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Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

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Wireless Sensor Network Coverage Optimization Using a Modified Marine Predator Algorithm.

Guohao Wang¹, Xun Li¹

¹School of Electronics and Information Engineering, Hebei University of Technology, Tianjin 300401, China.

Sensors (Basel, Switzerland)

|January 11, 2025

Summary

This summary is machine-generated.

A modified marine predator algorithm (MMPA) enhances wireless sensor network node deployment for forest fire monitoring. MMPA achieves superior coverage rates and node distribution uniformity compared to other algorithms.

Keywords:

coverage optimization marine predator algorithm wireless sensor network

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Area of Science:

Computer Science
Optimization Algorithms
Wireless Sensor Networks

Background:

Random deployment of wireless sensor network nodes in forest fire monitoring leads to coverage problems.
Existing metaheuristic algorithms may not provide optimal node distribution for effective monitoring.

Purpose of the Study:

To address the coverage problem in forest fire-monitoring wireless sensor networks.
To propose and evaluate a modified marine predator algorithm (MMPA) for improved node deployment and coverage.

Main Methods:

A modified marine predator algorithm (MMPA) incorporating tent mapping, hybrid search, golden sine mechanism, and stage-adjustment strategy.
Performance evaluation using CEC2017 and benchmark test functions.
Coverage tests in three scenarios comparing MMPA with other metaheuristic algorithms.

Main Results:

MMPA demonstrated superior optimization capability and stability compared to MPA, grey wolf optimizer, sine cosine algorithm, and sea horse optimizer.
MMPA achieved higher average coverage rates: 91.8% (scenario 1), 95.98% (scenario 2), and 93.88% (scenario 3).
MMPA resulted in a more uniform distribution of wireless sensor network nodes.

Conclusions:

The proposed MMPA effectively solves the coverage problem in wireless sensor networks for forest fire monitoring.
MMPA offers significant improvements in coverage rate and node distribution uniformity.
MMPA shows superiority over existing metaheuristic-based algorithms for this application.