Dynamic pricing and scheduling in LEO satellite networks

Abstract

The dynamic nature of Low Earth Orbit (LEO) satellite networks, characterized by high-speed movement, narrow coverage, uneven spatial distribution and multi-satellite coordination, presents unique challenges and opportunities for network resource allocation. Existing literature has not fully addressed all the practical implementation challenges in LEO satellite networks; the predefined LEO pricing system lacks flexibility and does not consider user utility. This work introduces an auction-based framework to dynamically price and schedule Internet services in LEO satellite networks, optimizing resource allocation among users. We model the NP-Hard LEO Internet service scheduling problem into an Integer Linear Programming (ILP), providing both primal and dual forms. Leveraging an auction mechanism design, our online algorithm OSAL efficiently distributes satellite network resources while maximizing social welfare by ensuring resources are allocated to users who value them most. We demonstrate that OSAL effectively addresses the complexities of node mobility and spatial coverage in LEO satellites, improving the availability and efficiency of Internet services in this rapidly evolving field.