Offloading strategy with edge optimization of time delay and energy consumption in integrated satellite-terrestrial relay network

Abstract

The integrated satellite-terrestrial relay network (ISTRN) is a necessary part of the next-generation wireless communication system, and has important practical significance for accelerating the construction of my country's air-space-terrestrial integrated network system.In the traditional ISTRN architecture, a large amount of signaling needs to be forwarded to the ground control center for processing, which increases the delay of network control and management.A new cloud fog computing architecture was proposed, which constructs a sub-regional edge fog computing layer between the ground access and the central cloud to improve the flexibility of business flow management and control.Under the cloud network framework, a Q-learning based edge computing offloading strategy was designed, and the offloading performance was evaluated by time delay and energy consumption.Simulation results show that, compared with Min-min algorithm and backtracking algorithm, Q-learning based computational offload algorithm has better performance in terms of time delay and energy consumption, and can achieve a balance between the joint optimization of time delay and energy consumption.

Keywords

• integrated satellite-terrestrial relay network;multi-access edge computing;cloud fog network;offloading strategy;Q-learning