On-Demand Routing in LEO Mega-Constellations with Dynamic Laser Inter-Satellite Links

TL;DR

This paper introduces a nonlinear optimization model and heuristic algorithms for on-demand routing in LEO satellite mega-constellations, considering laser link setup delays to improve latency and energy efficiency.

Contribution

It presents a novel optimization framework and heuristics for dynamic LISL establishment, balancing latency and computational complexity in satellite networks.

Findings

Adaptive routing schemes reduce average latency.

More complex algorithms lower latency at higher computational cost.

Scalable schemes can be chosen based on latency tolerance.

Abstract

Low Earth orbit (LEO) satellite mega constellations are beginning to include laser inter-satellite links (LISLs) to extend the Internet to the most remote locations on Earth. Since the process of establishing these links incurs a setup delay on the order of seconds, a static network topology is generally established well in advance, which is then used for the routing calculations. However, this involves keeping links active even when they are not being used to forward traffic, leading to poor energy efficiency. Motivated by technological advances that are gradually decreasing the LISL setup delays, we foresee scenarios where it will be possible to compute routes and establish dynamic LISLs on demand. This will require considering setup delays as penalties that will affect the end-to-end latency. In this paper, we present a nonlinear optimization model that considers these penalties in the cost function and propose three heuristic algorithms that solve the problem in a tractable way. The algorithms establish different trade-offs in terms of performance and computational complexity. We extensively analyze metrics including average latency, route change rate, outage probability, and jitter in Starlink's Phase I version 2 constellation. The results show the benefit of adaptive routing schemes according to the link setup delay. In particular, more complex schemes can decrease the average end-to-end latency in exchange for an increase in execution time. On the other hand, depending on the maximum tolerated latency, it is possible to use less computationally complex schemes which will be more scalable for the satellite mega constellations of the future.