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EPTS/Dagstuhl Event Processing Grand challenge

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Event Processing Grand Challenge by the Grand Challenge Working Group of the Dagstuhl 2010 Event Processing Seminar. Presented at the 6th EPTS Symposium, March 24, 2011.

Event Processing Grand Challenge by the Grand Challenge Working Group of the Dagstuhl 2010 Event Processing Seminar. Presented at the 6th EPTS Symposium, March 24, 2011.


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  • (In)validate assumptionsTypes of users, actions, rules, queries, eventsCompare, constrast use cases
  • (In)validate assumptionsTypes of users, actions, rules, queries, eventsCompare, constrast use cases
  • Used by private and public agentsManufacturing industries can use the Fabric to instrument production lines and issue warnings as neededEnergy providers can instrument their energy grids to monitor for safety levels and warn people and cut off systems when necessary.Airlines can inform users of changed scheduleHealth organizations can monitor check-in types and numbers, make predictions, and raise alarms of epidemicsSchools can alert parents on local events.
  • Transcript

    • 1. Event Processing Grand ChallengeMarch 24, 2011
      Pedro Bizarro – University of Coimbra
      On behalf of the
      Grand Challenge Working Group of the
      Dagstuhl2010 Event Processing Seminar
    • 2. 2
      GrandChallenge
      Identify a single, though broad challenge that impacts society
      (measures progressof EP community)
    • 3. 3
      GrandChallengeGroupeffortstartedattheDagstuhl 2010 EventProcessingSeminar, May 2010
    • 4. Event Processing Grand Challenge (EPGC)
      Event Processing Fabric
      A decentralized, global, Internet-like infrastructure, built upon widely-accepted open standards
      Applications
      The design, development, deployment, and management of life-changing, or society- changing applications that utilize the Event Processing Fabric
      4
    • 5. Event Processing Grand Challenge (EPGC)
      Requires new cutting-edge R&D results
      To help create a society that proactively exploits opportunities and guards against threats
      5
    • 6. The Event ProcessingFabric
      Infrastructure
      Widely-accepted open standards
      Enables plug-in of…
      …Time-driven or event-driven applications
      “on-the-fly-adaptive”
      6
    • 7. Precise and timely as the Global Positioning System
      Distributed ownership and reach of the World Wide Web
      Community-based, self-curated, constantly-updated of Wikipedia
      Adaptivenature of complex adaptive systems
      7
      The Event ProcessingFabric
    • 8. Designed to be the highway of globalreal-time data, and the enabler of applications for a proactive society.
      8
      The Event ProcessingFabric
    • 9. The Applications – a preview
      Wide-range of applications in scope and complexity
      From detecting incoming earthquakes
      To warnings of schedule changes in daily commutes
      9
    • 10. Challenges of building the Fabric (1)
      Thousands, millions of different sources
      From across the globe
      Filtering, aggregating, transforming, & detecting patterns
      Using real-time and historical data
      10
    • 11. Challenges of building the Fabric (2)
      Manage subscriptions and locations of millions of users
      In a secure and anonymous way
      Across different geographic and administrative domains
      Sending alerts in a timely fashion
      Utilizing the most appropriate channels of communication.
      11
    • 12. Challenges of building the Fabric (3)
      Used by private and public agents
      Manufacturing industries can instrument production lines
      Energy providers can instrument their energy grids
      Airlines can inform users of changed schedule
      Health organizations can monitor check-in types and numbers, make predictions, and raise alarms of epidemics
      Schools can alert parents on local events.
      12
    • 13. Limitations
      May be inappropriate for highly secure applications
      such as military or homeland security.
      May be unsuitable for high-performance applications
      such as real-time stock trading.
      As with the Internet, extremely useful, but not the only way to connect components and systems
      13
    • 14. Implementation ISSUESAND QUALITY ATTRIBUTES
      Event Processing Fabric
      14
    • 15. Privacy
      Ensuring the confidentiality of published information
      15
    • 16. Security
      Protection from hackers that attack the fabric
      16
    • 17. Interoperability
      Plug-and-play standards necessary
      17
    • 18. Provenance
      Should always be possible to trace back a chain of events
      18
    • 19. Elastic performance
      Accommodating variable requirements
      19
    • 20. Energy-efficiency
      Minimizing the energy consumptionof the devices connected to it
      20
    • 21.
      Autonomic computing support
      Non-repudiation
      Authentication
      Anonymity
      Availability
      Quality-of-Service

      21
    • 22. The Applications
      22
    • 23. The Applications
      Extreme-scale disasters
      Eg, hurricanes, earthquakes, or terrorist attacks.
      Data sources managed by
      government agencies (eg, meteorological services)
      companies (eg, monitoring congestion in roads)
      individuals (eg, images or videos from disaster)
      23
    • 24. The Applications
      Critical societal applications
      Eg, smart-grid, or home-health care for the old
      These systems are becoming increasingly event-driven
      24
    • 25. The Applications
      Personal applications
      Eg, finding optimal commute using buses, metro, etc, based on location, availability, schedules
      Social “eventing”
      Partially exists in some social networks (foursquare, Google Latitude, TripIt)
      25
    • 26. Elements of the Challenge
      26
    • 27. Elements of the challenge
      Data acquisition components
      Event processing agents
      Responders or actuators that execute actions
      Communication networks
      Management components
      27
    • 28. Related work – www.Pachube.com
      “Pachubeis a data brokerage platform for the internet of things, managing millions of datapoints per day from thousands of individuals, organisations & companies around the world”
      28
    • 29. Membersandacknowledgements
      ORGANIZATION
      Moderator: Bernhard Seeger
      Facilitator: Ronen Vaisenberg
      Organizors:
      Mani Chandy
      OpherEtzion
      Rainer von Ammon
      PARTICIPANTS
      Stefan Appel , TU Darmstadt
      Pedro Bizarro , University of Coimbra
      Alejandro P. Buchmann , TU Darmstadt
      Sharma Chakravarthy, UT Arlington
      K. Mani Chandy , CalTech - Pasadena
      Kenneth Moody , University of Cambridge
      Tore Risch, Uppsala University, Sweden
      PlamenSimeonov, Berlin
      NenadStojanovic, FZI, Karlsruhe, Germany
      John Sutcliffe-Braithwaite, U Reading
      Richard Tibbetts, Streambase Systems Inc.
      Carlo Zaniolo , Univ. California - Los Angeles
      29
    • 30. Q&A?
      30