Fix the search algorithm

[samplevnf.git] / VNFs / DPPD-PROX / helper-scripts / rapid / rapid_test.py

diff --git a/VNFs/DPPD-PROX/helper-scripts/rapid/rapid_test.py b/VNFs/DPPD-PROX/helper-scripts/rapid/rapid_test.py
index 2466d89..6badfb4 100644 (file)
--- a/VNFs/DPPD-PROX/helper-scripts/rapid/rapid_test.py
+++ b/VNFs/DPPD-PROX/helper-scripts/rapid/rapid_test.py
@@ -1,7 +1,7 @@
 #!/usr/bin/python
 
 ##
 #!/usr/bin/python
 
 ##

-## Copyright (c) 2010-2020 Intel Corporation
+## Copyright (c) 2020 Intel Corporation

 ##
 ## Licensed under the Apache License, Version 2.0 (the "License");
 ## you may not use this file except in compliance with the License.
 ##
 ## Licensed under the Apache License, Version 2.0 (the "License");
 ## you may not use this file except in compliance with the License.


@@ -17,34 +17,66 @@
 ## limitations under the License.
 ##
 
 ## limitations under the License.
 ##
 

+import yaml
+import requests

 import time
 import time

+import os
+import copy

 from past.utils import old_div
 from rapid_log import RapidLog
 from rapid_log import bcolors
 from past.utils import old_div
 from rapid_log import RapidLog
 from rapid_log import bcolors

+inf = float("inf")
+from datetime import datetime as dt
+
+_CURR_DIR = os.path.dirname(os.path.realpath(__file__))

 
 class RapidTest(object):
     """
 
 class RapidTest(object):
     """

-    Class to manage the flowsizetesting
+    Class to manage the testing

     """
     """

+    def __init__(self, test_param, runtime, testname, environment_file ):
+        self.test = test_param
+        self.test['runtime'] = runtime
+        self.test['testname'] = testname
+        self.test['environment_file'] = environment_file
+        if 'maxr' not in self.test.keys():
+            self.test['maxr'] = 1
+        if 'maxz' not in self.test.keys():
+            self.test['maxz'] = inf
+        with open(os.path.join(_CURR_DIR,'format.yaml')) as f:
+            self.data_format = yaml.load(f, Loader=yaml.FullLoader)
+

     @staticmethod
     def get_percentageof10Gbps(pps_speed,size):
         # speed is given in pps, returning % of 10Gb/s
     @staticmethod
     def get_percentageof10Gbps(pps_speed,size):
         # speed is given in pps, returning % of 10Gb/s

-        return (pps_speed / 1000000.0 * 0.08 * (size+28))
+        # 12 bytes is the inter packet gap 
+        # pre-amble is 7 bytes
+        # SFD (start of frame delimiter) is 1 byte
+        # Total of 20 bytes overhead per packet
+        return (pps_speed / 1000000.0 * 0.08 * (size+20))

 
     @staticmethod
     def get_pps(speed,size):
         # speed is given in % of 10Gb/s, returning Mpps
 
     @staticmethod
     def get_pps(speed,size):
         # speed is given in % of 10Gb/s, returning Mpps

-        return (speed * 100.0 / (8*(size+28)))
+        # 12 bytes is the inter packet gap 
+        # pre-amble is 7 bytes
+        # SFD (start of frame delimiter) is 1 byte
+        # Total of 20 bytes overhead per packet
+        return (speed * 100.0 / (8*(size+20)))

 
     @staticmethod
     def get_speed(packet_speed,size):
         # return speed in Gb/s
 
     @staticmethod
     def get_speed(packet_speed,size):
         # return speed in Gb/s

-        return (packet_speed / 1000.0 * (8*(size+28)))
+        # 12 bytes is the inter packet gap 
+        # pre-amble is 7 bytes
+        # SFD (start of frame delimiter) is 1 byte
+        # Total of 20 bytes overhead per packet
+        return (packet_speed / 1000.0 * (8*(size+20)))

 
     @staticmethod
     def set_background_flows(background_machines, number_of_flows):
         for machine in background_machines:
 
     @staticmethod
     def set_background_flows(background_machines, number_of_flows):
         for machine in background_machines:

-            machine.set_flows(number_of_flows)
+            _ = machine.set_flows(number_of_flows)

 
     @staticmethod
     def set_background_speed(background_machines, speed):
 
     @staticmethod
     def set_background_speed(background_machines, speed):


@@ -68,122 +100,205 @@ class RapidTest(object):
             machine.stop()
 
     @staticmethod
             machine.stop()
 
