The combat domain of modern warfare is becoming increasingly multidimensional. It is important to evaluate the resilience of the air-ground cooperative network for defending against attack threats and recovery performance. First, a resilience analysis model was proposed to effectively analyze and evaluate the resilience of the air-ground cooperative network. Then, considering the available resources, three dynamic reconfiguration strategies were given from the global perspective to help the air-ground cooperative network quickly recover performance and enhance combat capabilities. Finally, a typical 50-node network was taken as an example to prove the effectiveness and feasibility of the proposed model. The proposed method can provide scientific guidance for improving the air-ground cooperative network combat capabilities.
Citation: Xiaoyang Xie, Shanghua Wen, Minglong Li, Yong Yang, Songru Zhang, Zhiwei Chen, Xiaoke Zhang, Hongyan Dui. Resilience evaluation and optimization for an air-ground cooperative network[J]. Electronic Research Archive, 2024, 32(5): 3316-3333. doi: 10.3934/era.2024153
The combat domain of modern warfare is becoming increasingly multidimensional. It is important to evaluate the resilience of the air-ground cooperative network for defending against attack threats and recovery performance. First, a resilience analysis model was proposed to effectively analyze and evaluate the resilience of the air-ground cooperative network. Then, considering the available resources, three dynamic reconfiguration strategies were given from the global perspective to help the air-ground cooperative network quickly recover performance and enhance combat capabilities. Finally, a typical 50-node network was taken as an example to prove the effectiveness and feasibility of the proposed model. The proposed method can provide scientific guidance for improving the air-ground cooperative network combat capabilities.
[1] |
Y. Sun, Z. Fang, Research on projection gray target model based on FANP-QFD for weapon system of systems capability evaluation, IEEE Syst. J., 15 (2020), 4126–4136. https://doi.org/10.1109/JSYST.2020.3027585 doi: 10.1109/JSYST.2020.3027585
![]() |
[2] |
X. Wang, Y. Zhang, L. Wang, D. Lu, G. Zeng, Robustness evaluation method for unmanned aerial vehicle swarms based on complex network theory, Chin. J. Aeronaut., 33 (2020), 352–364. https://doi.org/10.1016/j.cja.2019.04.025 doi: 10.1016/j.cja.2019.04.025
![]() |
[3] |
P. Uday, R. Chandrahasa, K. Marais, System importance measures: Definitions and application to system-of-systems analysis, Reliab. Eng. Syst. Saf., 191 (2019), 106582. https://doi.org/10.1016/j.ress.2019.106582 doi: 10.1016/j.ress.2019.106582
![]() |
[4] |
Z. Chen, Z. Zhou, L. Zhang, C. Cui, J. Zhong, Mission reliability modeling and evaluation for reconfigurable unmanned weapon system-of-systems based on effective operation loop, J. Syst. Eng. Electron., 34 (2023), 588–597. https://doi.org/10.23919/JSEE.2023.000082 doi: 10.23919/JSEE.2023.000082
![]() |
[5] |
K. Yang, J. Li, M. Liu, Complex systems and network science: a survey, J. Syst. Eng. Electron., 34 (2023), 543–573. https://doi.org/10.23919/JSEE.2023.000080 doi: 10.23919/JSEE.2023.000080
![]() |
[6] |
