GANSlicing: A GAN-Based Software Defined Mobile Network Slicing Scheme for IoT Applications
Ruichun Gu, Junxing Zhang · 2019
With the rapid development of the mobile network and growing complexity of new networking applications, it is challenging to meet the diverse resource demands under the current mobile network architecture, especially for IoT applications. In this paper, we propose GANSlicing, a dynamic service-oriented software-defined mobile network slicing scheme that leverages Generative Adversarial Networks (GANs) based prediction to timely and flexibly allocate resources for IoT applications and to improve Quality of Experience (QoE) of users. Compared with the current tenant-oriented mobile network slicing scheme, GANSlicing is able to accept 16% more requests with 12% fewer resources for the same service request batch according to our evaluation. The result demonstrates that the proposed scheme not only improves the utilization of resources but also enhances the QoE of IoT applications.