Optimal Controller Placement in MEC-aided Software-defined UAV Networks Against Jamming Attack

In this paper, we solve the problem of optimal placement of controllers in a software-defined UAV network assisted by mobile edge computing (MEC) under jamming attack. In order to solve the problem of the dynamic change of the quality of the wireless link caused by the maneuver of the jammer, we designed a bargaining game-based dynamic controller deployment algorithm. Specifically, we simplified the controller placement problem to a sequential decision-making problem. The controller can be deployed on the UAV or on a fixed base station on the ground. In our work, we first predict the position of the jammer at the next moment based on the current position and speed of the jammer. After that, we calculate the communication cost between nodes in the network accordingly. We first predict the position of the jammer at the next moment based on the current position and speed of the jammer. After that, we calculate the Signal to Interference plus Noise Ratio (SINR) between nodes in the network accordingly. Finally, we comprehensively consider time delay, communication cost and load balance, and use game theory to determine the number and location of controllers. The simulation results prove the effectiveness of the proposed method.