Volume 43 Issue 9
Sep.  2017
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PAN Xing, JIANG Zhuo, YANG Yanjinget al. Resilience-based component importance and recovery strategy for system-of-systems[J]. Journal of Beijing University of Aeronautics and Astronautics, 2017, 43(9): 1713-1720. doi: 10.13700/j.bh.1001-5965.2016.0727(in Chinese)
Citation: PAN Xing, JIANG Zhuo, YANG Yanjinget al. Resilience-based component importance and recovery strategy for system-of-systems[J]. Journal of Beijing University of Aeronautics and Astronautics, 2017, 43(9): 1713-1720. doi: 10.13700/j.bh.1001-5965.2016.0727(in Chinese)

Resilience-based component importance and recovery strategy for system-of-systems

doi: 10.13700/j.bh.1001-5965.2016.0727
Funds:

National Natural Science Foundation of China 71171008

National Natural Science Foundation of China 71571004

More Information
  • Corresponding author: PAN Xing, E-mail:panxing@buaa.edu.cn
  • Received Date: 08 Sep 2016
  • Accepted Date: 30 Dec 2016
  • Publish Date: 20 Sep 2017
  • System-of-systems (SoS) is always under the influence of both intra and extra disruptive events. SoS architecture is the foundation of SoS design and construction, whose resilience is not only an significant indicator to reflect the ability to recover from disruptions, but also an important embodiment of evolution of SoS. Based on resilience, an effective SoS architecture evaluation method was proposed to conduct component importance measures (CIMs). In the method, the resilience of SoS architecture was defined in detail, relevant mathematical models were built, and influence of performance loss and recovery time on component importance were comprehensively weighed. Then, according to analysis of various disruptive events and recovery strategy, an optimized model for SoS resilience based on CIMs was proposed, and the optimized result of the proposed model on recovery capability of SoS was mainly analyzed. Finally, an example of evaluating resilience of SoS was introduced to validate the availability of the proposed model and method, and the final result shows that the optimized recovery strategy contributes to improving the recovery efficiency of SoS greatly.

     

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