A Hybrid Localization Algorithm for an Adaptive Strategy-Based Distance Vector-Hop and Improved Sparrow Search for...

Area of Science:

• Computer Science
• Electrical Engineering

Background:

• Node localization is crucial in wireless sensor networks (WSNs).
• The prevalent Distance Vector-Hop (DV-Hop) algorithm offers range-free localization but lacks sufficient accuracy.

Purpose of the Study:

• To enhance the localization accuracy of WSNs.
• To address the limitations of the standard DV-Hop algorithm.

Main Methods:

• Proposed a hybrid localization algorithm: adaptive strategy-based Distance Vector-Hop and improved Sparrow Search (HADSS).
• Implemented an adaptive hop count strategy with a correction factor for refined hop counts.
• Calculated average hop distance using mean square error and corrected it using anchor node trust degree and weighting methods.

Main Results:

• The adaptive hop count strategy reduces errors and communication overhead compared to traditional methods.
• The combined weighting and trust degree approach minimizes average hop distance errors by utilizing both global and local network information.
• Simulation experiments demonstrate significantly higher accuracy for HADSS compared to five existing localization algorithms.

Conclusions:

• The HADSS algorithm offers a substantial improvement in WSN localization accuracy.
• The proposed adaptive strategies effectively enhance the performance of DV-Hop based localization.