Available bandwidth-aware routing in urban vehicular ad-hoc networks

Vehicular communication for intelligent transportation systems will provide safety, comfort for passengers, and more efficient travels. This type of network has the advantage to warn drivers of any event occurred in the road ahead, such as traffic jam, accidents or bad weather. This way, the number of traffic accidents may decrease and many lives could be saved. Moreover, a better selection of non-congested roads will help to reduce pollution. Some other interesting services, such as downloading of multimedia services, would be possible and available through infrastructure along the roadside. Providing multimedia services over VANETs may require a QoS-aware routing protocol that often need to estimate available resources. In this paper, we study the performance, in realistic VANET urban scenarios, of an extension of AODV that includes the available bandwidth estimator ABE [1]. AODV-ABE establishes forwarding paths that satisfy the bandwidth required by the applications. The results, obtained on the NCTUns simulator [2], show that AODVABE could be used in urban-VANETs where vehicles’ speed is moderate.Peer ReviewedPostprint (author’s final draft

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

Physiology-Aware Rural Ambulance Routing

In emergency patient transport from rural medical facility to center tertiary hospital, real-time monitoring of the patient in the ambulance by a physician expert at the tertiary center is crucial. While telemetry healthcare services using mobile networks may enable remote real-time monitoring of transported patients, physiologic measures and tracking are at least as important and requires the existence of high-fidelity communication coverage. However, the wireless networks along the roads especially in rural areas can range from 4G to low-speed 2G, some parts with communication breakage. From a patient care perspective, transport during critical illness can make route selection patient state dependent. Prompt decisions with the relative advantage of a longer more secure bandwidth route versus a shorter, more rapid transport route but with less secure bandwidth must be made. The trade-off between route selection and the quality of wireless communication is an important optimization problem which unfortunately has remained unaddressed by prior work. In this paper, we propose a novel physiology-aware route scheduling approach for emergency ambulance transport of rural patients with acute, high risk diseases in need of continuous remote monitoring. We mathematically model the problem into an NP-hard graph theory problem, and approximate a solution based on a trade-off between communication coverage and shortest path. We profile communication along two major routes in a large rural hospital settings in Illinois, and use the traces to manifest the concept. Further, we design our algorithms and run preliminary experiments for scalability analysis. We believe that our scheduling techniques can become a compelling aid that enables an always-connected remote monitoring system in emergency patient transfer scenarios aimed to prevent morbidity and mortality with early diagnosis treatment.Comment: 6 pages, The Fifth IEEE International Conference on Healthcare Informatics (ICHI 2017), Park City, Utah, 201