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A Novel Positioning System Based on Coverage Area Pruning in Wireless Sensor Networks.

Shih-Chang Huang¹, Fu-Gong Li²

¹Department of Computer Science and Information Engineering, National Formosa University, Yunlin 63201, Taiwan. schuang@nfu.edu.tw.

Sensors (Basel, Switzerland)

|December 20, 2018

Summary

This summary is machine-generated.

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This study introduces the Coverage Area Pruning Positioning System (CAPPS), a novel range-free algorithm for wireless sensor networks. CAPPS significantly enhances positioning accuracy in environmental monitoring by effectively pruning potential target areas.

Area of Science:

Wireless Sensor Networks
Environmental Monitoring
Localization Algorithms

Background:

Wireless sensor networks (WSNs) are vital for environmental monitoring, but accurate event localization remains challenging.
Existing positioning technologies often demand high computational power or specialized hardware, unsuitable for resource-constrained WSNs.
The need for efficient and accurate localization in WSNs drives the development of new algorithms.

Purpose of the Study:

To propose a novel range-free positioning algorithm, the Coverage Area Pruning Positioning System (CAPPS), for WSNs.
To enhance the accuracy of target localization in WSNs without requiring specialized hardware or high computational capabilities.
To evaluate the performance of CAPPS under practical scenarios, including radio coverage variations.

Keywords:

centroid point coverage area pruning degree of irregularity range-free positioning wireless sensor networks

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Main Methods:

CAPPS determines an approximate target area using sensors that detect the event.
It then refines this area by utilizing sensors that do not detect the event, effectively pruning the search space.
A heuristic mechanism and centroid point approach are employed to mitigate positioning errors in dynamic radio environments.

Main Results:

CAPPS achieved significantly smaller positioning areas compared to Distance Vector Hop (98% smaller), Angle of Arrival (97% smaller), and Received Signal Strength Indicator (93% smaller).
The proposed centroid point mechanism reduced the probability of excluding the target from 50%–95% to 10%–30% in radio variation scenarios.
Simulations demonstrated CAPPS's effectiveness in improving localization accuracy and reducing false positioning probabilities.

Conclusions:

CAPPS offers a highly accurate and efficient range-free localization solution for wireless sensor networks.
The algorithm is well-suited for resource-constrained WSNs commonly used in environmental monitoring.
CAPPS demonstrates superior performance over existing methods, particularly in challenging radio environments.