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A dynamic resilience evaluation method for cross-domain swarms in confrontation

Author

Listed:
  • Zhang, Chi
  • Liu, Tao
  • Bai, Guanghan
  • Tao, Junyong
  • Zhu, Wenjin

Abstract

As a typical Internet of Things system, unmanned swarms can execute missions efficiently, while reduce risks and ensure personnel safety during operations. Because swarms in different physical domains have different advantages, the cross-domain swarms received lots of attentions recently. Since swarm has the ability to resist damage and recover from damage through self-organization and self-reconfiguration, resilience has become an important indicator for swarm design and mission planning in adversarial environments. Existing resilience evaluation methods require a complete degradation-recovery-stabilization process of system performance, which is not proper for the cross-domain swarm under dynamic and uncertain environment. This paper proposes a dynamic resilience evaluation method for cross-domain swarms in confrontation scenario. First, a cross-domain swarm confrontation model is developed and the swarm confrontation performance indicator is proposed. Second, a dynamic resilience evaluation method is proposed for cross-domain swarm. Then, a confrontation strategy selection model is given based on the resilience measurement. A case study of air-ground swarm in confrontations is provided for illustration and analysis. As can be seen from the simulation results, the proposed dynamic resilience method can better capture the dynamic and uncertain nature of cross-domain swarms in confrontation. The proposed strategy selection model can improve the overall resilience of the swarm, and ultimately improve the winning percentage of the cross-domain swarm in confrontation.

Suggested Citation

  • Zhang, Chi & Liu, Tao & Bai, Guanghan & Tao, Junyong & Zhu, Wenjin, 2024. "A dynamic resilience evaluation method for cross-domain swarms in confrontation," Reliability Engineering and System Safety, Elsevier, vol. 244(C).
    • Handle: RePEc:eee:reensy:v:244:y:2024:i:c:s0951832023008189
    DOI: 10.1016/j.ress.2023.109904
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