     @staticmethod

-    def report_result(flow_number, size, speed, pps_req_tx, pps_tx, pps_sut_tx,
-        pps_rx, lat_avg, lat_perc, lat_perc_max, lat_max, tx, rx, tot_drop,
-        elapsed_time,speed_prefix='', lat_avg_prefix='', lat_perc_prefix='',
-        lat_max_prefix='', abs_drop_rate_prefix='', drop_rate_prefix=''):
+    def parse_data_format_dict(data_format, variables):
+        for k, v in data_format.items():
+            if type(v) is dict:
+                RapidTest.parse_data_format_dict(v, variables)
+            else:
+                if v in variables.keys():
+                    data_format[k] = variables[v]
+
+    def post_data(self, variables):
+        test_type = type(self).__name__
+        var = copy.deepcopy(self.data_format)
+        self.parse_data_format_dict(var, variables)
+        if var.keys() >= {'URL', test_type, 'Format'}:
+            URL=''
+            for value in var['URL'].values():
+                URL = URL + value
+            HEADERS = {'X-Requested-With': 'Python requests', 'Content-type': 'application/rapid'}
+            if var['Format'] == 'PushGateway':
+                data = "\n".join("{} {}".format(k, v) for k, v in var[test_type].items()) + "\n"
+                response = requests.post(url=URL, data=data,headers=HEADERS)
+            elif var['Format'] == 'Xtesting':
+                data = var[test_type]
+                response = requests.post(url=URL, json=data)
+            if (response.status_code >= 300):
+                RapidLog.info('Cannot send metrics to {}'.format(URL))
+                RapidLog.info(data)
+        return (var[test_type])
+
+    @staticmethod
+    def report_result(flow_number, size, data, prefix):

         if flow_number < 0:
             flow_number_str = '| ({:>4}) |'.format(abs(flow_number))
         else:
             flow_number_str = '|{:>7} |'.format(flow_number)
         if flow_number < 0:
             flow_number_str = '| ({:>4}) |'.format(abs(flow_number))
         else:
             flow_number_str = '|{:>7} |'.format(flow_number)

-        if pps_req_tx is None:
+        if data['pps_req_tx'] is None:

             pps_req_tx_str = '{0: >14}'.format('   NA     |')
         else:
             pps_req_tx_str = '{0: >14}'.format('   NA     |')
         else:

-            pps_req_tx_str = '{:>7.3f} Mpps |'.format(pps_req_tx)
-        if pps_tx is None:
+            pps_req_tx_str = '{:>7.3f} Mpps |'.format(data['pps_req_tx'])
+        if data['pps_tx'] is None:

             pps_tx_str = '{0: >14}'.format('   NA     |')
         else:
             pps_tx_str = '{0: >14}'.format('   NA     |')
         else:

-            pps_tx_str = '{:>7.3f} Mpps |'.format(pps_tx) 
-        if pps_sut_tx is None:
+            pps_tx_str = '{:>7.3f} Mpps |'.format(data['pps_tx']) 
+        if data['pps_sut_tx'] is None:

             pps_sut_tx_str = '{0: >14}'.format('   NA     |')
         else:
             pps_sut_tx_str = '{0: >14}'.format('   NA     |')
         else:

-            pps_sut_tx_str = '{:>7.3f} Mpps |'.format(pps_sut_tx)
-        if pps_rx is None:
+            pps_sut_tx_str = '{:>7.3f} Mpps |'.format(data['pps_sut_tx'])
+        if data['pps_rx'] is None:

             pps_rx_str = '{0: >25}'.format('NA        |')
         else:
             pps_rx_str = '{0: >25}'.format('NA        |')
         else:

-            pps_rx_str = bcolors.OKBLUE + '{:>4.1f} Gb/s |{:7.3f} Mpps {}|'.format(RapidTest.get_speed(pps_rx,size),pps_rx,bcolors.ENDC)
-        if tot_drop is None:
+            pps_rx_str = bcolors.OKBLUE + '{:>4.1f} Gb/s |{:7.3f} Mpps {}|'.format(
+                    RapidTest.get_speed(data['pps_rx'],size),data['pps_rx'],bcolors.ENDC)
+        if data['abs_dropped'] is None:

             tot_drop_str = ' |       NA  | '
         else:
             tot_drop_str = ' |       NA  | '
         else:

-            tot_drop_str = ' | {:>9.0f} | '.format(tot_drop)
-        if lat_perc is None:
-            lat_perc_str = ' |{:^10.10}|'.format('NA')
-        elif lat_perc_max == True:
-            lat_perc_str = '|>{}{:>5.0f} us{} |'.format(lat_perc_prefix,float(lat_perc), bcolors.ENDC) 
+            tot_drop_str = ' | {:>9.0f} | '.format(data['abs_dropped'])
+        if data['lat_perc'] is None:
+            lat_perc_str = '|{:^10.10}|'.format('NA')
+        elif data['lat_perc_max'] == True:
+            lat_perc_str = '|>{}{:>5.0f} us{} |'.format(prefix['lat_perc'],
+                    float(data['lat_perc']), bcolors.ENDC) 

         else:
         else:

