Abstract
Motivated by the growing amount of digitally-accessible information in our physical surroundings and the ephemeral nature of that information, there is a profound need to efficiently search information with spatiotemporal underpinnings without a priori indexing. Human users in Personalized Network Spaces (PNetS), pervasive computing environments connected by opportunistic peer-to-peer connections, need information that is immediate and localized. This tight integration of the user with his immediate surroundings introduces novel search requirements. The requisite support for performing search of the here and now in the here and now calls for a new paradigm of search that explicitly separates search from advanced indexing of data. In light of this vision, this paper presents Gander, a scalable search engine for PNetS, along with myGander, a prototype mobile interface for Gander. The utility and usability of myGander as supported by Gander is demonstrated through a practical real-world pervasive computing scenario.