Reconstruction of Aggregation Tree in spite of Faulty Nodes in Wireless Sensor Networks

TL;DR

This paper presents a distributed algorithm for reconstructing aggregation trees in wireless sensor networks, effectively handling multiple faulty nodes to maintain energy-efficient data aggregation.

Contribution

A novel distributed algorithm that reconstructs aggregation trees in WSNs despite multiple faulty nodes, improving network robustness and energy efficiency.

Findings

Successfully reconstructs aggregation trees with multiple faulty nodes.

Operates in a synchronous, multi-round model.

Enhances network resilience and data aggregation reliability.

Abstract

Recent advances in wireless sensor networks (WSNs) have led to many new promissing applications. However data communication between nodes consumes a large portion of the total energy of WSNs. Consequently efficient data aggregation technique can help greatly to reduce power consumption. Data aggregation has emerged as a basic approach in WSNs in order to reduce the number of transmissions of sensor nodes over {\it aggregation tree} and hence minimizing the overall power consumption in the network. If a sensor node fails during data aggregation then the aggregation tree is disconnected. Hence the WSNs rely on in-network aggregation for efficiency but a single faulty node can severely influence the outcome by contributing an arbitrary partial aggregate value. In this paper we have presented a distributed algorithm that reconstruct the aggregation tree from the initial aggregation tree excluding the faulty sensor node. This is a synchronous model that is completed in several rounds. Our proposed scheme can handle multiple number of faulty nodes as well.