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An Opposition-Based Learning Black Hole Algorithm for Localization of Mobile Sensor Network.

Wei-Min Zheng¹, Shi-Lei Xu¹, Jeng-Shyang Pan¹

¹College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao 266590, China.

Sensors (Basel, Switzerland)

|May 13, 2023

Summary

This summary is machine-generated.

This study introduces an Opposition-Based Learning Black Hole (OBH) algorithm to enhance mobile wireless sensor network (MWSN) localization accuracy. The OBH algorithm demonstrates superior performance in real-time node tracking and trajectory capture.

Keywords:

black hole algorithm mobile node localization opposition-based learning wireless sensor network

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Area of Science:

Computer Science
Wireless Sensor Networks
Optimization Algorithms

Background:

Mobile node localization is crucial for real-time tracking and trajectory analysis in wireless networks.
Intelligent optimization algorithms offer simplicity and efficiency for these localization tasks.
The standard Black Hole algorithm faces challenges with weak exploration and slow convergence.

Purpose of the Study:

To propose an enhanced Black Hole algorithm, termed Opposition-Based Learning Black Hole (OBH), for improved mobile wireless sensor network (MWSN) localization.
To address the limitations of the traditional Black Hole algorithm, specifically its exploration capability and convergence speed.
To enhance the accuracy of MWSN localization using the novel OBH algorithm.

Main Methods:

Development of the Opposition-Based Learning Black Hole (OBH) algorithm.
Integration of the OBH algorithm with the Monte Carlo localization method.
Performance evaluation using the CEC2013 test function set and comparative analysis against other algorithms.

Main Results:

The OBH algorithm demonstrated superior performance compared to other tested algorithms on the CEC2013 benchmark.
Experimental results confirmed that the OBH algorithm achieves the best optimization effect when applied to Monte Carlo localization.
The proposed OBH algorithm significantly improves the accuracy of mobile wireless sensor network localization.

Conclusions:

The Opposition-Based Learning Black Hole (OBH) algorithm effectively overcomes the limitations of the standard Black Hole algorithm.
OBH offers a more robust and efficient solution for real-time mobile node localization in wireless sensor networks.
The OBH algorithm represents a significant advancement in improving the accuracy and convergence of MWSN localization techniques.