一种基于收敛松鼠搜索算法的资源受限网络节点部署方法
The CSSA algorithm solves the convergence and parameter blindness problems in the deployment of nodes in resource-constrained networks, achieves the global optimal solution under a limited budget, improves the solution accuracy and stability, and is suitable for resource-constrained network planning and scheduling.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- NANJING UNIV OF SCI & TECH
- Filing Date
- 2026-04-08
- Publication Date
- 2026-07-17
AI Technical Summary
Existing methods for deploying nodes in resource-constrained networks lack theoretical convergence guarantees, are prone to search traps, and involve blind parameter selection, making it difficult to achieve the global optimal solution under limited budgets.
We employ a convergent squirrel search algorithm (CSSA), specifying the value range of key parameters through rigorous theoretical analysis, introducing the concept of search traps, designing seasonal monitoring and Lévy flight reset mechanisms, and combining Sigmoid mapping and nested local search strategies to ensure that the algorithm converges to the global optimum in the BMCP problem.
It achieves strict convergence in network node deployment under resource-constrained conditions, improves solution accuracy and stability, significantly reduces computational costs, avoids local optima traps, and provides a coverage scheme with high engineering practicality.
Smart Images
Figure CN122001776B_ABST