-            lat_perc_str = '| {}{:>5.0f} us{} |'.format(lat_perc_prefix,float(lat_perc), bcolors.ENDC) 
-        if elapsed_time is None:
+            lat_perc_str = '| {}{:>5.0f} us{} |'.format(prefix['lat_perc'],
+                    float(data['lat_perc']), bcolors.ENDC) 
+        if data['actual_duration'] is None:

             elapsed_time_str = ' NA |'
         else:
             elapsed_time_str = ' NA |'
         else:

-            elapsed_time_str = '{:>3.0f} |'.format(elapsed_time)
-        return(flow_number_str + '{:>5.1f}'.format(speed) + '% '+speed_prefix +'{:>6.3f}'.format(RapidTest.get_pps(speed,size)) + ' Mpps|'+ pps_req_tx_str + pps_tx_str + bcolors.ENDC + pps_sut_tx_str + pps_rx_str +lat_avg_prefix+ ' {:>6.0f}'.format(lat_avg)+' us'+lat_perc_str+lat_max_prefix+'{:>6.0f}'.format(lat_max)+' us | ' + '{:>9.0f}'.format(tx) + ' | {:>9.0f}'.format(rx) + ' | '+ abs_drop_rate_prefix+ '{:>9.0f}'.format(tx-rx) + tot_drop_str +drop_rate_prefix+ '{:>5.2f}'.format(old_div(float(tx-rx),tx))  +bcolors.ENDC+' |' + elapsed_time_str)
-            
+            elapsed_time_str = '{:>3.0f} |'.format(data['actual_duration'])
+        if data['mis_ordered'] is None:
+            mis_ordered_str = '    NA   '
+        else:
+            mis_ordered_str = '{:>9.0f} '.format(data['mis_ordered'])
+        return(flow_number_str + '{:>5.1f}'.format(data['speed']) + '% ' + prefix['speed']
+                + '{:>6.3f}'.format(RapidTest.get_pps(data['speed'],size)) + ' Mpps|' +
+                pps_req_tx_str + pps_tx_str + bcolors.ENDC + pps_sut_tx_str +
+                pps_rx_str + prefix['lat_avg'] + ' {:>6.0f}'.format(data['lat_avg']) +
+                ' us' + lat_perc_str +prefix['lat_max']+'{:>6.0f}'.format(data['lat_max'])
+                + ' us | ' + '{:>9.0f}'.format(data['abs_tx']) + ' | {:>9.0f}'.format(data['abs_rx']) +
+                ' | '+ prefix['abs_drop_rate']+ '{:>9.0f}'.format(data['abs_tx']-data['abs_rx']) +
+                tot_drop_str + prefix['drop_rate'] +
+                '{:>5.2f}'.format(100*old_div(float(data['abs_tx']-data['abs_rx']),data['abs_tx'])) + ' |' + 
+                prefix['mis_ordered'] + mis_ordered_str + bcolors.ENDC +
+                ' |' + elapsed_time_str)
+

     def run_iteration(self, requested_duration, flow_number, size, speed):
         BUCKET_SIZE_EXP = self.gen_machine.bucket_size_exp
     def run_iteration(self, requested_duration, flow_number, size, speed):
         BUCKET_SIZE_EXP = self.gen_machine.bucket_size_exp

+        sleep_time = self.test['sleep_time']

         LAT_PERCENTILE = self.test['lat_percentile']
         LAT_PERCENTILE = self.test['lat_percentile']

-        r = 0;
-        sleep_time = 2
-        while (r < self.test['maxr']):
+        iteration_data= {}
+        time_loop_data= {}
+        iteration_data['r'] = 0;
+
+        while (iteration_data['r'] < self.test['maxr']):
+            self.gen_machine.start_latency_cores()

             time.sleep(sleep_time)
             # Sleep_time is needed to be able to do accurate measurements to check for packet loss. We need to make this time large enough so that we do not take the first measurement while some packets from the previous tests migth still be in flight
             t1_rx, t1_non_dp_rx, t1_tx, t1_non_dp_tx, t1_drop, t1_tx_fail, t1_tsc, abs_tsc_hz = self.gen_machine.core_stats()
             t1_dp_rx = t1_rx - t1_non_dp_rx
             t1_dp_tx = t1_tx - t1_non_dp_tx
             time.sleep(sleep_time)
             # Sleep_time is needed to be able to do accurate measurements to check for packet loss. We need to make this time large enough so that we do not take the first measurement while some packets from the previous tests migth still be in flight
             t1_rx, t1_non_dp_rx, t1_tx, t1_non_dp_tx, t1_drop, t1_tx_fail, t1_tsc, abs_tsc_hz = self.gen_machine.core_stats()
             t1_dp_rx = t1_rx - t1_non_dp_rx
             t1_dp_tx = t1_tx - t1_non_dp_tx

