DLECP: A Dynamic Learning-based Edge Cloud Placement Framework for Mobile Cloud Computing
Xiaoqun Yuan, Mengting Sun, Qing Fang, Changlai Du · 2019
In our poster, we deal with the edge cloud placement of Mobile Cloud Computing(MCC) by proposing a dynamic edge cloud placement framework, which integrates Machine Learning methods and Spot Instance pricing model of cloud computing. The former is implemented to predict the information of mobile users' requests and resource price, and the latter is used to reduce the edge cloud placement cost. Simulation results demonstrate that our proposed framework achieves higher performance with lower time complexity.