SpaceGlue: linking spaces for adaptive service location

摘要

We describe a mechanism called SpaceGlue for adaptively locating services based on the preferences and locations of users in a distributed and dynamic network environment. In SpaceGlue, services are bound to physical locations, and a mobile user accesses local services depending on the current space he/she is visiting. SpaceGlue dynamically identifies the relationships between different spaces and links or "glues" spaces together depending on how previous users moved among them and used those services. Once spaces have been glued, users receive a recommendation of remote services (i.e., services provided in a remote space) reflecting the preferences of the crowd of users visiting the area. The strengths of bonds are implicitly evaluated by users and adjusted by the system on the basis of their evaluation. SpaceGlue is an alternative to existing schemes such as data mining and recommendation systems and it is suitable for distributed and dynamic environments. The bonding algorithm for SpaceGlue incrementally computes the relationships or "bonds" between different spaces in a distributed way. We implemented SpaceGlue using a distributed network application platform Ja-Net and evaluated it by simulation to show that it adaptively locates services reflecting trends; in user preferences. By using "Mutual Information (MI)" and "F-measure" as measures to indicate the level of such trends and the accuracy of service recommendation, the simulation results showed that (1) in SpaceGlue, the F-measure increases depending on the level of MI (i.e., the more significant the trends, the greater the F-measure values), (2) SpaceGlue achives better precision and F-measure than "Flooding case (i.e., every service information is broadcast to everybody)" and "No glue case" by narrowing appropriate partners to send recommendations based on bonds, and (3) SpaceGlue achieves better F-measure with large number of spaces and users than other cases (i.e., "flooding" and "no glue").