Designing Large-Scale Constellations for the Internet of Space Things With CubeSats
A.C. Kak, Ian F. Akyildiz
Abstract
The emergence of CubeSats as a viable means for realizing satellite networks at low costs has given rise to ubiquitous cyber–physical systems spanning air, ground, and space, in what is being recognized as the Internet of Space Things (IoST). IoST is expected to serve a wide variety of applications ranging from monitoring and reconnaissance to in-space backhauling. The pervasiveness of cyber–physical systems of this kind necessitates a robust constellation design, characterized by optimized coverage and consistent connectivity. Thus, optimal constellation design is of great importance to system architects. However, the constellation design frameworks prevalent today do not scale well beyond a few dozen satellites, adversely impacting the system’s operational abilities. To this end, the objective of this article is two fold. The primary objective is the development of a modular and highly customizable large-scale constellation design framework, with the secondary objective involving the use of the proposed framework for designing robust constellations for IoST, serving a wide variety of use cases ranging from global coverage to region-specific coverage scenarios. More specifically, the framework presented herein has been developed to optimize constellation design based on CubeSat density, as well as a rigorous mathematical characterization of coverage and connectivity parameters. Furthermore, an extensive set of performance comparisons with existing state-of-the-art constellations has been presented to validate the efficacy of the IoST constellations designed using the proposed framework. Finally, the impact of design parameter variations on the developed constellations has also been examined in great detail.