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Database Support for Mobile Computing Applications

Database Support for Mobile Computing Applications. R. Bayer Institut für Informatik TU München 3.6.2000 Rudolf/Vorlesungen/DWH-SS2000/DWH-MobileComp. Future Mobile Phones. contain WEB browser have UTMS bandwidth 1.2 Mb/s

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Database Support for Mobile Computing Applications

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  1. Database Support for Mobile Computing Applications R. Bayer Institut für Informatik TU München 3.6.2000 Rudolf/Vorlesungen/DWH-SS2000/DWH-MobileComp R. Bayer, DB for Mobile Comp.

  2. Future Mobile Phones • contain WEB browser • have UTMS bandwidth 1.2 Mb/s • integrated with GPS, i.e. exact position of phone and owner is known  entirely novel applications R. Bayer, DB for Mobile Comp.

  3. Car Traveler on Road • Car knows destination, gas consumption, gas remaining • Questions and services: • reachable cheapest gas station along route? • next BMW repair station? • restaurant with in 100 km serving asparagus or lobster? R. Bayer, DB for Mobile Comp.

  4. Car Traffic Management in Munich Assumptions: 106 cars registered 105 cars traveling Route-DB for preplanned routes, 10 per car, 104 B/route 106 cars * 10 routes/car * 104 B/route = 1011 B = 100 GB Drive-DB 105 cars *1 route/car * 104 B/route = 109 B = 1 GB R. Bayer, DB for Mobile Comp.

  5. Reads and Updates Updates to Drive-DB: 1 update/(car*min) 105 cars*1 update/(car*min) = 105 updates/min ~ 1.700 t/s Reads from Route-DB: travel time = 30 minutes (105 cars/30 min)*1 read/car = 105 reads/(30*60) sec ~ 56 t/s R. Bayer, DB for Mobile Comp.

  6. Route Calculations Initial Routes: compute one optimal route on departure of car based on present traffic situation in Drive-DB 56 routes/s Adaption of Routes: with every update of own position, car wants to know optimal route, in most cases the same as before? 1.700 checks/s R. Bayer, DB for Mobile Comp.

  7. City Tourist • What is this? ( I am standing in front of?) I want to know more, what is the URL? • Where is the next bus or subway station, taxi point, public toilet, please guide me to it (load down part of city map with direct route inserted or text: ) • Where is medium priced fish restaurant within 500 m? Show it, make a reservation. • I need an antihistamine, where is the next open pharmacy? R. Bayer, DB for Mobile Comp.

  8. Air Traveler • T is approaching airport Munich by car, server knows flight F and car or subway. • „Proceed to parking P1, level 2, space 437“ • „Mr. Bayer, you are checked into flight LH451 to Cologne, leaving from gate A17, boarding time is 7:45, go towards gate in 7 minutes • On return: parking ticket paid automatically, gate opens, when car approaches. R. Bayer, DB for Mobile Comp.

  9. Truck Management • What is position of trucks near Cologne with at least 1 ton loading capacity and slack of 1 hour in their delivery schedule? • Show me planned travel route and stops of truck 327 R. Bayer, DB for Mobile Comp.

  10. Shoppers: Info pull or push? • On entering Kaufhof, select WEB server • Information pull: • guide me to the perfume dept. • bestsellers in detective stories? • Information push (to close shoppers): • McDonald coming up 120 meters to right • H&M has bikini special • WOM: Madonna‘s new single just arrived R. Bayer, DB for Mobile Comp.

  11. Nightlife • Which friends are in Schwabing now? • Who is DJ at P1? • Live video shot with soundtrack from P1. ODODO, Kunstpark Ost • „My position is ...“ • „Anybody close to share taxi to ...? R. Bayer, DB for Mobile Comp.

  12. Sales Representative • On approaching customer C: download the relevant marketing materials, sales and delivery data for C, combined with DWH. • Show homepage and picture of person I meet • Did C have any reclamations recently? • Any significant changes in buying pattern of C recently? • Question: B2B applications ??? R. Bayer, DB for Mobile Comp.

  13. Taxi Service • Please pick me up to go to Kentvale apartments • Taxi server finds optimal taxi: „Mr. Bayer, please stay where you are, a blue Comfort Taxi with plate SHA-488 368C will pick you up in approximately 3 minutes R. Bayer, DB for Mobile Comp.

  14. Emergency Service • Pushing the panic button calls police or ambulance • mobile phone transmits position and medical data of owner, voice of attacker R. Bayer, DB for Mobile Comp.

  15. Hotel Guest • Theatre in walking distance showing movie with Meryl Streep starting around 20 h? Show map with route. • reserve and pay ticket • nearby bar serving Heineken? • ... R. Bayer, DB for Mobile Comp.

  16. The Database Problem • Types of Subjects: • Fixed location • constant state: buildings, statues, paintings in museums, with a lot of additional information • variable state: restaurants with seats • Mobile • constant state, if subject refuses to disclose state • variable state R. Bayer, DB for Mobile Comp.

  17. Attributes and Dimensions • 1. Location: 2 or 3 dimensions • 2. Time: for tractable subjects like trucks • 3. Classification of Subjects: hierarchies and MHC ~ subject ID, e.g. • automotive (cars, gas stations, parking, repair stations) • eating • shopping • arts 4 to 5 dimensions • 4. State: movie playing now, number of free seats, ... probably modeled like features of GfK R. Bayer, DB for Mobile Comp.

  18. Database Size (Mengengerüst) • 1. Assumptions about Size • 107 mobile subjects in Bavaria * 1000 B = 10 GB • 105 fixed subjects, which are constant, but with 105 Bytes for image = 1010 B = 10 GB • 105 variable subjects * 10 KB = 1 GB • 11 GB with high update frequency ! R. Bayer, DB for Mobile Comp.

  19. 2. Assumptions about Updates and Queries • A person is moving at most 10% of the time, i.e. 2.5 hours per day? • Update rate 1 per minute for variable subjects • 11*105 variable subjects * 1 update per minute • = 11*105 /60 U/s ~ 20.000 updates /s •  achievable with parallel DBMS ! R. Bayer, DB for Mobile Comp.

  20. Crosscheck for Airport Munich 20 flights /h* 300 passengers/flight = 6.000 passengers / h ~ DB size 60 MB 10 updates or queries per passenger? 60.000 t/h = 1000 t/m ~ 20 t/s  1 Server handles problem, second server for redundancy and mirroring DB! R. Bayer, DB for Mobile Comp.

  21. Hurdles • Data Acquisition • Mobile subjects: Telekom companies • Fixed constant subjects: 105 * 10 DM = 1 million DM • Variable subjects: free data via advertising • Business Model • network providers • content providers • SW and technology providers R. Bayer, DB for Mobile Comp.

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