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Optimization for Atlas Reactive Engine Dunam Kim, Hokyu Kang, Yangbae Park.

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Presentation on theme: "Optimization for Atlas Reactive Engine Dunam Kim, Hokyu Kang, Yangbae Park."— Presentation transcript:

1 Optimization for Atlas Reactive Engine Dunam Kim, Hokyu Kang, Yangbae Park

2 Table of Contents

3 Introduction The problems of the basic RE –PUSH only –Too much energy consumption Our objectives –To reduce accessing sensors –To fix minor bugs of the basic RE

4 Evaluation Shortcut Finding optimized execution plan of pulling events Steps –Enumerate all possible query-evaluation plans All possible sequences of evaluation of atomic events(terminal events) Equivalent Rules –Compute the cost for the plans Probability of each events –Pick up the plan having the minimum cost

5 Evaluation Shortcut (cont’d) Probability Model –P(event1) = # Occurrence / # Observation –P(~event1) = 1 - P(event1) –P(event1 ∧ event2) = P(event1) * P(event2) Example –P(S1(0,100)) * 1 + P(~S1(0,100)) * P(~S2(0,50)) * 2 + P(~S1(0,100)) * P(S2(0,50)) * 3 –[S1,S2,S3], [S1,S2,S3] –[S2,S1,S3],[S2,S3,S1] –[S3,S1,S2],[S3,S2,S1]

6 Evaluation Shortcut (cont’d) Formal Representation of Cost Calculation –n size of atomic events in forms of S(Number) or S[Number, Number]. n is 3 in the previous example. –Integer x truth value for each sensing event x = 011 for [S1(0,100) = FALSE, S2(0,50) = TRUE, S3(0,50) = TRUE] –M(x) minimum number of evaluation for the case x, x = 100 for [S1(0,100) = TRUE, S2(0,50) = FALSE, S3(0,50) = FALSE] –Pi probability that ith sensing event is true. For [S1(0,100), S2(0,50), S3(0,50)], P2 = P(S2(0,50)) –B(x, i) ith bit value of integer x B(x, i) = (x >> (n-i)) bitwise & 1 –Expected number of evaluation of sensing event is

7 Cache System Atlas Client (Reactive Engine) History Manager Cache Manager Database

8 Cache System (cont’d) Data History Manager –Stores all received data on the database MySQL + JDBC Driver –Provides statistical functions The number of reports in certain period Average time interval Range Standard Deviation Probability of event

9 Cache System (cont’d) Cache Manager –Tracks each sensor’s stability Timestamps Values –Controls PUSH/PULL mode of a sensor Additive Increase Multiplicative Decrease algorithm –Updates out-of-date caches

10 Cache System (cont’d)

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