+            self.gen_machine.set_generator_speed(0)

             self.gen_machine.start_gen_cores()
             self.gen_machine.start_gen_cores()

+            self.set_background_speed(self.background_machines, 0)
+            self.start_background_traffic(self.background_machines)
+            if 'ramp_step' in self.test.keys():
+                ramp_speed = self.test['ramp_step']
+            else:
+                ramp_speed = speed
+            while ramp_speed < speed:
+                self.gen_machine.set_generator_speed(ramp_speed)
+                self.set_background_speed(self.background_machines, ramp_speed)
+                time.sleep(2)
+                ramp_speed = ramp_speed + self.test['ramp_step']
+            self.gen_machine.set_generator_speed(speed)
+            self.set_background_speed(self.background_machines, speed)
+            iteration_data['speed'] = speed
+            time_loop_data['speed'] = speed

             time.sleep(2) ## Needs to be 2 seconds since this 1 sec is the time that PROX uses to refresh the stats. Note that this can be changed in PROX!! Don't do it.
             time.sleep(2) ## Needs to be 2 seconds since this 1 sec is the time that PROX uses to refresh the stats. Note that this can be changed in PROX!! Don't do it.

+            start_bg_gen_stats = []
+            for bg_gen_machine in self.background_machines:
+                bg_rx, bg_non_dp_rx, bg_tx, bg_non_dp_tx, _, _, bg_tsc, _ = bg_gen_machine.core_stats()
+                bg_gen_stat = {
+                        "bg_dp_rx" : bg_rx - bg_non_dp_rx,
+                        "bg_dp_tx" : bg_tx - bg_non_dp_tx,
+                        "bg_tsc"   : bg_tsc
+                        }
+                start_bg_gen_stats.append(dict(bg_gen_stat))

             if self.sut_machine!= None:
                 t2_sut_rx, t2_sut_non_dp_rx, t2_sut_tx, t2_sut_non_dp_tx, t2_sut_drop, t2_sut_tx_fail, t2_sut_tsc, sut_tsc_hz = self.sut_machine.core_stats()
             t2_rx, t2_non_dp_rx, t2_tx, t2_non_dp_tx, t2_drop, t2_tx_fail, t2_tsc, tsc_hz = self.gen_machine.core_stats()
             tx = t2_tx - t1_tx
             if self.sut_machine!= None:
                 t2_sut_rx, t2_sut_non_dp_rx, t2_sut_tx, t2_sut_non_dp_tx, t2_sut_drop, t2_sut_tx_fail, t2_sut_tsc, sut_tsc_hz = self.sut_machine.core_stats()
             t2_rx, t2_non_dp_rx, t2_tx, t2_non_dp_tx, t2_drop, t2_tx_fail, t2_tsc, tsc_hz = self.gen_machine.core_stats()
             tx = t2_tx - t1_tx

-            dp_tx =  tx - (t2_non_dp_tx - t1_non_dp_tx )
-            dp_rx =  t2_rx - t1_rx - (t2_non_dp_rx - t1_non_dp_rx) 
-            tot_dp_drop = dp_tx - dp_rx
+            iteration_data['abs_tx'] =  tx - (t2_non_dp_tx - t1_non_dp_tx )
+            iteration_data['abs_rx'] =  t2_rx - t1_rx - (t2_non_dp_rx - t1_non_dp_rx) 
+            iteration_data['abs_dropped'] = iteration_data['abs_tx'] - iteration_data['abs_rx']

             if tx == 0:
                 RapidLog.critical("TX = 0. Test interrupted since no packet has been sent.")
             if tx == 0:
                 RapidLog.critical("TX = 0. Test interrupted since no packet has been sent.")

-            if dp_tx == 0:
+            if iteration_data['abs_tx'] == 0:

                 RapidLog.critical("Only non-dataplane packets (e.g. ARP) sent. Test interrupted since no packet has been sent.")
             # Ask PROX to calibrate the bucket size once we have a PROX function to do this.
             # Measure latency statistics per second
                 RapidLog.critical("Only non-dataplane packets (e.g. ARP) sent. Test interrupted since no packet has been sent.")
             # Ask PROX to calibrate the bucket size once we have a PROX function to do this.
             # Measure latency statistics per second

