Flamo: Filtering Algorithms for Location Based Publish/Subscribe on Moving Objects

Anu Mary Thomas, Laiji George

Abstract: Flamo The growth of social networks and mobile telephony has facilitated the real time propagation of location based services. Instant location based publish/subscribe system are unavoidable for next generation location based models. The existing works in this area are designed for static publishers/ subscribers. To explore the nearby local events and to get instant replies a push model system is necessary where user registers their interests and the server publishes instant relevant answers. In FLAMO we introduces an efficient publish/subscribe method that can easily publish location aware results even for moving subscribers. This uses an R-tree based index by integrating textual descriptions into R-tree nodes is used to achieve results. This method can support both conjunctive queries and ranking queries and also works for both static and moving objects.

Keywords: Subscription, Filter, LBS, Rt-Tree, Tokens