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Project II Rule Optimizer for the Atlas Reactivity Engine CNT 5517-5564

Project II Rule Optimizer for the Atlas Reactivity Engine CNT 5517-5564. Dr. Sumi Helal Computer & Information Science & Engineering Department University of Florida, Gainesville, FL 32611 helal@cise.ufl.edu. Manuals & Downloads. The Atlas Class Web Page http://www.icta.ufl.edu/atlas/

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Project II Rule Optimizer for the Atlas Reactivity Engine CNT 5517-5564

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  1. Project IIRule Optimizer for the Atlas Reactivity EngineCNT 5517-5564 Dr. Sumi Helal Computer & Information Science & Engineering Department University of Florida, Gainesville, FL 32611 helal@cise.ufl.edu

  2. Manuals & Downloads • The Atlas Class Web Page • http://www.icta.ufl.edu/atlas/ • The Atlas Reactivity Engine • http://www.cise.ufl.edu/~helal/classes/AtlasRE.zip

  3. Overall Architecture Command Interpreter RE Optimizer Atlas Reactivity Engine Atlas Middleware Atlas Emulator Atlas Emulator

  4. Atlas RE Engine • An Event/Condition/Action paradigm • A programming model for pervasive space • A Command line interface to interact with the engine • View Basic Events & Actions. • Predefine: Events, Conditions and Actions • Define Rules • Accept commands & Provide results/feedback • Engine interacts with the sensors /actuators through the Atlas middleware

  5. EVENTS

  6. Conditions

  7. Rules Actions

  8. Commands

  9. Tokens & Delimiters

  10. Optimization Frameworks • Push/Pull Envelop • Caching • Evaluation Short Cuts • Application Characteristics

  11. Push / Pull Envelop • Configuration of which sensors should participate, and if so, in which mode (push or pull, and if latter, at which frequency). push pure push pull Application Layer Atlas ReactivityEngine pure pull Optimal push/pull envelope …… sensor sensor sensor sensor sensor

  12. Example Caching: Time/Frequency Modifier

  13. Evaluation Short Cuts • Exploit Dominant Events • For a composite event whose sub-events are connected by logic +, some of its sub-events may have significantly higher probability of occurrence than others which makes them a dominant factor in determining the value of the composite event. ( Likewise, for composite events whose sub-events are connected by logic *, sub-events with lower probability of occurrence become dominant )

  14. Project II Summary • Form groups of 4 by no later than Friday Nov 5 noon. • Understand all the components • Study source code of RE Engine • Develop the Optimizer • Think, formalize and create your algorithms • Implement • Assess the success/failure of your Optimizer

  15. Deliverables • You will deliver source code with detailed documentation and about 5-10 pages report describing the following: • Status of your project: what is completed and what not; what works and what not • Your optimization ideas and strategies • Formal description of your optimization algorithm • Your experiment results • Any additional features implemented and the rationale • Conclusions

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