Abstract
Cascading failures pose a serious threat to the survivability of underwater unmanned swarm networks (UUSNs), significantly limiting their service ability in collaborative missions such as military reconnaissance and environmental monitoring. Existing failure models primarily focus on power grids and traffic systems, and don't address the unique challenges of weak-communication UUSNs. In UUSNs, cascading failure present a complex and dynamic process driven by the coupling of unstable acoustic channels, passive node drift, adversarial attacks, and network heterogeneity. To address these challenges, a directed weighted graph model of UUSNs is first developed, in which node positions are updated according to ocean-current–driven drift and link weights reflect the probability of successful acoustic transmission. Building on this UUSNs graph model, a cascading failure model is proposed that integrates a normal–failure–recovery state-cycle mechanism, multiple attack strategies, and routing-based load redistribution. Finally, under a five-level connectivity UUSNs scheme, simulations are conducted to analyze how dynamic topology, network load, node recovery delay, and attack modes jointly affect network survivability. The main findings are: (1) moderate node drift can improve survivability by activating weak links; (2) based-energy routing (BER) outperform based-depth routing (BDR) in harsh conditions; (3) node self-recovery time is critical to network survivability; (4) traditional degree-based critical node metrics are inadequate for weak-communication UUSNs. These results provide a theoretical foundation for designing robust survivability mechanisms in weak-communication UUSNs.
| Original language | English |
|---|---|
| Pages (from-to) | 66-82 |
| Number of pages | 17 |
| Journal | Defence Technology |
| Volume | 56 |
| DOIs | |
| State | Published - Feb 2026 |
Keywords
- Cascading failure
- Link success probability
- Node self-recovery
- Survivability analysis
- Underwater unmanned swarm networks (UUSNs)
- Weak communication
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