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Ibm infosphere mgarren

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This is my presentation for CSIS 638 on 08/03/2011

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Ibm infosphere mgarren

  1. 1. IBM InfoSphere Streams for Scalable, Real-Time, Intelligent Transportation Services Matt Garren
  2. 2. Problem● Congestion in urban areas● Too expensive/not enough room to build more highways● Large amount of traffic data from multiple sensors● Processing needed in real-time● Large number of users wanting different views
  3. 3. Infosphere Streams● Structured and Unstructured Data● Scalable●  Data Flow Graph ○ Streaming Data Objects (SDO) ○ Processing Elements (PE) ○  SPADE processing engine
  4. 4. Stream Processing ApplicationDeclarative Engine (SPADE)● Provides a programming language ○ Intermediate ○ Flexible ○ Type-generic operators ○ Extensible using C++/JAVA ○ Broad range of adapters
  5. 5. SPADE: Built in operators● Source● Sink● Functor● Aggregate● Join● Sort● Barrier● Punctor● Split● Delay 
  6. 6. Intelligent Transportation Systems● Stockholm, Sweden●  Functionality ○  Monitor current traffic ○  Compare to historical data ○  Estimate travel times ○  Compute shortest paths● Pilot system used only historical data● Real-time data in the future
  7. 7. Input● 2008 GPS data traces ○ 1500 Taxis (1 reading/60 secs) ○ 400 Trucks (1 reading/30 secs) ○ 170 Million probe points over the year ○  1000 GPS readings/sec peak rate
  8. 8. Application Logic● Steps ○ Obtain, clean, de-noise, match to underlying roads/networks ○ Aggregate to obtain statistics per link and per time interval ○ Compute derived information (shortest times, etc)
  9. 9. Data Flow
  10. 10. GPS Data Issues● Matching to underlying roads● Match to regions instead of links ○ Parking lots
  11. 11. End User Interactions (ITS)● Visualize entire city on Google Earth● Submit specific queries● Web-based visualizations
  12. 12. Performance● Cluster ○  64-bit Intel Xeon quad core processors ○  3GHz clock speed ○ 16 Gb Ram per machine
  13. 13. Performance
  14. 14. Performance
  15. 15. Questions? 

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