From Human Mobility to Data Mobility: Leveraging Spatiotemporal History in Device-to-Device Information Diffusion

摘要

Supporting mobile applications in densely populated environments requires connecting mobile users and their devices with the surrounding digital landscape. Device-to-device communications (without the support of an infrastructure) will play a critical role in facilitating transparent access to proximate digital resources. A variety of approaches exist to support device-to-device dissemination, yet very few capitalize on the contextual history of disseminated data itself to distribute additional data. We introduce a fully decentralized model that captures the causal history of shared information across a lifetime of device-to-device propagation. Our approach enhances each transmitted message with a spatiotemporal trajectory, a portion of the message's contextual history, which provides a window into the time-varying state of the network and the overall spreading behavior of the message. We benchmark the performance of spatiotemporal trajectories at a global level and demonstrate the practical utility of our constructs for making intelligent distributed routing decisions through two use cases. The first illustrates how locally-available contextual history may be used to make inferences about remote nodes' knowledge and thus direct routing of future messages. The second example uses trajectories from different types of data to identify commonly co-located data and devices, which can then be used as substitutable routing targets.