Fault-Tolerant Data Aggregation for Reliable Wireless Sensor Networks

Abstract—precise data & information is the lifeblood for the operation of Wireless Sensor Networks (WSNs). Incorrect (faulty data) information may lead to the wrong decision; it decreases the reliability in communication and overall operation of WSN. Fault tolerance is one of the issues in WSNs. Proposed fault-tolerant data aggregation scheme for identifying the faulty data sent by the sensors to the cluster head, where the aggregation is performed. Faulty information or data is discarded before aggregation. It would help to improve the accuracy of data aggregation. Consequently, the transmission overhead reduces, since erroneous data is eliminated. The proposed solution gives better performance by detecting and eliminating faulty data providing nodes

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-03-08
DOI
https://doi.org/10.5281/zenodo.14992246
Primary Topic
Subterranean biodiversity and taxonomy
Type
article
Field-Weighted Citation Impact
0.00
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article

Fault-Tolerant Data Aggregation for Reliable Wireless Sensor Networks

Zenodo (CERN European Organization for Nuclear Research)
Subterranean biodiversity and taxonomy
article

Fault-Tolerant Data Aggregation for Reliable Wireless Sensor Networks

article en

Abstract

Abstract—precise data & information is the lifeblood for the operation of Wireless Sensor Networks (WSNs). Incorrect (faulty data) information may lead to the wrong decision; it decreases the reliability in communication and overall operation of WSN. Fault tolerance is one of the issues in WSNs. Proposed fault-tolerant data aggregation scheme for identifying the faulty data sent by the sensors to the cluster head, where the aggregation is performed. Faulty information or data is discarded before aggregation. It would help to improve the accuracy of data aggregation. Consequently, the transmission overhead reduces, since erroneous data is eliminated. The proposed solution gives better performance by detecting and eliminating faulty data providing nodes

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 57%
Subterranean biodiversity and taxonomy
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