Geographic Centroid Routing for Vehicular Networks

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.Comment: 6 page

Implementation of Epidemic Routing with IP Convergence Layer in ns-3

We present the Epidemic routing protocol implementation in ns-3. It is a full-featured DTN protocol in that it supports the message abstraction and store-and-haul behavior. We compare the performance of our Epidemic routing ns-3 implementation with the existing implementation of Epidemic in the ONE simulator, and discuss the differences

Geolocation Assisted Routing Protocols for Vehicular Networks

International Conference on Connected Vehicles (ICCVE)The class of flooding-based DTN routing protocols that leverage (transitive) encounter probabilities have been shown to perform well in selected simulations and scenarios, however they are especially sensitive to heterogeneous mobility models in which some nodes’ mobility pattern is on a significantly differ- ent timescale than others. In particular, military and disaster response scenarios can exhibit abrupt topology changes. We analytically show that the worst-case inputs to these existing DTN routing algorithms can drastically reduce their performance. In light of such scenarios, we develop new protocols that inherit the benefits of existing schemes, while leveraging geographic assis- tance to enable faster recovery from abrupt topology changes.This work was funded in part by the US Marine Corps and US Nav