Gateway Placement Optimization in LEO Satellite Networks Based on Traffic Estimation

Abstract

Using satellite constellations to provide global Internet access services has recently drawn increasing attention. A low-Earth orbit (LEO) satellite network with multiple satellites provides global coverage, low latency, and operates independently, by which it effectively complements terrestrial IP networks. Satellite gateways are located on the ground and can serve as data exchange points between satellite networks and the Internet. As the placement scheme can affect network performance, finding appropriate sites for gateways constitutes a fundamental problem. This paper proposes a gateway placement optimization (GPO) method for LEO satellite networks in order to solve this problem by modeling it as a combination optimization problem. We aim to identify the best gateway locations that can balance traffic loads while using as few gateways as possible. The constraints to be satisfied concern the physical links between gateways and satellites: specifically, link interference, satellite bandwidth, and number of satellite antennas. We use a gravity model to estimate the traffic matrix from/to gateways and satellites, then we adopt and modify the discrete particle swarm optimization (PSO) algorithm to solve this problem. Finally, we apply the GPO method to numerical tests on real satellite constellations. The results indicate that our method performs well and effectively.

Optimal Gateway Placement for Minimizing Intersatellite Link Usage in LEO Megaconstellation Networks

“…Therefore, with 4.42% less time consuming, the IBD-PSO algorithm can still achieve a better result than GA. Compared to the MD-PSO algorithm [21], the two algorithms have very close performance on objective value, but the IBD-PSO consumes 1.96% less time than MD-PSO. The reason may be that the population initialization scheme speeds up the optimization.…”

“…With the growing concerns on MCNs, some researchers have started to study the gateway placement in LEO constellation networks in recent years. Guo et al [21] formulate a combination optimization model to optimize the GSO problem in a traditional Iridium-like constellation scenario and propose a heuristic algorithm to solve it. The gravity model is adopted to estimate the traffic aggregated at the gateways, which avoids the traffic routing calculation.…”

“…The parameters for the IBD-PSO algorithm refer to [21] and are set as N pop = 50, c 1 = c 2 = 2, β = 0.5. ω ranges from 0.9 to 0.4 and varies linearly with the iteration. The maximum iteration number N iter is 100.…”

“…Note that the iteration stop before N iter if the best-obtained solution maintains unchanged for 30 iterations. To evaluate the optimization performance, we also adopt three approaches for comparison: i) Greedy Strategy (GS) that successively traverses and finds the local optimal sites in each cluster without recursion [16]; ii) Modified Discrete PSO (MD-PSO) as in [21]; iii) Genetic Algorithm (GA) as in [10]. We adopt the same population size and stop criterion as the IBD-PSO algorithm.…”

Static Placement and Dynamic Assignment of SDN Controllers in LEO Satellite Networks

“…It is reasonable to use the world population distribution to represent the arrival traffic of users [36]. The world population density data with resolution of 1 • are generated from [37], which is the first version in 2020.…”