Abstract
To promote the development of high-bandwidth IP networks of nongeostationary Earth orbit (NGEO) satellites, this article designs a new benefit measurement model. Moreover, we propose the class-A QoS benefit criterion (QABC), which is established based on a mathematical model involving the remaining queue length and QoS. The benefit model includes three maximum and minimum conflict subgoals and is designed to avoid the problem that the ant colony algorithm easily falls to local optima. This new model is solved with the wolf colony algorithm, which provides both next-hop selection and bottleneck bandwidth reservation mechanisms. Additionally, many burst flows can occur in satellite networks, and they lead to a slow convergence speed and unnecessary overhead. In this article, the Kalman filter algorithm is used to address these issues. Considering the long-term correlation of satellite traffic, it is feasible to smooth the queue length with a Kalman filter. Finally, the Kalman filter wolf colony algorithm (KFWCA) can solve the conflict problem in the new benefit measurement model. The algorithm is applied in the network simulator NS2.35, and the results verify the effectiveness of load balancing and QoS maximization in a satellite network. The results indicate that the KFWCA yields better performance than other algorithms based on traffic allocation, the average delay, the packet loss rate and other factors, especially under high-traffic conditions.
Highlights
With the increasing demand for satellite technology and communication requirements in near-Earth orbit [1], it is necessary to provide global Internet services
Reference [30] verified that the ant colony algorithm has some advantages in solving such functions, but the pheromone transfer and updating method has a slow convergence speed and falls to the local optimal path, making it unsuitable for the conflict benefit model proposed in this article
SATELLITE ROUTING STRATEGY BASED ON THE KALMAN FILTER WOLF COLONY ALGORITHM The algorithm designed in this article is innovative and achieves better routing results through global searching than do traditional methods
Summary
With the increasing demand for satellite technology and communication requirements in near-Earth orbit [1], it is necessary to provide global Internet services. In node-enabled routing, traffic allocation is only based on the instantaneous state of the node itself and the information in one hop, as noted in reference [70]; this approach guarantees that the strategy has a faster convergence speed and lower processing costs than other methods, but it will inevitably lead to the satellite network falling to the local optimal path. Some common solutions are the ant colony algorithm [9], particle swarm algorithm [10], etc These routing algorithms have some shortcomings related to the long calculation time, these issues can be avoided by establishing an ideal routing cost function or adopting a method for satellite queue length prediction.
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