Characterizing the Energy Trade-Offs of End-to-End Vehicular Communications using an Hyperfractal Urban Modelling

TL;DR

This paper models urban vehicular communication networks using a hyperfractal approach to analyze the trade-offs between energy consumption and communication delay, providing theoretical bounds and validating with real data and simulations.

Contribution

It introduces a hyperfractal model for urban vehicular networks that incorporates infrastructure and offers rigorous analysis of energy-delay trade-offs.

Findings

End-to-end hop count scales as O(n^{1-rac{eta}{d_F-1}})

Energy consumption decreases with longer routing paths in large networks

Model aligns with real urban deployment data

Abstract

We characterize trade-offs between the end-to-end communication delay and the energy in urban vehicular communications with infrastructure assistance. Our study exploits the self-similarity of the location of communication entities in cities by modeling them with an innovative model called "hyperfractal". We show that the hyperfractal model can be extended to incorporate road-side infrastructure and provide stochastic geometry tools to allow a rigorous analysis. We compute theoretical bounds for the end-to-end communication hop count considering two different energy-minimizing goals: either total accumulated energy or maximum energy per node. We prove that the hop count for an end-to-end transmission is bounded by $O(n^{1-\alpha/(d_F-1)})$ where $\alpha<1$ and $d_F>2$ is the fractal dimension of the mobile nodes process. This proves that for both constraints the energy decreases as we allow choosing routing paths of higher length. The asymptotic limit of the energy becomes significantly small when the number of nodes becomes asymptotically large. A lower bound on the network throughput capacity with constraints on path energy is also given. We show that our model fits real deployments where open data sets are available. The results are confirmed through simulations using different fractal dimensions in a Matlab simulator.