# Online Network Slicing for Real Time Applications in Large-scale Satellite Networks

arXiv: https://arxiv.org/abs/2301.09372 · HTML: https://mlsanity.com/paper/2301.09372/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 23 Jan 2023.

## Built on by (most cited first, 1 of 1)

- [Accelerating Privacy-Preserving Federated Learning in Large-Scale LEO Satellite Systems](https://mlsanity.com/paper/2509.12222/) (2025)

## Abstract (arXiv)

In this work, we investigate resource allocation strategy for real time communication (RTC) over satellite networks with virtual network functions. Enhanced by inter-satellite links (ISLs), in-orbit computing and network virtualization technologies, large-scale satellite networks promise global coverage at low-latency and high-bandwidth for RTC applications with diversified functions. However, realizing RTC with specific function requirements using intermittent ISLs, requires efficient routing methods with fast response times. We identify that such a routing problem over time-varying graph can be formulated as an integer linear programming problem. The branch and bound method incurs O(|Lτ| · (3 |Vτ| + |Lτ|)^|Lτ|) time complexity, where |Vτ| is the number of nodes, and |Lτ| is the number of links during time interval τ. By adopting a k-shortest path-based algorithm, the theoretical worst case complexity becomes O(|Vτ|! · |Vτ|3). Although it runs fast in most cases, its solution can be sub-optimal and may not be found, resulting in compromised acceptance ratio in practice. To overcome this, we further design a graph-based algorithm by exploiting the special structure of the solution space, which can obtain the optimal solution in polynomial time with a computational complexity of O(3|Lτ| + (2log|Vτ|+1) |Vτ|). Simulations conducted on starlink constellation with thousands of satellites corroborate the effectiveness of the proposed algorithm.