The Role of Fractal Dimension in Wireless Mesh Network Performance

TL;DR

This paper investigates how the fractal dimension of node placement in wireless mesh networks affects their performance, introducing a new topology generation algorithm and demonstrating improved resilience and throughput with fractal structures.

Contribution

A novel algorithm for creating WMN topologies with controllable fractal dimensions, enabling exploration of spatial complexity effects on network performance.

Findings

Higher fractal dimensions improve network resilience.

Fractal topologies outperform classical models in throughput.

Performance varies systematically with fractal dimension.

Abstract

Wireless mesh networks (WMNs) depend on the spatial distribution of nodes, which directly influences connectivity, routing efficiency, and overall network performance. Conventional models typically assume uniform or random node placement, which inadequately represent the complex, hierarchical spatial patterns observed in practical deployments. In this study, we present a novel algorithm that constructs WMN topologies with tunable fractal dimensions, allowing precise control over spatial self-similarity. By systematically varying the fractal dimension, the algorithm generates network layouts spanning a continuum of spatial complexities, ranging from sparse fragmented clusters to dense, cohesive structures. Through NS-3 simulations, Key performance metrics including throughput, latency, jitter, and packet delivery ratio were evaluated across a range of fractal dimensions. Comparative evaluations against classical random, small-world, scale-free, grid and hierarchical tree networks models reveal that high-dimensional fractal topologies achieve enhanced resilience and throughput under equivalent conditions. These findings demonstrate the potential of fractal geometry as a design paradigm for scalable and efficient WMN architectures.