When one protocol fits none: Self-organized network routing through evolutionary game dynamics
Packet routing on scale-free networks faces a fundamental trade-off: shortest-path routing is efficient at low demand but funnels traffic through hubs and jams early, whereas congestion-aware routing postpones jamming at the price of a sharper collapse. Since neither paradigm dominates across the full range of traffic load, here we ask whether the appropriate balance can emerge endogenously rather than being imposed by design. To answer this, we recast adaptive packet routing on networks as an evolutionary game letting a heterogeneous population of strategies compete for prevalence under selection pressure generated by their own performance. We study this competition under two formalisms (strategy anchored to the packet or to the generating node), global and local update rules, and two payoff metrics. Across every implementation the evolutionary dynamics yield the same outcome: the jamming transition is delayed relative to shortest-path routing while the violent collapse of fixed congestion-aware routing is avoided. This improvement emerges spontaneously, without centralized coordination or global information. Crucially, under local update rules, the node-level volatility of strategy choices peaks sharply at the transition, furnishing a purely local early-warning signal of imminent jamming that requires no global monitoring.
Authors
- Luciano Stucchi (ORCID: https://orcid.org/0000-0002-2823-0778)
- Sandro Meloni (ORCID: https://orcid.org/0000-0001-6202-3302)
- Jesús Gómez‐Gardeñes (ORCID: https://orcid.org/0000-0001-5204-1937)
- Pablo Gallarta-Sáenz (ORCID: https://orcid.org/0009-0001-1681-9569)
- Francesca Dilisante
Institutions
- Universidad de Zaragoza (ES)
- Institute for Cross-Disciplinary Physics and Complex Systems (ES)
- Centro Ricerche Enrico Fermi (IT)
- University of the Pacific (PE)
Publication Details
- Journal
- Chaos Solitons & Fractals
- Published
- 2026-09-05
- DOI
- https://doi.org/10.1016/j.chaos.2026.119076
- Primary Topic
- Complex Network Analysis Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Ministerio de Ciencia, Innovación y Universidades
- Gobierno de Aragón
- Agencia Estatal de Investigación
- Departamento de Educación, Cultura y Deporte, Gobierno de Aragón
- European Social Fund