The Role of Fractal Dimension in Wireless Mesh Network Performance

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.

14 pages, 8 figures, 2 tables. Accepted for publication in Nature Scientific Reports

References in corpus (6)

• How to calculate the fractal dimension of a complex network: the box covering algorithm
• Self-similarity, small-world, scale-free scaling, disassortativity, and robustness in hierarchical lattices
• Comparative Analysis of Box-Covering Algorithms for Fractal Networks
• Scaling theory of fractal complex networks
• Single Gateway Placement in Wireless Mesh Networks
• Beyond traditional box-covering: Determining the fractal dimension of complex networks using a fixed number of boxes of flexible diameter