Location-based services have been widely adopted in many systems. Existing works employ a pull model or userinitiated model, where a user issues a query to a server which replies with location-aware answers. To provide users with instant replies, a push model or server-initiated model is becoming an inevitable computing model in the next-generation locationbased services. In the push model, subscribers register spatio-textual subscriptions to capture their interests, and publishers post spatio-textual messages. These calls for a high-performance location-aware publish/subscribe system to deliver publishers’ messages to relevant subscribers. The research challenges has been studied that arise in designing a location-aware publish/subscribe system. An R-tree based index is proposed by integrating textual descriptions into R-tree nodes. An efficient filtering algorithm is proposed and effective pruning techniques to achieve high performance. This method can support both conjunctive queries and ranking queries. Adding location-awareness to publish-subscribe middleware infrastructures would open-up new opportunities to use this technology in the hot area of mobile applications. On the other hand, this requires to radically change the way published events are matched against received subscriptions.