Service migration algorithms in distributed edge computing systems
In future networks, to enable massive number of devices and to handle the dramatic increase in traffic new technologies such as MEC, D2D, NFV, SDN and AI should be deployed. An efficient way to reduce, manage and control the network traffic dynamically is to employs means of AI over MEC servers and SDN controllers. Deep learning algorithms will be implemented at the MEC servers to manage and control the network traffic within the RAN. In this talk we will discuss an architecture to provide services migration between FoG and edge computing structures and elements based on information about computational and network capabilities taking into account user query statistics in each of FoG structures. This solution can be used for IoT-based application development and deployment which provides new time constraint services like a Tactile internet, Autonomous Vehicles, etc, then we have to talk about platform and service placement using the Genetic Algorithm to analyze and predict services.