-            lat_min, lat_max, lat_avg, used_avg, t2_lat_tsc, lat_hz, buckets = self.gen_machine.lat_stats()
-            lat_samples = sum(buckets)
+            iteration_data.update(self.gen_machine.lat_stats())
+            t2_lat_tsc = iteration_data['lat_tsc']

             sample_count = 0
             sample_count = 0

-            for sample_percentile, bucket in enumerate(buckets,start=1):
+            for sample_percentile, bucket in enumerate(iteration_data['buckets'],start=1):

                 sample_count += bucket
                 sample_count += bucket

-                if sample_count > (lat_samples * LAT_PERCENTILE):
+                if sample_count > sum(iteration_data['buckets']) * LAT_PERCENTILE:

                     break
                     break

-            percentile_max = (sample_percentile == len(buckets))
-            sample_percentile = sample_percentile *  float(2 ** BUCKET_SIZE_EXP) / (old_div(float(lat_hz),float(10**6)))
+            iteration_data['lat_perc_max'] = (sample_percentile == len(iteration_data['buckets']))
+            iteration_data['bucket_size'] = float(2 ** BUCKET_SIZE_EXP) / (old_div(float(iteration_data['lat_hz']),float(10**6)))
+            time_loop_data['bucket_size'] = iteration_data['bucket_size']
+            iteration_data['lat_perc'] = sample_percentile * iteration_data['bucket_size'] 

             if self.test['test'] == 'fixed_rate':
             if self.test['test'] == 'fixed_rate':

-                RapidLog.info(self.report_result(flow_number,size,speed,None,None,None,None,lat_avg,sample_percentile,percentile_max,lat_max, dp_tx, dp_rx , None, None))
+                iteration_data['pps_req_tx'] = None
+                iteration_data['pps_tx'] = None
+                iteration_data['pps_sut_tx'] = None
+                iteration_data['pps_rx'] = None
+                iteration_data['lat_perc'] = None
+                iteration_data['actual_duration'] = None
+                iteration_prefix = {'speed' : '',
+                        'lat_avg' : '',
+                        'lat_perc' : '',
+                        'lat_max' : '',
+                        'abs_drop_rate' : '',
+                        'drop_rate' : ''}
+                RapidLog.info(self.report_result(flow_number, size,
+                    iteration_data, iteration_prefix ))

             tot_rx = tot_non_dp_rx = tot_tx = tot_non_dp_tx = tot_drop = 0
             tot_rx = tot_non_dp_rx = tot_tx = tot_non_dp_tx = tot_drop = 0

-            lat_avg = used_avg = 0
-            buckets_total = [0] * 128
-            tot_lat_samples = 0
+            iteration_data['lat_avg'] = iteration_data['lat_used'] = 0

             tot_lat_measurement_duration = float(0)
             tot_lat_measurement_duration = float(0)

-            tot_core_measurement_duration = float(0)
+            iteration_data['actual_duration'] = float(0)

             tot_sut_core_measurement_duration = float(0)
             tot_sut_rx = tot_sut_non_dp_rx = tot_sut_tx = tot_sut_non_dp_tx = tot_sut_drop = tot_sut_tx_fail = tot_sut_tsc = 0
             lat_avail = core_avail = sut_avail = False
             tot_sut_core_measurement_duration = float(0)
             tot_sut_rx = tot_sut_non_dp_rx = tot_sut_tx = tot_sut_non_dp_tx = tot_sut_drop = tot_sut_tx_fail = tot_sut_tsc = 0
             lat_avail = core_avail = sut_avail = False

-            while (tot_core_measurement_duration - float(requested_duration) <= 0.1) or (tot_lat_measurement_duration - float(requested_duration) <= 0.1):
+            while (iteration_data['actual_duration'] - float(requested_duration) <= 0.1) or (tot_lat_measurement_duration - float(requested_duration) <= 0.1):

                 time.sleep(0.5)
                 time.sleep(0.5)

-                lat_min_sample, lat_max_sample, lat_avg_sample, used_sample, t3_lat_tsc, lat_hz, buckets = self.gen_machine.lat_stats()
+                time_loop_data.update(self.gen_machine.lat_stats())

                 # Get statistics after some execution time
                 # Get statistics after some execution time

-                if t3_lat_tsc != t2_lat_tsc:
-                    single_lat_measurement_duration = (t3_lat_tsc - t2_lat_tsc) * 1.0 / lat_hz  # time difference between the 2 measurements, expressed in seconds.
+                if time_loop_data['lat_tsc'] != t2_lat_tsc:
+                    single_lat_measurement_duration = (time_loop_data['lat_tsc'] - t2_lat_tsc) * 1.0 / time_loop_data['lat_hz']  # time difference between the 2 measurements, expressed in seconds.

