The tornado model: Uncertainty model for continuously changing data

To support emerging database applications that deal with continuously changing (or moving) data objects (CCDOs), such as vehicles, RFIDs, and multi-stimuli sensors, one requires an efficient data management system that can store, update, and retrieve large sets of CCDOs. Although actual CCDOs can continuously change over time, computer systems cannot deal with continuously occurring infinitesimal changes. Thus, in the data management system, each object's spatiotemporal values are associated with a certain degree of uncertainty at virtually every point in time, and the queries are mostly processed over estimates characterizing the uncertainty. The smaller the uncertainty is, the better the query performance becomes. The paper proposes a sophisticated asymmetric uncertainty model, called the Tornado Model, which can effectively represent, process, and minimize the data uncertainty for a wide variety of CCDO database applications.