Continuous Query Processing in Spatio-Temporal Databases

Provided by: Purdue Federal Credit Union
Topic: Data Management
Format: PDF
In this paper, the authors aim to develop a framework for continuous query processing in spatio-temporal databases. The proposed framework distinguishes itself from other query processors by employing two main paradigms Scalability in terms of the number of concurrent continuous spatio-temporal queries. Incremental evaluation of continuous spatio-temporal queries. Scalability is achieved thorough employing a shared execution paradigm. Incremental evaluation is achieved through computing only the updates to the previously reported answer. They distinguish between two types of updates; positive updates and negative updates. Positive or negative updates indicate that a certain object should be added to or removed from the previously reported answer, respectively.

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