Efficient Filtering Algorithms for Location- Aware Publish/subscribe

Location-based services have been mostly used in many systems. preceding systems uses a pull model or user-initiated model, where a user arrival a query to a server which gives response with location-aware answers. To offer outcomes to users with fast responses, a push model or server-initiated model is flattering an important computing model in the next-generation location-based services. In the push model, subscribers arrive spatio-textual subscriptions to fastening their curiosities, and publishers send spatio-textual messages. It is used for a high-performance location-aware publish/subscribe system to send publishers� messages to valid subscribers. In this paper, we find the exploration happenstances that start in manipulative a location-aware publish/subscribe system. We recommend an R-tree based index by merging textual descriptions into R-tree nodes. We design efficient filtering algorithms and effective pruning techniques to accomplish high performance. This method can support likewise conjunctive queries and ranking queries.