PLACE: a query processor for handling real-time spatio-temporal data streams

  • Authors:

  • Mohamed F. Mokbel;Xiaopeng Xiong;Walid G. Aref;Susanne E. Hambrusch;Sunil Prabhakar;Moustafa A. Hammad

  • Affiliations:

  • Department of Computer Sciences, Purdue University, West Lafayette, IN;Department of Computer Sciences, Purdue University, West Lafayette, IN;Department of Computer Sciences, Purdue University, West Lafayette, IN;Department of Computer Sciences, Purdue University, West Lafayette, IN;Department of Computer Sciences, Purdue University, West Lafayette, IN;Department of Computer Sciences, Purdue University, West Lafayette, IN

  • Venue:
  • VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
  • Year:
  • 2004

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Abstract

The emergence of location-aware services calls for new real-time spatio-temporal query processing algorithms that deal with large numbers of mobile objects and queries. In this demo, we present PLACE (Pervasive Location-Aware Computing Environments); a scalable location-aware database server developed at Purdue University. The PLACE server addresses scalability by adopting an incremental evaluation mechanism for answering concurrently executing continuous spatio-temporal queries. The PLACE server supports a wide variety of stationery and moving continuous spatio-temporal queries through a set of pipelined spatio-temporal operators. The large numbers of moving objects generate real-time spatio-temporal data streams.