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Location Information Management and Moving Object Databases “Moving Object Databases: Issues and Solutions” Ouri, Bo, Sam and Liqin 1 Contents Introduction Challenges of Location Information Management – – – – Location Modeling Uncertainty Management Distributed/Mobile Environment Location Prediction 2 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 3 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. 4 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. 5 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 6 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 ) 7 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 8 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. 9 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 10 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 11 updated 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 12 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 13 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 14 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)) 15 Other Temporal Query Predicates Future queries – – – – – UNTIL NextTime Eventually_within( c, g ) Eventually_after( c, g ) Always_for( c, g ) 16 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) ) 17 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 18 Indexing Contd.. Value-time space representation 19 Uncertainty Management The location of a moving object is inherently imprecise regardless the update policy. To accommodate uncertainty, a new subattribute to the dynamic attribute named L.uncertainty should be added. “May” and “must” semantics should be incorporated in the query language 20 Implementation Details Architecture 21 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 22 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. 23 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. 24 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 25 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 26