                     # A second has passed in between to lat_stats requests. Hence we need to process the results
                     tot_lat_measurement_duration = tot_lat_measurement_duration + single_lat_measurement_duration
                     # A second has passed in between to lat_stats requests. Hence we need to process the results
                     tot_lat_measurement_duration = tot_lat_measurement_duration + single_lat_measurement_duration

-                    if lat_min > lat_min_sample:
-                        lat_min = lat_min_sample
-                    if lat_max < lat_max_sample:
-                        lat_max = lat_max_sample
-                    lat_avg = lat_avg + lat_avg_sample * single_lat_measurement_duration # Sometimes, There is more than 1 second between 2 lat_stats. Hence we will take the latest measurement
-                    used_avg = used_avg + used_sample * single_lat_measurement_duration  # and give it more weigth.
-                    lat_samples = sum(buckets)
-                    tot_lat_samples += lat_samples
+                    if iteration_data['lat_min'] > time_loop_data['lat_min']:
+                        iteration_data['lat_min'] = time_loop_data['lat_min']
+                    if iteration_data['lat_max'] < time_loop_data['lat_max']:
+                        iteration_data['lat_max'] = time_loop_data['lat_max']
+                    iteration_data['lat_avg'] = iteration_data['lat_avg'] + time_loop_data['lat_avg'] * single_lat_measurement_duration # Sometimes, There is more than 1 second between 2 lat_stats. Hence we will take the latest measurement
+                    iteration_data['lat_used'] = iteration_data['lat_used'] + time_loop_data['lat_used'] * single_lat_measurement_duration # and give it more weigth.

                     sample_count = 0
                     sample_count = 0

-                    for sample_percentile, bucket in enumerate(buckets,start=1):
+                    for sample_percentile, bucket in enumerate(time_loop_data['buckets'],start=1):

                         sample_count += bucket
                         sample_count += bucket

-                        if sample_count > lat_samples * LAT_PERCENTILE:
+                        if sample_count > sum(time_loop_data['buckets']) * LAT_PERCENTILE:

                             break
                             break

-                    percentile_max = (sample_percentile == len(buckets))
-                    sample_percentile = sample_percentile *  float(2 ** BUCKET_SIZE_EXP) / (old_div(float(lat_hz),float(10**6)))
-                    buckets_total = [buckets_total[i] + buckets[i] for i in range(len(buckets_total))] 
-                    t2_lat_tsc = t3_lat_tsc
+                    time_loop_data['lat_perc_max'] = (sample_percentile == len(time_loop_data['buckets']))
+                    time_loop_data['lat_perc'] = sample_percentile *  iteration_data['bucket_size']
+                    iteration_data['buckets'] = [iteration_data['buckets'][i] + time_loop_data['buckets'][i] for i in range(len(iteration_data['buckets']))]
+                    t2_lat_tsc = time_loop_data['lat_tsc'] 

                     lat_avail = True
                 t3_rx, t3_non_dp_rx, t3_tx, t3_non_dp_tx, t3_drop, t3_tx_fail, t3_tsc, tsc_hz = self.gen_machine.core_stats()
                 if t3_tsc != t2_tsc:
                     lat_avail = True
                 t3_rx, t3_non_dp_rx, t3_tx, t3_non_dp_tx, t3_drop, t3_tx_fail, t3_tsc, tsc_hz = self.gen_machine.core_stats()
                 if t3_tsc != t2_tsc:

-                    single_core_measurement_duration = (t3_tsc - t2_tsc) * 1.0 / tsc_hz  # time difference between the 2 measurements, expressed in seconds.
-                    tot_core_measurement_duration = tot_core_measurement_duration + single_core_measurement_duration
+                    time_loop_data['actual_duration'] = (t3_tsc - t2_tsc) * 1.0 / tsc_hz  # time difference between the 2 measurements, expressed in seconds.
+                    iteration_data['actual_duration'] = iteration_data['actual_duration'] + time_loop_data['actual_duration']

                     delta_rx = t3_rx - t2_rx
                     tot_rx += delta_rx
                     delta_non_dp_rx = t3_non_dp_rx - t2_non_dp_rx
                     delta_rx = t3_rx - t2_rx
                     tot_rx += delta_rx
                     delta_non_dp_rx = t3_non_dp_rx - t2_non_dp_rx


@@ -194,8 +309,8 @@ class RapidTest(object):
                     tot_non_dp_tx += delta_non_dp_tx
                     delta_dp_tx = delta_tx -delta_non_dp_tx
                     delta_dp_rx = delta_rx -delta_non_dp_rx
                     tot_non_dp_tx += delta_non_dp_tx
                     delta_dp_tx = delta_tx -delta_non_dp_tx
                     delta_dp_rx = delta_rx -delta_non_dp_rx

