DOI: 10.25549/usctheses-c40-332097
title: Network on wheels: from data dissemination to distributed sensing

description: There is an ongoing revolution in the automotive world, as vehicles are all starting to become permanently connected to the Internet. Different car manufacturing companies are working on models that are equipped with different communication devices. This will allow for Vehicle to Vehicle (V2V), vehicle infrastructure (V2I) and Vehicles to everything (V2X) communication capabilities. This has in turn led into new different applications and architectures that are conceivable on the new platform. This thesis focuses on two of the most important applications in this framework, namely: ❧ 1. Data Dissemination ❧ 2. Distributed field sensing. ❧ We also investigate the use of traffic regulations in order to alter urban traffic pattern to a desired form which may fit better to the needs of targeted applications as well as urban standards. Traditionally, vehicular traffic control has focused primarily on easing congestion on public roads and thereby reducing the end to end trip delay for drivers. We consider how traffic control could be optimized to additionally address environmental impact, for instance by reducing the amount of traffic in areas of the city with higher residential population. We model the corresponding optimization as a combinatorial graph problem, with an objective that incorporates both the average end to end delay for commuters as well as penalties on traffic for each road segment. We present a fully distributed algorithm with a guaranteed constant-factor approximation ratio with respect to the optimal solution. We evaluate the proposed algorithm through numerical simulations. ❧ In the data dissemination application study, we present a two-tier hybrid mobile network architecture. In this architecture, the data plane consists of store and forward routing through an intermittently connected mobile network, and the control plane consists of an always-on infrastructure-based wireless network. This architecture aims to enhance bandwidth utilization while providing efficient centralized control. The goal is to investigate how best to utilize the intermediate nodes (called helper nodes) to disseminate content with the help of the control plane. ❧ On the other hand, when all these connected vehicles on the road are equipped with external sensors, we will see the emergence of the ""urban macroscope""—an unprecedented new instrument for city-scale environmental monitoring and scientific discovery. As the numbers of connected sensing vehicles, the number of sensors per vehicle, and the sensing resolution and capabilities grow, the resulting data deluge from the urban macroscope will over-run even the bandwidth improvements to the infrastructure aimed for in the ongoing 5G cellular efforts, unless the data is suitably sampled and compressed. In the distributed field sensing study, we present a rigorous approach for sampling vehicular sensors, which aims to maximize the information collected by the urban macroscope about a given spatio-temporally varying random field, while satisfying communication constraints. The proposed solution in this case is also a two-layer structure that makes use of a low bandwidth feedback channel to address this problem. We show that an optimum data probing scheme within this structure for a basic version of the problem is equivalent to a variant of the maximum coverage problem which, to the best of our knowledge, has not been addressed in the literature before. A sequential probing algorithm is presented for the proposed feedback structure, with mathematical guarantees. We then expand our solution to a more general setting to optimally schedule probes through time and account for unknown traffic trajectories. Simulated traffic as well as real world Beijing taxi traces are used on both synthesized and real field data in order to evaluate and further investigate the performance bound of the proposed system.