Location Information Management and Moving Object Databases

1. Location Information Management and Moving Object Databases “Moving Object Databases: Issues and Solutions” Ouri, Bo, Sam and Liqin

2. Contents • Introduction • Challenges of Location Information Management • Location Modeling • Uncertainty Management • Distributed/Mobile Environment • Location Prediction

3. Contents contd… • Moving Object Databases • Location Modeling • Dynamic Attributes • Data Model • Linguistics Issues • Spatial and Temporal Query Language • Indexing • Uncertainty/Imprecision Management • Advantages and Disadvantages • Conclusions and Future work

4. Introduction • Location management is managing location information of mobile devices and using the data in various applications. • Location management is a fundamental component of applications like location based services, tourist services, disaster recovery, context awareness, and dynamic resource discovery.

5. Introduction contd.. • Location-based services can be divided into two categories - Mobile Resource Management, and Location-Aware Content Delivery • Mobile Resource Management applications • Mobile workforce management • Automatic location Management • Transportation Management These Systems use location data combined with route schedules to track and manage service personnel or transportation systems.

6. Location-aware Content Delivery Services • These services use location data to tailor the information delivered to the mobile user to increase relevancy. • Delivering driving directions • Instant coupons to customers nearing a store • Nearest resource information like local restaurants, hospitals, ATM machines, or gas stations

7. Example queries to be answered by a Location Management System • How many times was bus#5 late by more than 5 minutes at some station( Past Query ) • Retrieve the helicopters that enter region R within next 10 minutes( Future Query ) • Send a message when a helicopter is in a given Region( Trigger )

8. Required Capabilities of a Location Management System • Modeling of Location Information • Spatio-temporal data access languages • Uncertainty Management • Indexing and scalability issues • Data mining(traffic and location prediction) • Privacy and Security • Synchronization of data from multiple sensors

9. Location Modeling • Existing DBMS are not well equipped to handle continuously changing data. Here data is assumed to be constant unless explicitly notified. • To represent moving objects to the database has two disadvantages • DBMS cannot handle frequent updates from many mobile devices • Frequent updates impose a serious wireless bandwidth overhead.

10. Using Dynamic attributes to model data • This approach tries to use DBMS will new attribute called the “dynamic attribute” to model data • Dynamic attribute is used to store location as a function of time • The answer to a query depends on database contents and also the time when the query is asked. • A higher level of abstraction is used

11. Dynamic attribute • A Dynamic Attribute A is represented by three sub-attributes • A.update_value • A.update_time • A.function • The value of the dynamic attribute at time A.update_time + t0 is A.update_value + A.function( t0 ) • The location attribute has sub-attributes L.x, L.y, L.speed, and L.angle or L.route, where x and y are of type A • Only when there is a change in speed or change in direction of the object, the database needs to be updated

12. Example on Dynamic attribute • Speed = 10miles/unit_time, Direction = North • update_value = 100 • update_time = 5 • function = 10*t for y direction • Value of y at time 15 = 100 + 10*(15-5) = 100+100 = 200

13. Linguistics Issues • Traditional query languages such as SQL are inadequate for expressing queries involving spatio-temporal data • Temporal predicates used • begin_time( … ) • end_time( … ) • now

14. Spatial Query language predicates • DIST( o, n ), where o and n are two mobile devices • INSIDE( o, R ), where o is a mobile device and R is a region

15. Queries using defined predicates • Retrieve the pairs of objects o and n such that the distance between o and n stays within 5 miles until they both enter the polynomial P • RETRIEVE o, n • FROM Moving-Objects • WHERE begin_time( DIST(o,n) <=5 )<=now • and end_time( DIST(o,n) <= 5 ) >= • begin_time( INSIDE(o,P) ^ INSIDE(n,P))

16. Other Temporal Query Predicates • Future queries • UNTIL • NextTime • Eventually_within( c, g ) • Eventually_after( c, g ) • Always_for( c, g )

17. Example Future Query • “ Retrieve all objects o that enter the polygon P within three units of time and have the attribute GAS <= 10gallons” • RETRIEVE o • WHERE o.GAS <=10 ^ Eventually_within( 3, INSIDE(o,P) )

18. Indexing Dynamic attributes • To index queries like “Retrieve the objects that are currently inside the polygon P” or “Retrieve the objects whose dynamic attribute value is in the range[Ac …. Ae] at time t” • R+ trees cannot be used to index temporal queries because they cannot be used to model temporal data

19. Indexing Contd.. • Value-time space representation

20. Uncertainty Management • The location of a moving object is inherently imprecise regardless the update policy. • To accommodate uncertainty, a new sub-attribute to the dynamic attribute named L.uncertainty should be added. • “May” and “must” semantics should be incorporated in the query language

21. Implementation Details • Architecture

22. Implementation Details contd.. • DBMS: Oracle database is selected as DBMS because it handles multi-user access which is an inherent property. • A Wrapper application shall be used on DBMS, because normal DBMS do not have spatio-temporal query handling capabilities. • Because the mobile device have movement involved, updations to the location data is web enabled, a servlet is used

23. Advantages • Simple approach to handle location management using DBMS. • Very few updates to database are needed. • The architecture shall not cost much to construct. • Answers queries that involve both temporal and spatial data. • Handles uncertainty of mobile unit location.

24. Disadvantages • The mobile unit should have capability to give its location uncertainty. • Dynamic attribute may also need to be updated frequently if the mobility pattern is not smooth. • A function for the dynamic attribute may not be able to expressed in few cases.

25. Conclusion • Advances in wireless communication and sensor technology are few forces that are propagating computing from desktops to outdoor mobile units. • Location management is the key to applications used by mobile units such as mobile resource management applications and location-aware content delivery applications. • Location management is key to answer queries that involve spatio-temporal data and answer issues like location modeling, uncertainity management, and location prediction

26. Future work • Extending the architecture of centralized database to a distributed database. • Handle if uncertain data is submitted from different sensors • Study the implications of network QoS on update policies and query processing. • Integrate with GIS