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Managing Location Information for Billions of Gizmos on the Move

Managing Location Information for Billions of Gizmos on the Move – What’s in it for the Database Folks. Ralf Hartmut Güting Fernuniversität Hagen, Germany. Panel: Managing Location Information. My background: spatial database systems

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Managing Location Information for Billions of Gizmos on the Move

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  1. Managing Location Information for Billions of Gizmos on the Move – What’s in it for the Database Folks Ralf Hartmut Güting Fernuniversität Hagen, Germany

  2. Panel: Managing Location Information ... • My background: • spatial database systems • some work on models and query languages for moving objects • DBMS technology should be extended as follows: • 1. Describing moving objects (gizmos) • Extending data models so that moving objects can be described (new data types, in my view). • Extending query languages so that all (well, many) kinds of questions about moving objects and their relationships to static spatial objects can be formulated.

  3. 1. Describing Moving Objects • Static spatial object: • position: point • Moving object: • position: f: time point • distance(mo, obj) f: time real • inside(mo, obj) f: time bool • Continuous functions must be handled in DBMS models and languages. t y x

  4. 1. Describing Moving Objects • Specific challenges: • Integrate proposals dealing with moving objects in the past with those describing them at present/future. • Integrate modeling and querying of networks with modeling of movement (objects move in networks in many cases). • Model aggregation of moving objects. • Given observations of (lots of) cars on highways, compute traffic jams. • Integrate position uncertainty into modeling and querying. May come from observations or from descriptions. • “On monday morning, I arrived in Heidelberg. I took a walk downtown. From about 11am to 2pm I visited the castle. I then took a train to Munich ...”

  5. 2. Location Dependent Queries • A person or device on the move issues a query, e.g. • “Finde the five Italian restaurants closest from here.” • In principle a normal spatial query (substitute current position for here), but ... • Indexing might continuously adapt to current position. For example, restaurants always ordered by distance. • For a PDA with limited memory, a cache might be continuously updated to contain the current environment information. • Query depending on moving location: • “Notify me as soon as we get within 5 kms of a gas station.” • Can also be viewed as a continuous query: • “Find gas stations within 5 kms from now on” – stop query n • Result can also be dynamic due to movement of queried objects: • “How many police cars are in the city center?” from now on. “Notify me whenever their number changes by more than 3.”

  6. 3. More ... • Implementation issues: • Indexing of current / past movement • Algorithms for operations on spatio-temporal (= moving object) data types • Mapping of abstract, continuous models into finitely representable, discrete models • Problems of scale: • Handle position updates for two million cars moving around in Germany, reporting their position every ten seconds. • Distributed, localized management of information • Allow uniform, integrated access to local, space-related information residing on many heterogeneous servers.

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