A number of geolocation-based Delay Tolerant Networking (DTN) routing protocols have been shown to perform well in selected simulation and mobility scenarios. However, the suitability of these mechanisms for vehicular networks utilizing widely-available inexpensive Global Positioning System (GPS) hardware has not been evaluated. We propose a novel geolocation-based routing primitive (Centroid Routing) that is resilient to the measurement errors commonly present in low-cost GPS devices. Using this notion of Centroids, we construct two novel routing protocols and evaluate their performance with respect to positional errors as well as traditional DTN routing metrics. We show that they outperform existing approaches by a significant margin.
We presented a 2-page poster paper describing the issue of ignoring GPS errors when simulating geographic grouting protocols @cite_0 , however it did not include our novel protocols or the simulation analysis described in this work.
@cite_0
2071091794 2754689497 2108653777 2100801339
This paper describes a process for automatically inferring maps from large collections of opportunistically collected GPS traces. In this type of dataset, there is often a great disparity in terms of coverage. For example, a freeway may be represented by thousands of trips, whereas a residential road may only have a handful of observations. Additionally, while modern GPS receivers typically produce high-quality location estimates, errors over 100 meters are not uncommon, especially near tall buildings or under dense tree coverage. Combined, GPS trace disparity and error present a formidable challenge for the current state of the art in map inference. By tuning the parameters of existing algorithms, a user may choose to remove spurious roads created by GPS noise, or admit less-frequently traveled roads, but not both. In this paper, we present an extensible map inference pipeline, designed to mitigate GPS error, admit less-frequently traveled roads, and scale to large datasets. We demonstrate and compare the performance of our proposed pipeline against existing methods, both qualitatively and quantitatively, using a real-world dataset that includes both high disparity and noise. Our results show significant improvements over the current state of the art. A number of geolocation-based DTN (Delay Tolerant Networking) routing protocols have been shown to perform well in selected simulation and mobility scenarios. However, the suitability of these mechanisms for widely-available inexpensive GPS hardware has not been evaluated. In this brief paper we evaluate the effect of GPS positional error on our own and previously existing geographic routing protocols. Geographic routing protocols for wireless ad hoc networks have gained great attention in the anticipation of the broader use of GPS or other localization schemes. However, location inaccuracies depending on environment and the localization system may affect the performance and even correctness of geographic routing. In this paper, we propose a novel Location-fault-tolerant Geographic Routing (LGR) scheme based on the combination of position-based clustering and geographic routing technologies. We divide the routing problem into the global geographic routing step and the local gradient routing step. Performance analyses and the NS-2 simulation results demonstrate that our scheme has much better performance than others when facing location inaccuracies. This paper presents a method for correcting dead reckoning parameters, which are heading and step size, for a pedestrian navigation system. In this method, the compass bias error and the step size error can be estimated during the period that the Global Positioning System (GPS) signal is available. The errors are used for correcting those parameters to improve the accuracy of position determination using only the dead reckoning system when the GPS signal is not available. The results show that the parameters can be estimated with reasonable accuracy. Moreover, the method also helps to increase the positioning accuracy when the GPS signal is available.