-                    delta_dp_drop = delta_dp_tx - delta_dp_rx
-                    tot_dp_drop += delta_dp_drop
+                    time_loop_data['abs_dropped'] = delta_dp_tx - delta_dp_rx
+                    iteration_data['abs_dropped'] += time_loop_data['abs_dropped']

                     delta_drop = t3_drop - t2_drop
                     tot_drop += delta_drop
                     t2_rx, t2_non_dp_rx, t2_tx, t2_non_dp_tx, t2_drop, t2_tx_fail, t2_tsc = t3_rx, t3_non_dp_rx, t3_tx, t3_non_dp_tx, t3_drop, t3_tx_fail, t3_tsc
                     delta_drop = t3_drop - t2_drop
                     tot_drop += delta_drop
                     t2_rx, t2_non_dp_rx, t2_tx, t2_non_dp_tx, t2_drop, t2_tx_fail, t2_tsc = t3_rx, t3_non_dp_rx, t3_tx, t3_non_dp_tx, t3_drop, t3_tx_fail, t3_tsc


@@ -203,7 +318,7 @@ class RapidTest(object):
                 if self.sut_machine!=None:
                     t3_sut_rx, t3_sut_non_dp_rx, t3_sut_tx, t3_sut_non_dp_tx, t3_sut_drop, t3_sut_tx_fail, t3_sut_tsc, sut_tsc_hz = self.sut_machine.core_stats()
                     if t3_sut_tsc != t2_sut_tsc:
                 if self.sut_machine!=None:
                     t3_sut_rx, t3_sut_non_dp_rx, t3_sut_tx, t3_sut_non_dp_tx, t3_sut_drop, t3_sut_tx_fail, t3_sut_tsc, sut_tsc_hz = self.sut_machine.core_stats()
                     if t3_sut_tsc != t2_sut_tsc:

-                        single_sut_core_measurement_duration = (t3_sut_tsc - t2_sut_tsc) * 1.0 / tsc_hz  # time difference between the 2 measurements, expressed in seconds.
+                        single_sut_core_measurement_duration = (t3_sut_tsc - t2_sut_tsc) * 1.0 / sut_tsc_hz  # time difference between the 2 measurements, expressed in seconds.

                         tot_sut_core_measurement_duration = tot_sut_core_measurement_duration + single_sut_core_measurement_duration
                         tot_sut_rx += t3_sut_rx - t2_sut_rx
                         tot_sut_non_dp_rx += t3_sut_non_dp_rx - t2_sut_non_dp_rx
                         tot_sut_core_measurement_duration = tot_sut_core_measurement_duration + single_sut_core_measurement_duration
                         tot_sut_rx += t3_sut_rx - t2_sut_rx
                         tot_sut_non_dp_rx += t3_sut_non_dp_rx - t2_sut_non_dp_rx


@@ -216,76 +331,109 @@ class RapidTest(object):
                 if self.test['test'] == 'fixed_rate':
                     if lat_avail == core_avail == True:
                         lat_avail = core_avail = False
                 if self.test['test'] == 'fixed_rate':
                     if lat_avail == core_avail == True:
                         lat_avail = core_avail = False

-                        pps_req_tx = (delta_tx + delta_drop - delta_rx)/single_core_measurement_duration/1000000
-                        pps_tx = delta_tx/single_core_measurement_duration/1000000
+                        time_loop_data['pps_req_tx'] = (delta_tx + delta_drop - delta_rx)/time_loop_data['actual_duration']/1000000
+                        time_loop_data['pps_tx'] = delta_tx/time_loop_data['actual_duration']/1000000

                         if self.sut_machine != None and sut_avail:
                         if self.sut_machine != None and sut_avail:

-                            pps_sut_tx = delta_sut_tx/single_sut_core_measurement_duration/1000000
+                            time_loop_data['pps_sut_tx'] = delta_sut_tx/single_sut_core_measurement_duration/1000000

                             sut_avail = False
                         else:
                             sut_avail = False
                         else:

