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Optimization-Based Approaches for Minimizing Deployment Costs for Wireless Sensor Networks with Bounded Estimation
Chiu-Han Hsiao1, Frank Yeong-Sung Lin2, Hao-Jyun Yang1
1Research Center for Information Technology Innovation, Academia Sinica, Taipei 115, Taiwan.
Sensors (Basel, Switzerland)
|November 13, 2021
Summary
This study optimizes wireless sensor networks (WSN) deployment by minimizing costs and maintaining accuracy. Correlation-aware methods reduce sensors while ensuring data integrity and extending network lifetime.
Area of Science:
- Computer Science
- Electrical Engineering
- Network Engineering
Background:
- Wireless sensor networks (WSN) are increasingly common, generating vast amounts of data.
- Cost and energy constraints necessitate sensor reduction strategies.
- Maintaining data accuracy within acceptable error tolerances is crucial.
Purpose of the Study:
- To develop an optimization-based approach for sensor deployment in WSN.
- To minimize deployment costs while adhering to error thresholds.
- To enhance the accuracy and longevity of WSN.
Main Methods:
- A correlation-aware mathematical model combining theoretical and practical aspects.
- Sensor deployment strategies utilizing XGBoost, Pearson correlation, and Lagrangian Relaxation (LR).
- Minimizing sensor count and deployment expenses.
Main Results:
- Achieved significant cost reduction in sensor deployment.
- Maintained estimation errors below a predefined threshold.
- Ensured high accuracy of gathered data and extended WSN operational lifetime.
Conclusions:
- The proposed correlation-aware method effectively balances cost, accuracy, and WSN lifetime.
- The approach is adaptable for sensor distribution challenges across diverse applications.
- Optimization strategies like LR are vital for efficient WSN management.
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