Skip to Main Content
Our work draws on a concrete parking space search application to explore fundamental tradeoffs of wireless networking solutions to the provision of real-life services. In particular, we consider a city area, wherein each vehicle (mobile user) moves towards a chosen destination and seeks vacant parking space in its vicinity. Three main approaches to the parking space search problem are investigated, each representing a distinct paradigm of how wireless networking communications can assist the information management process. In the first approach, the vehicles execute the currently common “blind” sequential search for parking space by wandering around the destination. In the second distributed approach, the vehicles, while moving around the area, opportunistically collect and share with each other information on the location and status of each parking spot they encounter. Finally, with the third approach, the allocation of parking spots is managed by a central server availing global knowledge about the parking space availability. We compare the three approaches with respect to the time and distance vehicles need to travel before they park as well as the proximity of the assigned parking spots to the travel destinations. Results obtained under two scenarios for the user travel preferences (uniformly distributed travel destinations vs. a single hotspot road), reveal that the relative performance of the three solutions can vary significantly and not always inline with intuition. In the hotspot scenario, the centralized system consistently yields the minimum times and distances at the expense of more distant parking spot assignments; whereas, when user travel destinations are uniformly distributed, the relative performance of all three schemes changes as the vehicle volume grows, with the centralized approach gradually becoming the worst solution. We discuss the way each approach modulates the information dissemination process in space and time and resolve- - s the emerging competition for the parking resources. We also outline models for getting analytical insights to the behavior of the centralized approach.