CapEst: A Measurement-based Approach to Estimating Link Capacity in Wireless Networks

TL;DR

CapEst is a simple, measurement-based method for accurately estimating wireless link capacity that converges quickly and is applicable across various MAC/PHY layers with minimal overhead.

Contribution

It introduces CapEst, a novel iterative measurement-based approach that accurately estimates wireless link capacity without complex models or high implementation costs.

Findings

Converges within 18 iterations to within 5% of true capacity

Model-independent and applicable to any MAC/PHY layer

Low implementation overhead and compatible with auto-rate adaptation

Abstract

Estimating link capacity in a wireless network is a complex task because the available capacity at a link is a function of not only the current arrival rate at that link, but also of the arrival rate at links which interfere with that link as well as of the nature of interference between these links. Models which accurately characterize this dependence are either too computationally complex to be useful or lack accuracy. Further, they have a high implementation overhead and make restrictive assumptions, which makes them inapplicable to real networks. In this paper, we propose CapEst, a general, simple yet accurate, measurement-based approach to estimating link capacity in a wireless network. To be computationally light, CapEst allows inaccuracy in estimation; however, using measurements, it can correct this inaccuracy in an iterative fashion and converge to the correct estimate. Our evaluation shows that CapEst always converged to within 5% of the correct value in less than 18 iterations. CapEst is model-independent, hence, is applicable to any MAC/PHY layer and works with auto-rate adaptation. Moreover, it has a low implementation overhead, can be used with any application which requires an estimate of residual capacity on a wireless link and can be implemented completely at the network layer without any support from the underlying chipset.