Publication
Embedded sensors and actuators are revolutionizing the way we perceive and interact with the physical world. Current research on such Cyber-Physical Systems (CPSs) has focused mostly on distributed sensing and data gathering. The next step is to move from passive information extraction from the physical world towards an active framework where information is retrieved, processed, and acted upon in situ. As an example of such sensor-actuator systems that provide large-scale, distributed coordination, we consider Intelligent Transportation Systems (ITSs), with the goal of increasing travel safety and efficiency. The proliferation of wireless technologies enables different actors (e.g., pedestrians, motorists, traffic operators) to communicate with each other cheaply, efficiently, and securely. By embedding computational intelligence, communication and control into such ITSs, it will be possible to build collaborative transportation applications that help solve, for example, congestion and parking problems. This thesis explores the following question: To what extent is it possible to build distributed ITS systems that rely exclusively on local communication between nodes? The potential benefits of building such systems without infrastructure are numerous, including lower fixed and variable costs, avoiding regulatory hurdles, lower entry barriers for new players, and more control over privacy. On the other hand, self-organized ITSs without infrastructure have to operate under challenging conditions: large scale, high mobility, lack of end-to-end connectivity, ephemeral contacts between wireless nodes, and heterogeneous node capabilities. Although the networking research community has invested a significant effort in designing service abstractions that mimic traditional IP connectivity on top of wireless ad hoc networks, the ITS scenarios considered in this work are too challenging to implement such a service model. The main goal of this thesis is to design communication service models and their underlying protocols that can operate in collaborative transportation applications, and to demonstrate their effectiveness through analysis of traffic data and through realistic simulations. A key point is that the ITS applications we consider can rely on more limited service primitives, because they do not require a general any-to-any delivery service with strict performance guarantees. We first define the collaborative transportation applications of interest. Then we quantify their potential benefits and discuss their functional requirements. Next, we focus on the problem of the collection of large-scale mobility data. We propose a new method for collecting such data and introduce a novel mobility data mining framework, which is necessary to study collective mobility patterns in the context of wireless ad hoc networking. Relying on the analysis of real-life mobility traces, we find that despite the high node mobility, clusters of time-stable connectivity emer