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.

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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.
  • EPTS/Dagstuhl Event Processing Grand challenge

    1. 1. Event Processing Grand ChallengeMarch 24, 2011<br />Pedro Bizarro – University of Coimbra<br />On behalf of the<br />Grand Challenge Working Group of the<br />Dagstuhl2010 Event Processing Seminar<br />
    2. 2. 2<br />GrandChallenge<br />Identify a single, though broad challenge that impacts society<br />(measures progressof EP community)<br />
    3. 3. 3<br />GrandChallengeGroupeffortstartedattheDagstuhl 2010 EventProcessingSeminar, May 2010<br />
    4. 4. Event Processing Grand Challenge (EPGC)<br />Event Processing Fabric<br />A decentralized, global, Internet-like infrastructure, built upon widely-accepted open standards<br />Applications<br />The design, development, deployment, and management of life-changing, or society- changing applications that utilize the Event Processing Fabric<br />4<br />
    5. 5. Event Processing Grand Challenge (EPGC)<br />Requires new cutting-edge R&D results<br />To help create a society that proactively exploits opportunities and guards against threats<br />5<br />
    6. 6. The Event ProcessingFabric<br />Infrastructure<br />Widely-accepted open standards<br />Enables plug-in of…<br />…Time-driven or event-driven applications<br />“on-the-fly-adaptive”<br />6<br />
    7. 7. Precise and timely as the Global Positioning System<br />Distributed ownership and reach of the World Wide Web<br />Community-based, self-curated, constantly-updated of Wikipedia<br />Adaptivenature of complex adaptive systems<br />7<br />The Event ProcessingFabric<br />
    8. 8. Designed to be the highway of globalreal-time data, and the enabler of applications for a proactive society.<br />8<br />The Event ProcessingFabric<br />
    9. 9. The Applications – a preview<br />Wide-range of applications in scope and complexity<br />From detecting incoming earthquakes<br />To warnings of schedule changes in daily commutes<br />9<br />
    10. 10. Challenges of building the Fabric (1)<br />Thousands, millions of different sources<br />From across the globe<br />Filtering, aggregating, transforming, & detecting patterns<br />Using real-time and historical data<br />10<br />
    11. 11. Challenges of building the Fabric (2)<br />Manage subscriptions and locations of millions of users<br />In a secure and anonymous way<br />Across different geographic and administrative domains<br />Sending alerts in a timely fashion<br />Utilizing the most appropriate channels of communication.<br />11<br />
    12. 12. Challenges of building the Fabric (3)<br />Used by private and public agents<br />Manufacturing industries can instrument production lines <br />Energy providers can instrument their energy grids<br />Airlines can inform users of changed schedule<br />Health organizations can monitor check-in types and numbers, make predictions, and raise alarms of epidemics<br />Schools can alert parents on local events.<br />12<br />
    13. 13. Limitations<br />May be inappropriate for highly secure applications<br />such as military or homeland security.<br />May be unsuitable for high-performance applications<br />such as real-time stock trading.<br />As with the Internet, extremely useful, but not the only way to connect components and systems<br />13<br />
    14. 14. Implementation ISSUESAND QUALITY ATTRIBUTES<br />Event Processing Fabric<br />14<br />
    15. 15. Privacy<br />Ensuring the confidentiality of published information<br />15<br />
    16. 16. Security<br />Protection from hackers that attack the fabric<br />16<br />
    17. 17. Interoperability<br />Plug-and-play standards necessary<br />17<br />
    18. 18. Provenance<br />Should always be possible to trace back a chain of events<br />18<br />
    19. 19. Elastic performance<br />Accommodating variable requirements<br />19<br />
    20. 20. Energy-efficiency<br />Minimizing the energy consumptionof the devices connected to it<br />20<br />
    21. 21. …<br />Autonomic computing support<br />Non-repudiation<br />Authentication<br />Anonymity<br />Availability<br />Quality-of-Service<br />…<br />21<br />
    22. 22. The Applications<br />22<br />
    23. 23. The Applications<br />Extreme-scale disasters<br />Eg, hurricanes, earthquakes, or terrorist attacks.<br />Data sources managed by<br /> government agencies (eg, meteorological services)<br />companies (eg, monitoring congestion in roads)<br /> individuals (eg, images or videos from disaster)<br />23<br />
    24. 24. The Applications<br />Critical societal applications<br />Eg, smart-grid, or home-health care for the old<br />These systems are becoming increasingly event-driven<br />24<br />
    25. 25. The Applications<br />Personal applications<br />Eg, finding optimal commute using buses, metro, etc, based on location, availability, schedules<br />Social “eventing”<br />Partially exists in some social networks (foursquare, Google Latitude, TripIt)<br />25<br />
    26. 26. Elements of the Challenge<br />26<br />
    27. 27. Elements of the challenge<br />Data acquisition components<br />Event processing agents<br />Responders or actuators that execute actions<br />Communication networks<br />Management components<br />27<br />
    28. 28. Related work – www.Pachube.com<br />“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”<br />28<br />
    29. 29. Membersandacknowledgements<br />ORGANIZATION<br />Moderator: Bernhard Seeger<br />Facilitator: Ronen Vaisenberg<br />Organizors:<br />Mani Chandy<br />OpherEtzion<br />Rainer von Ammon <br />PARTICIPANTS<br />Stefan Appel , TU Darmstadt <br />Pedro Bizarro , University of Coimbra <br />Alejandro P. Buchmann , TU Darmstadt <br />Sharma Chakravarthy, UT Arlington <br />K. Mani Chandy , CalTech - Pasadena <br />Kenneth Moody , University of Cambridge <br />Tore Risch, Uppsala University, Sweden <br />PlamenSimeonov, Berlin <br />NenadStojanovic, FZI, Karlsruhe, Germany <br />John Sutcliffe-Braithwaite, U Reading <br />Richard Tibbetts, Streambase Systems Inc. <br />Carlo Zaniolo , Univ. California - Los Angeles <br />29<br />
    30. 30. Q&A?<br />30<br />