Locus: A Vehicular-based Content Management Network for Location-centric Applications

University Of Illinois At Urbana-Champaign, Urbana IL

Investigators

Abstract

Location-specific data is the enabling component of a new class of applications that can access near real-time and recent historical data about a specific location, driving applications such as vehicle route planning, real-time fuel efficiency and location-based data sharing. The focus on location-centric applications points towards caching of data in the geographic area where it was generated. Since the cache is location-sensitive and vehicles are constantly on the move, traditional caching and content Web-centric prefetching architectures not apply. Additionally, the large volumes of data these devices will generate cannot be supported by existing centralized approaches. Instead, we have designed Locus, a decentralized data overlay that runs on top of the mobile devices themselves. To keep data from a specific location near that location, Locus introduces the novel concept of "bubbles of knowledge", where the sensed data is actually stored in the network by the nodes in the surrounding geographic area, essentially providing localized memory in the network about the sensed data. By using such location information, Locus can achieve more efficient data storage and improve data look-up rates. As more users join the network, the benefits of Locus will be amplified due to the increasing density of the network, increasing both the performance and value of the overlay as the system grows. By maintaining content locally in the vehicular network, Locus reduces the reliance on and cost of infrastructure access, benefiting individuals with mobile data plans that limit total downloads or regions where the cellular data networks are overloaded.