J. Sun, B. Ge, J. Li, K. Yang, Operation network modeling with degenerate causal strengths for missile defense systems, IEEE Syst. J., 12 (2016), 274–284. https://doi.org/10.1109/JSYST.2016.2570519 doi: 10.1109/JSYST.2016.2570519
![]() |
[7] | J. R. Cares, R. J. Christian, R. C. Manke, Fundamentals of distributed, networked military forces and the engineering of distributed systems, NUWC-NPT Tech. Rep., 11 (2002), 200–209. https://www.researchgate.net/profile/Jeff-Cares/publication/235107120 |
[8] |
J. Li, B. Ge, K. Yang, Y. Chen, Y. Tan, Meta-path based heterogeneous combat network link prediction, Phys. A: Stat. Mech. Appl., 482 (2017), 507–523. https://doi.org/10.1016/j.physa.2017.04.126 doi: 10.1016/j.physa.2017.04.126
![]() |
[9] | J. Li, D. Zhao, J. Jiang, K. Yang, Y. Chen, Capability oriented equipment contribution analysis in temporal combat networks, IEEE Trans. Syst. Man Cybern.: Syst., 51 (2018), 696–704. https://doi.org/0.1109/TSMC.2018.2882782 |
[10] |
J. Li, J. Jiang, K. Yang, Y. Chen, Research on functional robustness of heterogeneous combat networks, IEEE Syst. J., 13 (2018), 1487–1495. https://doi.org/10.1109/JSYST.2018.2828779 doi: 10.1109/JSYST.2018.2828779
![]() |
[11] |
J. Sun, J. Li, Y. You, J. Jiang, B. Ge, Combat network link prediction based on embedding learning, J. Syst. Eng. Electron., 33 (2022), 345–353. https://doi.org/10.23919/JSEE.2022.000036 doi: 10.23919/JSEE.2022.000036
![]() |
[12] | L. Chen, C. Wang, C. Zeng, L. Wang, H. Liu, J. Chen, A novel method of heterogeneous combat network disintegration based on deep reinforcement learning, Front. Phys., 10 (2022), https://doi.org/1021245.10.3389/fphy.2022.1021245 |
[13] |
C. Cheng, G. Bai, Y. Zhang, J. Tao, Resilience evaluation for UAV swarm performing joint reconnaissance mission, Chaos, 29 (2019), 190–200. https://doi.org/10.1063/1.5086222 doi: 10.1063/1.5086222
![]() |
[14] |
B. A. Alkhaleel, H. Liao, K. M. Sullivan, Risk and resilience-based optimal post-disruption restoration for critical infrastructures under uncertainty, Eur. J. Oper. Res., 296 (2022), 174–202. https://doi.org/10.1016/j.ejor.2021.04.025 doi: 10.1016/j.ejor.2021.04.025
![]() |
[15] |
B. Cai, Y. Zhang, H. Wang, Y. Liu, R. Ji, C. Gao, et al., Resilience evaluation methodology of engineering systems with dynamic-Bayesian-network-based degradation and maintenance, Reliab. Eng. Syst. Saf., 209 (2021), 107464. https://doi.org/10.1016/j.ress.2021.107464 doi: 10.1016/j.ress.2021.107464
![]() |
[16] |
A. J. Kerkhoff, B. J. Enquist, The implications of scaling approaches for understanding resilience and reorganization in ecosystems, Bioscience, 57 (2007), 489–499. https://doi.org/10.1641/B570606 doi: 10.1641/B570606
![]() |
[17] |
Z. Chen, D. Hong, W. Cui, et al., Resilience evaluation and optimal design for weapon system of systems with dynamic reconfiguration, Reliab. Eng. Syst. Saf., 237 (2023), 109409. https://doi.org/10.1016/j.ress.2023.109409 doi: 10.1016/j.ress.2023.109409
![]() |
[18] |
Z. Chen, T. Zhao, J. Jiao, J. Chu, Performance-threshold-based resilience analysis of system of systems by considering dynamic reconfiguration, Proc. Inst. Mech. Eng., 236 (2022), 1828–1838. https://doi.org/10.1177/0954405420937528 doi: 10.1177/0954405420937528
![]() |
[19] |
