Towards Scalable Location-     aware Services:   Requirements and     Research Issues     Presented by Ishraq Fatafta
AgendaO Introduction.O What is PLACE project.O Spatio-Temporal Queries.O Scalability through sharing.O Conclusion.
Introduction
Location Aware ServicesO Large number of mobile and stationary  objects.O Small number of fixed regional servers.O Mobiles...
Location Aware ServicesO Snapshot queries: queries answered  using already collected data.O Continuous queries: queries wh...
Location Aware ServicesO What affect LAS:  O Scalability.    O Number of supported moving objects.    O Spatio-temporal qu...
PLACE Project
Spatio-Temporal QueryO Classified based on time:  O Historical.  O Now.  O Future.O Classified based on Objects and Querie...
ScalabilityO Framework to support any type of  concurrent continuous spatio-temporal  queries.O Sharing:  O Space.  O Quer...
Sharing in PLACE
Sharing in PLACEO Example:  O Vehicle navigation system to track all    moving vehicles.  O Data stored in vehicle table: ...
Sharing SpaceO Share underlying spatial domain through  containment.O How many vehicles areInside PSUT campus?O Challenging.
Sharing SpaceO E1=(2)(x1)+(1)(1-x1) = 1+x1.O E2 = (1)(x2)+(2)(1-x2) = 2-x2.O Suppose x1=0.7, x2=0.1  E1 = 1.7, E2 = 1.9O S...
Sharing Query OperatorO Continuously, how many vehicles are in  R1?O Alert me when number of vehicles in R2  exceed certai...
Sharing Query Operator
Sharing the Object InterestO How many cars in Amman from now  onwards?O How many trucks in Amman from now  onwards? SELECT...
Sharing the Object Interest
Sharing the SelectionO Find all vehicles with speed greater than  30 in Amman?O How many vehicles with speed greater  than...
Sharing the SelectionO Use Filter Pull up approach.O Pull up selection predicates after the join.O Filter inserted before ...
Sharing Window JoinO Share join operator among different  objects.O Moving objects are like a sliding window.O Find the ca...
ConclusionO Location aware services handle large number of  mobile, stationary objects and continuous  concurrent queries....
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Towards scalable locationaware

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  • Continuous: accumulated every time interval or based on triggering event.
  • Towards scalable locationaware

    1. 1. Towards Scalable Location- aware Services: Requirements and Research Issues Presented by Ishraq Fatafta
    2. 2. AgendaO Introduction.O What is PLACE project.O Spatio-Temporal Queries.O Scalability through sharing.O Conclusion.
    3. 3. Introduction
    4. 4. 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.
    5. 5. 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.
    6. 6. 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.
    7. 7. PLACE Project
    8. 8. 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.
    9. 9. 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.
    10. 10. Sharing in PLACE
    11. 11. Sharing in PLACEO Example: O Vehicle navigation system to track all moving vehicles. O Data stored in vehicle table: O Vehicles(ID, location, time, speed, type) O Now queries.
    12. 12. Sharing SpaceO Share underlying spatial domain through containment.O How many vehicles areInside PSUT campus?O Challenging.
    13. 13. Sharing SpaceO E1=(2)(x1)+(1)(1-x1) = 1+x1.O E2 = (1)(x2)+(2)(1-x2) = 2-x2.O Suppose x1=0.7, x2=0.1 E1 = 1.7, E2 = 1.9O Suppose x1=0.8, x2=0.5 E1 = 1.8, E2 = 1.5
    14. 14. Sharing Query OperatorO Continuously, how many vehicles are in R1?O Alert me when number of vehicles in R2 exceed certain threshold? SELECT Count(V.ID) FORM Vehicles V WHERE V.Location inside Ri
    15. 15. Sharing Query Operator
    16. 16. Sharing the Object InterestO How many cars in Amman from now onwards?O How many trucks in Amman from now onwards? SELECT Count(V.ID) FROM Vehicles V WHERE V.type=type and V.Location inside R
    17. 17. Sharing the Object Interest
    18. 18. 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
    19. 19. Sharing the SelectionO Use Filter Pull up approach.O Pull up selection predicates after the join.O Filter inserted before the join.
    20. 20. 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?
    21. 21. 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.

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