Joint Optimization of Controller Placement and Switch Assignment in SDN‐Based LEO Satellite Networks

ABSTRACT Software‐defined networking (SDN)–based low earth orbit (LEO) satellite networks utilize various characteristics of SDN to alleviate the problem of inefficient resource management under traditional network architectures. The most fundamental issue in SDN‐based LEO satellite networks is how to place controllers and assign switches. The strategies adopted directly affect the network performance. However, most existing strategies cannot sensibly and dynamically adjust the controller location and controller–switch mapping according to the topology variation and traffic fluctuation of the LEO satellite network. In this paper, based on the dynamic placement dynamic assignment scheme, we first formulate the controller placement and switch assignment (CPSA) problem in the LEO satellite networks, which is an integer nonlinear programming problem. Then, a prior population–based genetic algorithm (PPGA) is proposed. Some individuals of the final generation of the algorithm for the current time slot are used as the prior population of the next time slot, thus stringing together the algorithms of adjacent time slots for successive optimization. Finally, we obtain the near‐optimal solution for each time slot. Extensive experiments demonstrate that PPGA can adapt to the network topology changes and traffic surges and exhibits excellent robustness in the face of network failures, outperforming some existing CPSA strategies in the LEO satellite networks.