S. Hosseini, D. Ivanov, A. Dolgui, Review of quantitative methods for supply chain resilience analysis, Transp. Res. Part E: Logist. Transp. Rev., 125 (2019), 285–307. https://doi.org/10.1016/j.tre.2019.03.001 doi: 10.1016/j.tre.2019.03.001
![]() |
[20] |
M. Liu, Q. Feng, D. Fan, H. Dui, B. Sun, Y. Ren, et al., Resilience importance measure and optimization considering the stepwise recovery of system performance, IEEE Trans. Reliab., 178 (2022), 178–185. https://doi.org/10.1109/TR.2022.3196058 doi: 10.1109/TR.2022.3196058
![]() |
[21] |
H. Dui, M. Liu, J. Song, S. Wu, Importance measure-based resilience management: Review, methodology and perspectives on maintenance, Reliab. Eng. Syst. Saf., 235 (2023), 109383. https://doi.org/10.1016/j.ress.2023.109383 doi: 10.1016/j.ress.2023.109383
![]() |
[22] |
S. Geng, S. Liu, Z. Fang, A demand-based framework for resilience assessment of multistate networks under disruptions, Reliab. Eng. Syst. Saf., 222 (2022) 108423. https://doi.org/10.1016/j.ress.2022.108423 doi: 10.1016/j.ress.2022.108423
![]() |
[23] |
H. Tran, M. Balchanos, J. Domerçant, D. N. Mavris, A framework for the quantitative assessment of performance-based system resilience, Reliab. Eng. Syst. Saf., 158 (2017), 73–84. https://doi.org/10.1016/j.ress.2016.10.014 doi: 10.1016/j.ress.2016.10.014
![]() |
[24] |
G. Bai, Y. Li, Y. Fang, Y. A. Zhang, J. Tao, Network approach for resilience evaluation of a UAV swarm by considering communication limits, Reliab. Eng. Syst. Saf., 193 (2020), 106602. https://doi.org/10.1016/j.ress.2019.106602 doi: 10.1016/j.ress.2019.106602
![]() |
[25] |
C. Cheng, G. Bai, Y. Zhang, J. Tao, Improved integrated metric for quantitative assessment of resilience, Adv. Mech. Eng., 12 (2020), 168–180. https://doi.org/10.1177/1687814020906065 doi: 10.1177/1687814020906065
![]() |
[26] | Q. Sun, H. Li, Y. Wang, Y. Zhang, Multi-swarm-based cooperative reconfiguration model for resilient unmanned weapon system-of-systems, Reliab. Eng. Syst. Saf., 222 (2022), 108426. https://doi.org/108426.10.1016/j.ress.2022.108426 |
[27] |
Q. Feng, M. Liu, B. Sun, H. Dui, X. Hai, Y. Ren, et al., Resilience measure and fformation reconfiguration optimization for multi-UAV systems, IEEE Internet Things J., 11 (2024), 10616–10626. https://doi.org/10.1109/JIOT.2023.3326552 doi: 10.1109/JIOT.2023.3326552
![]() |
[28] |
H. T. Tran, J. C. Domerçant, D. N. Mavris, A network-based cost comparison of resilient and robust system-of-systems, Procedia Comput. Sci., 95 (2016), 126–133. https://doi.org/10.1016/j.procs.2016.09.302 doi: 10.1016/j.procs.2016.09.302
![]() |
[29] |
X. Pan, H. Wang, Y. Yang, G. Zhang, Resilience based importance measure analysis for SoS, J. Syst. Eng. Electron., 30 (2019), 920–930. https://doi.org/10.21629/JSEE.2019.05.10 doi: 10.21629/JSEE.2019.05.10
![]() |
[30] |
Y. Cheng, E. A. Elsayed, Z. Huang, Systems resilience assessments: a review, framework and metrics, Int. J. Prod. Res., 60 (2022), 595–622. https://doi.org/10.1080/00207543.2021.1971789 doi: 10.1080/00207543.2021.1971789
![]() |
[31] |
M. Versaci, G. Angiulli, P. Crucitti, D. D. Carlo, F. Laganà, D. Pellicanò, et al., A fuzzy similarity-based approach to classify numerically simulated and experimentally detected carbon fiber-reinforced polymer plate defects, Sensors, 22 (2022), 4232. https://doi.org/10.3390/s22114232 doi: 10.3390/s22114232
![]() |