Three-Dimensional Localization Algorithm Based on Improved A and DV-Hop Algorithms in Wireless Sensor Network

Area of Science:

• Computer Science
• Electrical Engineering
• Network Engineering

Background:

• Traditional wireless sensor network (WSN) localization algorithms, like DV-Hop, suffer from significant deviation and low accuracy in 3D environments.
• The Internet of Things (IoT) relies on accurate WSN localization for effective data collection and network management.

Purpose of the Study:

• To propose an improved wireless sensor network node location algorithm, MA*-3DDV-Hop, enhancing 3D localization accuracy.
• To address the limitations of existing 3D localization algorithms, specifically large deviations and low precision.

Main Methods:

• Integration of the A* algorithm with the 3DDV-Hop algorithm to create the MA*-3DDV-Hop algorithm.
• Optimization of hop-count values and correction of average distance per hop errors.
• Application of the NSGA-II algorithm for local coordinate optimization, utilizing selection, crossover, and mutation to achieve Pareto optimal solutions.

Main Results:

• The MA*-3DDV-Hop algorithm demonstrates superior robustness and higher localization accuracy in diverse 3D random scenarios.
• Achieved Pareto optimal solutions overcome premature convergence and poor convergence issues common in genetic algorithms.
• Reduced coordinate calculation errors, leading to enhanced localization precision for WSN nodes.

Conclusions:

• The MA*-3DDV-Hop algorithm significantly improves localization accuracy and robustness in 3D wireless sensor networks.
• The integration of improved A* and NSGA-II offers a more effective solution compared to standard 3DDV-Hop and other variants (PSO-3DDV-Hop, GA-3DDV-Hop, N2-3DDV-Hop).
• This enhanced algorithm is crucial for advancing IoT applications reliant on precise WSN localization.