SINA: Scalable Incremental Processing of Continuous Queries in Spatio-temporal Databases

This paper introduces the Scalable INcremental hash-based Algorithm (SINA, for short); a new algorithm for evaluating a set of concurrent continuous spatio-temporal queries. SINA is designed with two goals in mind: (1) Scalability in terms of the number of concurrent continuous spatiotemporal queries, and (2) Incremental evaluation of continuous spatio-temporal queries. SINA achieves scalability by employing a shared execution paradigm where the execucontinuous spatio-temporal queries is abstracted as a spatial join between a set of moving objects and a set of moving queries. Incremental evaluation is achieved by computing only the updates of the previously reported answer. We introduce two types of updates, namely positive and negative updates. Positive or negative updates indicate that a certain object should be added to or removed from the previously reported answer, respectively. SINA manages the computation of positive and negative updates via three phases: the hashing phase, the...

• Type: Conference
• Year: 2004
• Where: SIGMOD
• Authors: Mohamed F. Mokbel, Xiaopeng Xiong, Walid G. Aref
• Keywords: Continuous Spatio-temporal Queries, Database, Invalidation Phase, Negative Updates, SIGMOD 2004