Efficient Algorithms for Distributed Detection of Holes and Boundaries in Wireless Networks

TL;DR

This paper introduces two innovative, distributed algorithms for boundary detection in wireless sensor networks that operate solely on local connectivity data, offering robustness, simplicity, and superior performance over existing methods.

Contribution

The paper presents two new algorithms for boundary recognition that are fully distributed, require minimal information, and outperform previous approaches in robustness and ease of implementation.

Findings

Algorithms outperform previous methods in accuracy and robustness.

They are highly adaptable to dynamic network conditions.

Implementation is simpler compared to existing approaches.

Abstract

We propose two novel algorithms for distributed and location-free boundary recognition in wireless sensor networks. Both approaches enable a node to decide autonomously whether it is a boundary node, based solely on connectivity information of a small neighborhood. This makes our algorithms highly applicable for dynamic networks where nodes can move or become inoperative. We compare our algorithms qualitatively and quantitatively with several previous approaches. In extensive simulations, we consider various models and scenarios. Although our algorithms use less information than most other approaches, they produce significantly better results. They are very robust against variations in node degree and do not rely on simplified assumptions of the communication model. Moreover, they are much easier to implement on real sensor nodes than most existing approaches.