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Efficient Filtering Algorithms for Location- Aware Publish/subscribe


Pooja Prashant vinchu , SBPCOE,Indapur; Dnyanda Pandharinath Bhosale, SBPCOE,Indapur; Pallavi Bharat Dongare, SBPCOE,Indapur, SBPCOE,Indapur; Anjali Sanjivanrao More, SBPCOE,Indapur


LBS, Spatial-Context, MBR Filter, Token Filter, Ranking Query, R t-Tree


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.

Other Details

Paper ID: IJSRDV3I100136
Published in: Volume : 3, Issue : 10
Publication Date: 01/01/2016
Page(s): 137-139

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