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The "ZooKeeper/GSoCFailureDetector" page has been changed by AbmarBarros.
http://wiki.apache.org/hadoop/ZooKeeper/GSoCFailureDetector?action=diff&rev1=13&rev2=14

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   * Made Chen's alpha parameter configurable, and not a quarter of the timeout
  
  ==== 16/Aug/10 ====
+  * Refactored the way default values are passed to failure detectors
   * Finished experimentation and written experiment report
  
  == Experimentation ==
@@ -114, +115 @@

  
   * '''First batch of tests''':
    * 1 client and 1 server connected by an transcontinental link (Campina 
Grande-Brazil / Newark-USA)
+   * client sending async operations to server 
    * client running during 10 min (average)
    * link = 1MBps, 250ms
    * timeout = 5000ms
    * replication = 5
    * used the following failure detectors:
     * Fixed heartbeat
-    * Chen (alpha = 0, 500, 1000, 2000)
+    * Chen (alpha = [0, 1000])
-    * Bertier (moderationstep = 0, 250, 500, 1000)
+    * Bertier (moderationstep = [0, 1000])
-    * Phi accrual (threshold = .5, 2, 4, 8)
+    * Phi accrual (threshold = [.5, 8]; minwindowsize=50)
  
   * '''Second batch of tests''':
    * 200 clients and 1 server connected in an emulated WAN in emulab
+   * client sending async operations to server
    * clients running during 10 min (average)
    * link = 2MBps, 250ms, message loss probability of 0.1 
    * timeout = 5000ms
@@ -137, +140 @@

  
  ==== Results ====
   * '''First batch of tests''':
+    || Method || Average detection time || Stddev of the detection time || 
False suspicions ||
+    || Fixedhb || 4731.8 || 299.6985 || 0/5 ||
+    || Chen (alpha=0) || - || - || 5/5 ||
+    || Chen (alpha=1000) || 1810.8 || 347.3632 || 0/5 ||
+    || Bertier (moderation step = 0) || 784.6 || 483.5642 || 0/5 ||
+    || Bertier (moderation step = 1000) || 1228.2 || 804.5773 || 0/5 ||
+    || Phi accrual (threshold = 0.5) || 714.6667 || 521.9745 || 2/5 ||
+    || Phi accrual(threshold = 8.) || 1574.75 || 602.7799 || 1/5 ||
  
   * '''Second batch of tests''':
     * In these tests, Fixed heartbeat and Bertier's strategies did not present 
any false suspicion. With the given alpha, Chen's presented 13/200 false 
suspicions, and the Phi-accrual, with the windowminsize parameter equals to 0, 
have made false suspicion on all the clients. Below, we show the average 
detection time of all methods but the Phi-accrual: 
- 
-    * {{http://www2.lsd.ufcg.edu.br/~abmar/zk/fd-comparison.png}}
+    {{http://www2.lsd.ufcg.edu.br/~abmar/zk/fd-comparison.png}}
- 
-    * The Phi-accrual method must be evaluated again with a better 
windowminsize parameter and in a scenario with larger duration, so the warm-up 
period is not considered.   
+    * The Phi-accrual method must be evaluated again with a better 
windowminsize parameter in a scenario with a greater duration, so the warm-up 
period is not considered.   
  
  ==== Concluding remarks ====
  
  As expected, we noticed that the fixed heartbeat method works well when we 
run ZooKeeper in a controlled environment, where the network behavior is 
expected. In this cases we can tune the fixed timeout after some network 
analysis. However, in scenarios where we have a changing network behavior, such 
in a WAN, the adaptive methods can be a good pick. Below, there is an overview 
of each failure detector:
   * '''Fixed heartbeat''': In average, with default parameters, the fixed 
heartbeat strategy had the highest detection time, but with no false suspicion. 
However, if the timeout is not well defined, failures may take a long time to 
be detected, or false suspicion rate would be increased. As said before, this 
strategy is useful when there is a controlled environment, in which the network 
can be characterized.
   * '''Chen''': This strategy requires some assumption over the network, once 
the administrator needs to define the alpha parameter - the safety margin for 
the estimation. However, with default parameters, Chen et al. method performed 
well in a WAN deploy. It managed to decrease the average detection time with a 
low false suspicion rate.
-  * '''Bertier''': Bertier et al initially proposed a failure detector that 
requires no assumption over the network but a single moderation step to be 
added to the estimation when the monitored is at a suspected state when a 
heartbeat is received. With these experiments, we have come to same conclusion 
as Hayashibara et al: that this failure detector is very sensitive to message 
loss and fluctuation in the arrival times of heartbeats. In this sense, the 
moderation step turned out to be an important parameter for this failure 
detector. With a moderation step of 1000, Bertier's failure detector reached a 
higher average detection time than the Chen's method, but lower than the fixed 
hearbeat strategy. It is worth to mention that Bertier’s failure detector was 
primarily designed to be used over local area networks (LANs), that is, 
environments wherein messages are seldom lost.
+  * '''Bertier''': Bertier et al initially proposed a failure detector that 
requires no assumption over the network but a single moderation step to be 
added to the estimation when the monitored is at a suspected state when a 
heartbeat is received. With these experiments, we have come to same conclusion 
as Hayashibara et al: that this failure detector is very sensitive to message 
loss and fluctuation in the arrival times of heartbeats. In this sense, the 
moderation step turned out to be an important parameter for this failure 
detector. With a moderation step of 1000, Bertier's failure detector reached a 
higher average detection time than the Chen's method, but lower than the fixed 
hearbeat strategy. It is worth to mention that Bertier’s failure detector was 
primarily designed to be used over local area networks (LANs), that is, 
environments wherein messages are seldom lost. As we could see, with a single 
client Berties's method stands out with a low detection time and no false 
suspicions, even with the moderation step equals to 0.
   * '''Phi-accrual''': The phi-accrual is the method that requires less 
information about the network behavior. However it relies on a large sampling 
window to perform a good estimation. As we could see, in the experiments that a 
minimum window size was not used, there was a huge number of false suspicions. 
The effect of the threshold is only noticeable when there is some deviation 
from the average. The phi-accrual stands out in a WAN with unknown behavior, 
but it is mandatory to set a good (high) initial timeout value for the warm-up 
period of the method, which happens while the minimum window size is not 
reached.
    
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