Adaptive Interest Modeling Enables Proactive Content Services at the Network Edge.

We have successfully applied user modeling in a networking project. The goal of the project was to develop the network services to enable efficient and transparent distribution of content in mobile ad-hoc network (MANET) environments often deployed in emergency and tactical situations. How to get the relevant content to the right user quickly, in the midst of network disruptions and resource constraints, is a key research challenge. To address this problem, we have developed adaptive interest modeling (AIM) to capture user interests and information needs and build an interest model (IM) for each node. One key contribution of our approach is to anchor AIM at the content-based network layer, which allows all upper level mobile applications to benefit without modification. This adaptive IM can enable many user-aware features including content prefetching and IM sharing. We have developed a unique type of prefetching that is based on recognizing user situations. IM sharing is a novel and efficient way of automatically keeping users up to date with each other. This is especially useful in tactical scenarios where it is important to have a common operational picture among users. Our network emulation experiments show that IM-enabled prefetching significantly reduces response time while increasing data availability at the same time. When combined with IM sharing, additional sizable reduction in response time is achieved. Keywords—user modeling; context awareness; mobile device; interest; MANET; network layer; content availability; prefetch; sharing