On Asymptotic Statistics for Geometric Routing Schemes in Wireless Ad-Hoc Networks

TL;DR

This paper develops a statistical and geometric analysis framework to study the asymptotic behavior of routing path lengths in wireless ad-hoc networks, focusing on the random 1/2-disk routing scheme.

Contribution

It introduces a Markov process approximation for routing progress and establishes asymptotic connectivity and path length statistics for large networks.

Findings

Expected normalized path length converges to 3π/4.

Variance-to-mean ratio converges to 9π²/64 - 1.

Asymptotic results are accurate for finite networks.

Abstract

In this paper we present a methodology employing statistical analysis and stochastic geometry to study geometric routing schemes in wireless ad-hoc networks. In particular, we analyze the network layer performance of one such scheme, the random $\frac{1}{2}$disk routing scheme, which is a localized geometric routing scheme in which each node chooses the next relay randomly among the nodes within its transmission range and in the general direction of the destination. The techniques developed in this paper enable us to establish the asymptotic connectivity and the convergence results for the mean and variance of the routing path lengths generated by geometric routing schemes in random wireless networks. In particular, we approximate the progress of the routing path towards the destination by a Markov process and determine the sufficient conditions that ensure the asymptotic connectivity for both dense and large-scale ad-hoc networks deploying the random $\frac{1}{2}$disk routing scheme. Furthermore, using this Markov characterization, we show that the expected length (hop-count) of the path generated by the random $\frac{1}{2}$disk routing scheme normalized by the length of the path generated by the ideal direct-line routing, converges to $3\pi/4$ asymptotically. Moreover, we show that the variance-to-mean ratio of the routing path length converges to $9\pi^2/64-1$ asymptotically. Through simulation, we show that the aforementioned asymptotic statistics are in fact quite accurate even for finite granularity and size of the network.