FAIR: Fuzzy-based Aggregation providing In-network Resilience for real-time Wireless Sensor Networks

TL;DR

FAIR is a fuzzy-based aggregation framework that enhances in-network resilience in wireless sensor networks by ensuring data integrity, tolerating failures, and providing trust visibility, thus improving robustness against malicious and faulty nodes.

Contribution

The paper introduces FAIR, a novel fuzzy-based aggregation framework that offers in-network resilience, trust visibility, and general applicability for wireless sensor networks.

Findings

Achieves data integrity and fault tolerance in WSNs.

Provides trust level visibility to the querier.

Offers a flexible and promising resilience solution.

Abstract

This work introduces FAIR, a novel framework for Fuzzy-based Aggregation providing In-network Resilience for Wireless Sensor Networks. FAIR addresses the possibility of malicious aggregator nodes manipulating data. It provides data-integrity based on a trust level of the WSN response and it tolerates link or node failures. Compared to available solutions, it offers a general aggregation model and makes the trust level visible to the querier. We classify the proposed approach as complementary to protocols ensuring resilience against sensor leaf nodes providing faulty data. Thanks to our flexible resilient framework and due to the use of Fuzzy Inference Schemes, we achieve promising results within a short design cycle.