GDE: A Distributed Gradient-Based Algorithm for Distance Estimation in Large-Scale Networks

摘要

Today, wireless networks are connecting most of the devices around us. The scale of these systems demands for novel techniques to maintain availability for various services such as routing, localization, context detection etc. Distance estimation is one of their most important building blocks. The majority of current algorithms, presumes knowledge about node position via systems such as GPS. While for some application scenarios this approach is feasible, for a lot of cases it suffers from frequent unavailability and high costs in terms of energy consumption. The main contribution of this paper is the introduction of a novel distributed algorithm called GDE, for the estimation of distances in large-scale wireless networks. GDE is a. mechanism which estimates distances between nodes based solely on local interactions. The evaluation by means of simulations shows that GDE succeeds in estimating the distance between nodes in both static and mobile scenarios with considerably high accuracy, even under the influence of different kinds of environment parameters, such as node density, node speed, spatial node distribution, multicast percentage, etc.