Project II Rule Optimizer for the Atlas Reactivity Engine CNT 5517-5564 Dr. Sumi Helal Computer &...

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Project IIRule Optimizer for the Atlas

Reactivity Engine

CNT 5517-5564

Dr. Sumi HelalComputer & Information Science & Engineering Department

University of Florida, Gainesville, FL 32611helal@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

Atlas MiddlewareAtlas Middleware

RE Optimizer

Atlas Emulator

Atlas Emulator

Atlas Reactivity Engine

Atlas Reactivity Engine

Atlas Emulator

Atlas Emulator

CommandInterpreterCommandInterpreter

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

Rules

Actions

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

pullpure pushpure push

pure pullpure pull

sensor

Atlas Reactivity Engine

…… sensorsensorsensor

Optimal push/pull envelope

Application Layer

sensor

Example Caching: Time/Frequency Modifier

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