Support dataplane subnet mask & latency histogram

There is a new parameter in the config_file: dataplane_subnet_mask. This
parameter is added to the dataplane IP addresses and is needed by the
Linux stack to deal with some protocols (e.g. ARP). If not present, the
default value of 24 will be used. In the end, this will make sure that
IP addresses in the rapid.env file will have this mask, e.g. /24
If you use other tools than createrapid.py to create the rapid.env file,
make sure to add the mask.
This commit also introduces a change when exiting: we only copy the
prox.log files from the different prox instances in case we expect a new
prox.log file to be created in these instances.
When using a valid format.yaml file, the tool will now also send the
latency distribution data (histogram) to the URL.
The tool is now also checking the value of bucket_size_exp: it needs to
be 11 or more.

Change-Id: I633cdc64ef687fdb6625be1e7482a5a371f83e93
Signed-off-by: Luc Provoost <luc.provoost@intel.com>

1 files changed, 4 insertions, 2 deletions

diff --git a/VNFs/DPPD-PROX/helper-scripts/rapid/rapid_impairtest.py b/VNFs/DPPD-PROX/helper-scripts/rapid/rapid_impairtest.py
index 74d624d5..8b7f876e 100644
--- a/VNFs/DPPD-PROX/helper-scripts/rapid/rapid_impairtest.py
+++ b/VNFs/DPPD-PROX/helper-scripts/rapid/rapid_impairtest.py
@@ -57,7 +57,7 @@ class ImpairTest(RapidTest):
             sys.stdout.flush()
             time.sleep(1)
             # Get statistics now that the generation is stable and NO ARP messages any more
-            pps_req_tx,pps_tx,pps_sut_tx,pps_rx,lat_avg, lat_perc, lat_perc_max, lat_max, abs_tx, abs_rx, abs_dropped, abs_tx_fail, drop_rate, lat_min, lat_used, r, actual_duration, _ = self.run_iteration(float(self.test['runtime']),flow_number,size,speed)
+            pps_req_tx,pps_tx,pps_sut_tx,pps_rx,lat_avg, lat_perc, lat_perc_max, lat_max, abs_tx, abs_rx, abs_dropped, abs_tx_fail, drop_rate, lat_min, lat_used, r, actual_duration, _,bucket_size, buckets = self.run_iteration(float(self.test['runtime']),flow_number,size,speed)
             # Drop rate is expressed in percentage. lat_used is a ratio (0 to 1). The sum of these 2 should be 100%.
             # If the sum is lower than 95, it means that more than 5% of the latency measurements where dropped for accuracy reasons.
             if (drop_rate + lat_used * 100) < 95:
@@ -78,7 +78,9 @@ class ImpairTest(RapidTest):
                     'PCTLatency': lat_perc,
                     'MaxLatency': lat_max,
                     'PacketsLost': abs_dropped,
-                    'DropRate': drop_rate}
+                    'DropRate': drop_rate,
+                    'bucket_size': bucket_size,
+                    'buckets': buckets}
             self.post_data('rapid_impairtest', variables)
         self.gen_machine.stop_latency_cores()
         return (True)