Location Aware ServicesO Large number of mobile and stationary objects.O Small number of fixed regional servers.O Mobiles and objects issue spatio-temporal queries.O These queries change their location/shape over time.
Location Aware ServicesO Snapshot queries: queries answered using already collected data.O Continuous queries: queries whose response determined by data continuously accumulated into server.O Delay in response is obsolete or invalid answer.
Location Aware ServicesO What affect LAS: O Scalability. O Number of supported moving objects. O Spatio-temporal query types. O Complexity. O I/O and CPU intensive usage.O Fast response to large number of continuous concurrent spatio-temporal queries.
Spatio-Temporal QueryO Classified based on time: O Historical. O Now. O Future.O Classified based on Objects and Queries: O Stationary Queries on moving objects. O Moving Queries on stationary objects. O Moving Queries on moving objects.
ScalabilityO Framework to support any type of concurrent continuous spatio-temporal queries.O Sharing: O Space. O Query operator. O Object interest. O Selection. O Window Join.
Sharing the SelectionO Find all vehicles with speed greater than 30 in Amman?O How many vehicles with speed greater than 40 in Amman? SELECT V.ID FROM Vehicles V WHERE V.speed>speed AND V.Location inside R
Sharing the SelectionO Use Filter Pull up approach.O Pull up selection predicates after the join.O Filter inserted before the join.
Sharing Window JoinO Share join operator among different objects.O Moving objects are like a sliding window.O Find the cars and trucks with the same speed in the last 10 minutes?
ConclusionO Location aware services handle large number of mobile, stationary objects and continuous concurrent queries.O Scalability is needed in terms of processing CCSQ in real time response.O Different types of sharing was introduced to handle different types of spatio-temporal queries.