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/ The Atlas Reactivity Engine http://www.cise.ufl.edu/~helal/classes/AtlasRE.zip

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

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

EVENTS

Conditions

Actions Rules

Commands

Tokens & Delimiters

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

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 pull pure push pure pull sensor Atlas Reactivity Engine …… Optimal push/pull envelope Application Layer

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 )

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

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