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Enhancing semantic belief function to handle decision conflicts in SoS using k-means clustering.

Eman K Elsayed1,2, Ahmed Sharaf Eldin Ahmed3,4, Hebatullah Rashed Younes3

  • 1Mathematical and Computer Science Department, Faculty of Science, Al-Azhar University (Girls Branch), Cairo, Egypt.

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Summary

This study introduces a new method for detecting and solving conflicts in integrated systems, called the Smart Semantic Belief Function Clustered System of Systems (SSBFCSoS). The SSBFCSoS enhances conflict resolution efficiency and accommodates more systems, improving overall system performance.

Keywords:
ClusteringComponent Systems (CS)ConflictSystem of Systems (SoS)k-means

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Area of Science:

  • Computer Science
  • Systems Engineering

Background:

  • System of Systems (SoS) integrate individual systems for complex functions, aiming for simplified operations and cost reduction.
  • Co-integrating systems can lead to conflicts, undermining the core benefits of SoS.
  • Existing SoS approaches require enhancement in conflict detection and resolution times.

Purpose of the Study:

  • To improve the efficiency of detecting and resolving conflicts arising from co-integrating systems within a System of Systems (SoS).
  • To propose an enhanced SoS model that facilitates faster conflict management and accommodates future system additions.

Main Methods:

  • Utilized k-means clustering to partition the SoS into smaller, manageable clusters (Sub SoS or S-SoS).
  • Developed the Smart Semantic Belief Function Clustered System of Systems (SSBFCSoS), an advancement over the Ontology Belief Function System of Systems (OBFSoS).
  • Applied the SSBFCSoS to partition SoS entities, enabling localized conflict detection and resolution.

Main Results:

  • The SSBFCSoS demonstrated rapid conflict detection and resolution capabilities.
  • Achieved an average of 89% conflict resolution, outperforming other approaches (77%).
  • Showcased a 16% acceleration in conflict resolution and a 23% reduction in recurring conflicts compared to previous methods.

Conclusions:

  • The proposed SSBFCSoS effectively enhances conflict management in SoS environments.
  • The clustering approach improves scalability and maintains SoS objectives.
  • SSBFCSoS offers a significant improvement in conflict resolution rates and efficiency.