Changes between Initial Version and Version 1 of PerformanceData

Timestamp:

Sep 4, 2012 11:32:20 AM (12 years ago)

Author:

Mei

Comment:

--

PerformanceData

@@ +1 @@
+Performance data
+  
+  We have gathered performance data of two types of ABAC scenario.
+The first is the daisychaining of a large answer proof from a 
+similarly sized ruleset.  The second is the searching of a proof 
+from a noisy ruleset. 
+
+==> daisychain <==
+
+  Many cascading Likes-rules and their matching principal credentials are
+generated:
+
+  John0.likes <-John0
+  John1.likes <-John0
+  John2.likes <-John1
+  John3.likes <-John2
+  ...
+  JohnMax.likes <-JohnMax-1  
+
+  Following graph shows the the time needed to load both attribute
+credentials and principal certificates ((2*Max)+2) into the YAP prolog 
+db. The Y axis is the total time in milliseconds. The X axis is the 
+number of credentials that are in the YAP backend db.
+
+XXX
+
+
+  A valid query in the form of JohnMax.likes <-?-John0 is issued multiple
+times. The first query's time is collected and then subsequent 10 queries
+are collected and an average is taken.  Next graph shows these lines. The
+X axis is the query time in microseconds and the Y axis is number of 
+credentials in the YAP backend db.
+  
+XXX
+
+  An invalid query in the form of John0.likes <-?-JohnMax is issued 
+multiple times. The first query's time is collected and then subsequent 
+10 queries are collected and an average is taken.  Next graph shows these 
+lines. The X axis is the query time in microseconds and the Y axis is 
+number of credentials in the YAP backend db.
+
+XXX
+
+
+==> haystack <==
+
+  The core credential setup is borrowed from the
+Ralphs' fruitprice and shopper's eating preference RT2 example,
+ 
+  Mary.what2eat <- Ralphs.fruitprice(P:[.. 2.00])
+  Bob.what2eat <- Ralphs.fruitprice(P:[1.00 .. 5.00])
+  Ralphs.fruitprice(1.50) <- 'apple'
+  Ralphs.fruitprice(1.50) <- 'kiwi'
+  Ralphs.fruitprice(2.50) <- 'black rasberry'
+  Ralphs.fruitprice(0.50) <- 'navel orange'
+
+  Noises are introduced by adding the rules about bananas
+and Johns.
+
+  Ralphs.fruitprice(1.00) <- 'banana1'
+  Ralphs.fruitprice(2.00) <- 'banana2'
+  ..
+  Ralphs.fruitprice(Max.00) <- bananaMax
+
+  John1.what2eat <- Ralphs.fruitprice(P:[1.00 .. 5.00])
+  John2.what2eat <- Ralphs.fruitprice(P:[1.00 .. 5.00])
+  ..
+  JohnMAX.what2eat <- Ralphs.fruitprice(P:[1.00 .. 5.00])
+
+  Following graph shows the the time needed to load both attribute
+credentials and principal certificates ((3*Max)+9) into the YAP prolog 
+db. The Y axis is the total time in milliseconds. The X axis is the 
+number of credentials that are in the YAP backend db.
+
+XXX
+
+  A valid query, Mary.what2eat<-?-'navel orange', is issued multiple 
+times. The returning answer proof is, 
+     Mary.what2eat <- pRalphs.fruitprice(P:[..2.000000])
+     Ralphs.fruitprice(0.50) <- 'navel orange'.  
+The first query's time is collected and the subsequent 20 queries 
+are collected and averaged. Next graph shows these lines. The X 
+axis is the query time in 
+microseconds and the Y axis is number of credentials in the YAP 
+backend db.
+  
+XXX
+
+  An invalid query in the form of Bob.what2eat<-?-'navel orange'
+is issued multiple times. The first query's time is collected and
+then subsequent 20 queries are collected and averaged.  Next graph 
+shows these lines. The X axis is the query time in microseconds 
+and the Y axis is number of credentialsi in the YAP backend db.
+
+XXX
+