2013 LocationAwarePublishsubscribe

• (Li et al., 2013) ⇒ Guoliang Li, Yang Wang, Ting Wang, and Jianhua Feng. (2013). “Location-aware Publish/subscribe.” In: Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ISBN:978-1-4503-2174-7 doi:10.1145/2487575.2487617

Subject Headings:

Cited By

• http://scholar.google.com/scholar?q=%222013%22+Location-aware+Publish%2Fsubscribe
• http://dl.acm.org/citation.cfm?id=2487575.2487617&preflayout=flat#citedby

Quotes

Author Keywords

• Location-aware publish/subscribe; spatial databases and gis

Abstract

Location-based services have become widely available on mobile devices. Existing methods employ a pull model or user-initiated 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 location-based services. In the push model, subscribers register spatio-textual subscriptions to capture their interests, and publishers post spatio-textual messages. This calls for a high-performance location-aware publish / subscribe system to deliver publishers' messages to relevant subscribers.In this paper, we address the research challenges that arise in designing a location-aware publish / subscribe system. We propose an rtree based index structure by integrating textual descriptions into rtree nodes. We devise efficient filtering algorithms and develop effective pruning techniques to improve filtering efficiency. Experimental results show that our method achieves high performance. For example, our method can filter 500 tweets in a second for 10 million registered subscriptions on a commodity computer.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2013 LocationAwarePublishsubscribe	Yang Wang Ting Wang Guoliang Li Jianhua Feng			Location-aware Publish/subscribe				10.1145/2487575.2487617		2013