Title :
A Framework for Spatial Predictive Query Processing and Visualization
Author :
Hendawi, Abdeltawab M. ; Ali, Mohamed ; Mokbel, Mohamed F.
Abstract :
This demo presents the Panda system for efficient support of a wide variety of predictive spatio-temporal queries. These queries are widely used in several applications including traffic management, location-based advertising, and store finders. Panda targets long-term query prediction as it relies on adapting a long-term prediction function to: (a) scale up to large number of moving objects, and (b) support predictive queries. Panda does not only aim to predict the query answer, but, it also aims to predict the incoming queries such that parts of the query answer can be precomputed before the query arrival. Panda maintains a tunable threshold that achieves a trade-off between the predictive query response time and the system overhead in precomputing the query answer. Equipped with a Graphical User Interface (GUI), audience can explore the Panda demo through issuing predictive queries over a moving set of objects on a map. In addition, they are able to follow the execution of such queries through an eye on the Panda execution engine.
Keywords :
Data structures; Maintenance engineering; Microprocessors; Query processing; Systems architecture; Time factors;
Conference_Titel :
Mobile Data Management (MDM), 2015 16th IEEE International Conference on
Conference_Location :
Pittsburgh, PA, USA
Print_ISBN :
978-1-4799-9971-2
DOI :
10.1109/MDM.2015.79