Optimized Multi-Path Routing for IoT Connectivity in LEO Satellite Networks: A Load-Balanced Approach

The exponential growth of the global Internet of Things (IoT) network demands robust connectivity and enhanced Quality of Service (QoS) metrics such as reliability and low latency. With the increasing number of connected devices and network traffic, traditional terrestrial networks alone are insufficient to support real-time IoT applications, particularly in remote and underserved regions. Low Earth Orbit (LEO) multi-constellation satellite networks present a promising solution by offering low-latency connectivity. However, existing routing mechanisms, especially single-path routing, are inefficient due to congestion, link failures, and dynamic topology changes. To address these challenges, in this paper we propose a load-balanced multi-path routing protocol tailored for LEO satellite networks. Our approach constructs a real-time dynamic network topology using Two-Line Element (TLE) data and employs the Edmonds-Karp Algorithm to identify node-disjoint paths for data transmission. Furthermore, we use the Least Common Multiple-based Routing (LCMR) algorithm to distribute network traffic optimally across multiple paths, reducing transmission delay and enhancing network efficiency. The proposed framework is particularly suited for IoT applications requiring seamless, low-latency connectivity between distributed nodes. Simulation results demonstrate that our approach improves throughput, load balancing, and end-to-end delay, making it a viable solution for the evolving Internet of Space Things (IoST).