# Topology Duration Optimization for UAV Swarm Network under the System Performance Constraint
## 4 The Proposed GTSC Method
### Topology Generation
Figure 9: Algorithm convergence speed. ## 6 Conclusions

In this paper, we proposed a novel Group Trend Similarity based double-head Clustering method(GTSC) for UAV swarm network based on the criterion of topology duration. We first formulated the swarm network topology construction as an optimization problem of maximizing the topology duration while satisfying the constraints of network throughput, end-to-end delay and nodes energy consumption. In the solution of optimization model, we employed a novel group trend similarity based double-head clustering method, in which key factors affecting network performance are considered comprehensively. The simulations results verified that our proposed method is effective and of practical significance when used to perform the topology construction for UAV swarm. The proposed GTSC method is more superior to the representative algorithms in the performance of topology duration, network throughput, end-to-end delay and energy consumption balance. The future work will focus on the distributed solution scheme for our proposed method which will be applicable to a real swarm scenarios. Conceptualization, R.Z., X.Z. and D.S. ; methodology, R.Z., X.Z. and K.Q. ; writing--original draft preparation, R.Z. and D.S. ; writing--review and editing, R.Z., X.Z., L.X. and K.Q. ; visualization, R.Z. and D.S. ; supervision, X.Z., L.X. and K.Q. ; funding acquisition, X.Z. and L.X. All authors have read and agreed to the published version of the manuscript. This research received no external funding. Not applicable. The authors declare no conflict of interest. ## References

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