to minimize the average delay by introducing a continuously variable cloud and edge task segmentation coefficient. Besides, we transform the delay optimization problem into a convex optimization one, based on which an optimized task segmentation strategy is obtained. The experimental results indicate that the service delay and network congestion can be reduced greatly by reasonable loading of edge node tasks to the cloud center.