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CS-FCDA: A Compressed Sensing-Based on Fault-Tolerant Data Aggregation in Sensor Networks
Zeyu Sun1,2, Huihui Wang3, Baoluo Liu4
1School of Computer Science and Engineering, Luoyang Institute of Science and Technology, Luoyang 471023, China. lylgszy@163.com.
Sensors (Basel, Switzerland)
|November 8, 2018
Summary
This study introduces a Compressed Sensing based Fault-tolerant Correcting Data Aggregation (CS-FCDA) scheme. It improves data reconstruction accuracy and network energy efficiency in wireless sensor networks.
Area of Science:
- Computer Science
- Network Engineering
- Data Science
Background:
- Effective data aggregation and transmission in dense sensor networks are challenging.
- Existing Compressed Sensing (CS) schemes face load imbalance and coverage voids.
- Centralized data aggregation by a Sink node can be inefficient.
Purpose of the Study:
- To propose a novel Compressed Sensing based Fault-tolerant Correcting Data Aggregation (CS-FCDA) scheme.
- To address load imbalance and coverage void issues in data aggregation.
- To enhance data reconstruction accuracy and network communication efficiency.
Main Methods:
- Developed a CS-FCDA scheme for accurate compressed data reconstruction.
- Implemented a node clustering mechanism for load balancing.
- Utilized simulation to compare CS-FCDA with existing schemes.
Main Results:
- CS-FCDA accurately reconstructs compressed data, reducing network overhead.
- Node clustering optimizes and balances network load.
- Simulations demonstrate improved fault-tolerant correcting capability and energy efficiency.
Conclusions:
- The proposed CS-FCDA scheme effectively balances network load and enhances data reconstruction.
- CS-FCDA offers significant improvements in fault tolerance and energy efficiency over existing methods.
- This scheme is suitable for dense sensor networks requiring reliable data aggregation.
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