A Framework for Spatial Predictive Query Processing and Visualization

Abdeltawab M. Hendawi, Mohamed Ali, Mohamed F Mokbel

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

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.

Original languageEnglish (US)
Title of host publicationProceedings - 2015 IEEE 16th International Conference on Mobile Data Management, MDM 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages327-330
Number of pages4
ISBN (Electronic)9781479999729
DOIs
StatePublished - Sep 11 2015
Event16th IEEE International Conference on Mobile Data Management, MDM 2015 - Pittsburgh, United States
Duration: Jun 15 2015Jun 18 2015

Publication series

NameProceedings - IEEE International Conference on Mobile Data Management
Volume1
ISSN (Print)1551-6245

Other

Other16th IEEE International Conference on Mobile Data Management, MDM 2015
CountryUnited States
CityPittsburgh
Period6/15/156/18/15

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