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3D Deployment Optimization of Wireless Sensor Networks for Heterogeneous Functional Nodes.

Zean Lu^1,2, Chengqun Wang², Peng Wang²

¹School of Information Science and Engineering, Zhejiang Sci-Tech University, Hangzhou 310018, China.

Sensors (Basel, Switzerland)

|March 17, 2025

Summary

This study introduces an improved optimization algorithm for heterogeneous wireless sensor networks (WSNs), balancing coverage, connectivity, and cost. The new algorithm demonstrates superior performance in complex deployment scenarios.

Keywords:

C-connectivity K-coverage deployment optimization of heterogeneous wireless sensor networks improved bird optimization algorithm minimum spanning tree algorithm

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Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

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Published on: September 8, 2023

Area of Science:

Computer Science
Electrical Engineering
Network Optimization

Background:

Wireless Sensor Network (WSN) deployment optimization is crucial for industrial applications.
Existing WSN optimization methods are often too idealized for practical, multifunctional sensor needs.
Integrating sensors enhances monitoring capabilities and reduces deployment costs in diverse areas.

Purpose of the Study:

To design a novel multi-objective optimization problem for heterogeneous-function WSNs.
To balance network coverage, connectivity, and cost, considering diverse sensor functionalities.
To address the NP-hard nature of optimizing complex WSN deployments.

Main Methods:

A new multi-objective optimization problem for heterogeneous WSNs was formulated.
An Improved Secretary Bird Optimization Algorithm (ISBOA) was developed, featuring Gaussian Cuckoo Mutation and smooth exploitation.
ISBOA was benchmarked against original SBOA, PSO, WOA, and NGO on 23 functions and the new WSN problem.
A minimum spanning tree domain reduction strategy was proposed for large-scale problems.

Main Results:

ISBOA demonstrated faster convergence and higher accuracy compared to existing algorithms.
The proposed algorithm effectively balances coverage, connectivity, and cost in heterogeneous WSNs.
The domain reduction strategy significantly improved efficiency for large-scale WSN optimization with minimal accuracy loss.

Conclusions:

The ISBOA offers a robust solution for optimizing heterogeneous WSN deployments.
The study addresses practical challenges in WSN design, moving beyond idealized models.
The findings provide a more efficient and accurate approach to WSN deployment optimization for industrial applications.