低轨卫星物联网场景下基于吸引子选择算法的多星负载均衡算法

低地球轨道(low earth orbit,LEO)卫星物联网系统中由于低轨卫星的高速运动,导致卫星波束覆盖范围内节点业务模型在空间和时间两个维度呈现不均匀性和时变性.针对这一特征,提出一种空时二维卫星物联网业务模型,在空间维度采用网格划分的方法确定不同地理环境下节点密度和坐标位置,在时间维度采用贝塔分布进行建模,从而...

Multi-satellite load balancing algorithm based on attractor selection algorithm in low earth orbit satellite internet of things scenario

In low earth orbit(LEO) satellite internet of things system, due to the high-speed movement of LEO satellite, the node business model within the coverage of satellite beam presents non-uniformity and time variability in space and time. In view of this feature, a space-time two-dimensional satellite internet of things business model is proposed. In the spatial dimension, the grid division method is used to determine the node density and coordinate position in different geographical environments, and the beta distribution is used for modeling in the time dimension, so as to realize the space-time two-dimensional modeling of LEO satellite internet of things business model. On this basis, aiming at the scenario of multi satellite coverage of LEO satellite constellation in the future, a multi satellite load balancing algorithm based on attractor model is proposed. The satellite side estimates the activity of each satellite through the load estimation algorithm, and the node side uses multi-attribute decision-making algorithm to estimate the equipment satisfaction of different satellites to the node in combination with the pitch angle and other parameters of different satellites, In the high dynamic environment of LEO satellites, the network activity of satellites is kept in a dynamic balance. Simulation results show that compared with the traditional access strategy based on the highest priority, the proposed algorithm has significantly improved the peak to average ratio of single satellite service, system resource utilization, random access performance and so on.