Multi-hop Differential Topology based Algorithms for Resilient Network of UAV Swarm

TL;DR

This paper introduces multi-hop differential topology algorithms to restore connectivity in UAV swarm networks damaged in hostile environments, using local damage information and innovative graph-based methods.

Contribution

It proposes a new damage-aware recovery paradigm with two algorithms: one for low-intelligence UAVs using artificial potential fields, and another for high-intelligence swarms employing graph convolution on MDSG.

Findings

Algorithms significantly speed up network recovery.

Improved spatial coverage and topology uniformity after recovery.

Effective in restoring connectivity in simulated hostile scenarios.

Abstract

Unmanned aerial vehicle (UAV) swarm networks face severe challenges of communication network split (CNS) issues caused by massive damage in hostile environments. In this paper, we propose a new paradigm to restore network connectivity by repositioning remaining UAVs based on damage information within local topologies. Particularly, the locations of destroyed UAVs distributed in gaps between disconnected sub-nets are considered for recovery trajectory planning. Specifically, we construct the multi-hop differential sub-graph (MDSG) to represent local damage-varying topologies. Based on this, we develop two distinct algorithms to address CNS issues. The first approach leverages an artificial potential field algorithm to calculate the recovery velocities via MDSG, enabling simple deployment on low-intelligence UAVs. In the second approach, we design an MDSG-based graph convolution framework to find the recovery topology for high-intelligence swarms. As per the unique topology of MDSG, we propose a novel bipartite graph convolution operation, enhanced with a batch-processing mechanism to improve graph convolution efficiency. Simulation results show that the proposed algorithms expedite the recovery with significant margin while improving the spatial coverage and topology degree uniformity after recovery.