Gander is a distributed search engine for mobile networked environments characterized by high volumes of short-lived data. We refer to these emerging types of environments as Personalized Networked Spaces (PNetS).

PNetS are comprised of digital devices, both mobile and embedded in the environment (e.g., smart phones, sensors, RFID tags), connected by a dynamic network topology. As in the Internet, large volumes of data motivate the need for expressive search mechanisms that efficiently identify and provide access to information relevant to users' needs. However, the volatile and heterogeneous nature of PNetS' network and data preclude traditional information retrieval techniques.

This project aims to address the novel research and software engineering challenges that arise from the new requirements in this emerging search space.

This project is funded, in part, by the National Science Foundation under grant CNS-0844850 and a Google Research Award. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation (NSF).


Project Participants: Jonas Michel (Ph.D. student), Dr. Christine Julien (MPC director), Dr. Jamie Payton (collaborator at The University of North Carolina-Charlotte), Dr. Gruia-Catalin Roman (collaborator at The University of New Mexico)