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Disjoint Spanning Tree Based Reliability Evaluation of Wireless Sensor Network
Sonam Lata1, Shabana Mehfuz1, Shabana Urooj2
1Department of Electrical Engineering, Jamia Millia Islamia, New Delhi, 110025, India.
Sensors (Basel, Switzerland)
|June 4, 2020
Summary
This study introduces an efficient algorithm for evaluating wireless sensor network (WSN) reliability. The method uses minimal spanning trees for faster, more accurate connectivity assessments in large-scale WSNs.
Area of Science:
- Computer Science
- Electrical Engineering
- Network Engineering
Background:
- Wireless sensor networks (WSNs) are crucial in manufacturing, but ensuring their stable operation requires robust reliability measures.
- Network connectivity is paramount for WSN efficacy, especially in large-scale, harsh environments.
- Existing methods for WSN reliability assessment can be computationally intensive.
Purpose of the Study:
- To propose a novel, efficient algorithm for evaluating the reliability of wireless sensor networks (WSNs).
- To address the challenge of computing minimal spanning trees for enhanced network reliability analysis.
- To develop a method for assessing flow-oriented reliability in WSNs.
Main Methods:
- A one-step algorithm utilizing specific spanning trees and generating disjoint spanning trees efficiently.
- Implementation of a binary decision illustration for enumerating K-coverage communication reliability.
- A modified sum-of-disjoint products approach applied to enumerated minimal spanning trees.
Main Results:
- The proposed algorithm demonstrates reduced computation time and memory usage.
- The methodology provides a less complex and more efficient way to determine WSN reliability.
- The algorithm is applicable to WSNs of various scales, proving its versatility.
Conclusions:
- The developed algorithm offers a significant improvement in evaluating WSN reliability.
- This approach enhances network performance for secure and successful communication.
- The method is suitable for large-scale WSN deployments in demanding environments.
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