Connectivity Recovery Based on Boundary Nodes and Spatial Triangle Fermat Points for Three-Dimensional Wireless...

Area of Science:

• Computer Science
• Network Engineering
• Graph Theory

Background:

• Wireless sensor networks (WSNs) are crucial in 3D environments like underwater and mountainous regions.
• Harsh conditions can cause WSNs to fragment into isolated 'islands', hindering data transmission.
• Restoring network connectivity is vital for effective data delivery.

Purpose of the Study:

• To propose a novel connectivity recovery strategy for fragmented 3D wireless sensor networks.
• To address the NP-hard problem of minimizing relay nodes for network restoration.
• To enhance data transmission efficiency in damaged WSNs.

Main Methods:

• Modeling the connectivity recovery problem as a graph problem using boundary nodes of isolated islands.
• Developing three heuristic algorithms: variant Kruskal, variant Prim, and spatial triangle Fermat point algorithms.
• Utilizing minimum spanning trees and Steiner trees for placing relay nodes.

Main Results:

• The variant Kruskal and Prim algorithms construct minimum spanning trees to link boundary nodes.
• The spatial triangle Fermat point algorithm constructs a Steiner tree using derived formulas for Fermat points.
• Simulation experiments show superior performance compared to existing methods.

Conclusions:

• The proposed boundary node and spatial triangle Fermat point strategy effectively restores connectivity in 3D WSNs.
• Heuristic algorithms offer efficient solutions for the NP-hard relay node placement problem.
• The novel approach improves network resilience and data transmission capabilities in challenging environments.