-                            pps_sut_tx = None
-                        pps_rx = delta_rx/single_core_measurement_duration/1000000
-                        RapidLog.info(self.report_result(flow_number, size,
-                            speed, pps_req_tx, pps_tx, pps_sut_tx, pps_rx,
-                            lat_avg_sample, sample_percentile, percentile_max,
-                            lat_max_sample, delta_dp_tx, delta_dp_rx,
-                            tot_dp_drop, single_core_measurement_duration))
+                            time_loop_data['pps_sut_tx'] = None
+                        time_loop_data['pps_rx'] = delta_rx/time_loop_data['actual_duration']/1000000
+                        time_loop_data['abs_tx'] = delta_dp_tx
+                        time_loop_data['abs_rx'] = delta_dp_rx
+                        time_loop_prefix = {'speed' : '',
+                                'lat_avg' : '',
+                                'lat_perc' : '',
+                                'lat_max' : '',
+                                'abs_drop_rate' : '',
+                                'drop_rate' : ''}
+                        RapidLog.info(self.report_result(flow_number, size, time_loop_data,
+                            time_loop_prefix))
+                        time_loop_data['test'] = self.test['testname']
+                        time_loop_data['environment_file'] = self.test['environment_file']
+                        time_loop_data['Flows'] = flow_number
+                        time_loop_data['Size'] = size
+                        time_loop_data['RequestedSpeed'] = RapidTest.get_pps(speed, size)
+                        _ = self.post_data(time_loop_data)
+            end_bg_gen_stats = []
+            for bg_gen_machine in self.background_machines:
+                bg_rx, bg_non_dp_rx, bg_tx, bg_non_dp_tx, _, _, bg_tsc, bg_hz = bg_gen_machine.core_stats()
+                bg_gen_stat = {"bg_dp_rx" : bg_rx - bg_non_dp_rx,
+                        "bg_dp_tx" : bg_tx - bg_non_dp_tx,
+                        "bg_tsc"   : bg_tsc,
+                        "bg_hz"    : bg_hz
+                        }
+                end_bg_gen_stats.append(dict(bg_gen_stat))
+            self.stop_background_traffic(self.background_machines)
+            i = 0
+            bg_rates =[]
+            while i < len(end_bg_gen_stats):
+                bg_rates.append(0.000001*(end_bg_gen_stats[i]['bg_dp_rx'] -
+                    start_bg_gen_stats[i]['bg_dp_rx']) / ((end_bg_gen_stats[i]['bg_tsc'] -
+                    start_bg_gen_stats[i]['bg_tsc']) * 1.0 / end_bg_gen_stats[i]['bg_hz']))
+                i += 1
+            if len(bg_rates):
+                iteration_data['avg_bg_rate'] = sum(bg_rates) / len(bg_rates)
+                RapidLog.debug('Average Background traffic rate: {:>7.3f} Mpps'.format(iteration_data['avg_bg_rate']))
+            else:
+                iteration_data['avg_bg_rate'] = None

             #Stop generating
             self.gen_machine.stop_gen_cores()
             #Stop generating
             self.gen_machine.stop_gen_cores()

-            r += 1
-            lat_avg = old_div(lat_avg, float(tot_lat_measurement_duration))
-            used_avg = old_div(used_avg, float(tot_lat_measurement_duration))
+            time.sleep(3.5)
+            self.gen_machine.stop_latency_cores()
+            iteration_data['r'] += 1
+            iteration_data['lat_avg'] = old_div(iteration_data['lat_avg'], float(tot_lat_measurement_duration))
+            iteration_data['lat_used'] = old_div(iteration_data['lat_used'], float(tot_lat_measurement_duration))

             t4_tsc = t2_tsc
             while t4_tsc == t2_tsc:
                 t4_rx, t4_non_dp_rx, t4_tx, t4_non_dp_tx, t4_drop, t4_tx_fail, t4_tsc, abs_tsc_hz = self.gen_machine.core_stats()
             if self.test['test'] == 'fixed_rate':
             t4_tsc = t2_tsc
             while t4_tsc == t2_tsc:
                 t4_rx, t4_non_dp_rx, t4_tx, t4_non_dp_tx, t4_drop, t4_tx_fail, t4_tsc, abs_tsc_hz = self.gen_machine.core_stats()
             if self.test['test'] == 'fixed_rate':

-                t4_lat_tsc = t2_lat_tsc
-                while t4_lat_tsc == t2_lat_tsc:
-                    lat_min_sample, lat_max_sample, lat_avg_sample, used_sample, t4_lat_tsc, lat_hz, buckets = self.gen_machine.lat_stats()
+                iteration_data['lat_tsc'] = t2_lat_tsc
+                while iteration_data['lat_tsc'] == t2_lat_tsc:
+                    iteration_data.update(self.gen_machine.lat_stats())

                 sample_count = 0
                 sample_count = 0

-                lat_samples = sum(buckets)
-                for percentile, bucket in enumerate(buckets,start=1):
+                for percentile, bucket in enumerate(iteration_data['buckets'],start=1):

                     sample_count += bucket
                     sample_count += bucket

-                    if sample_count > lat_samples * LAT_PERCENTILE:
+                    if sample_count > sum(iteration_data['buckets']) * LAT_PERCENTILE:

                         break
                         break

-                percentile_max = (percentile == len(buckets))
-                percentile = percentile *  float(2 ** BUCKET_SIZE_EXP) / (old_div(float(lat_hz),float(10**6)))
-                lat_max = lat_max_sample
-                lat_avg = lat_avg_sample
+                iteration_data['lat_perc_max'] = (percentile == len(iteration_data['buckets']))
+                iteration_data['lat_perc'] = percentile *  iteration_data['bucket_size']

                 delta_rx = t4_rx - t2_rx
                 delta_non_dp_rx = t4_non_dp_rx - t2_non_dp_rx
                 delta_tx = t4_tx - t2_tx
                 delta_non_dp_tx = t4_non_dp_tx - t2_non_dp_tx
                 delta_dp_tx = delta_tx -delta_non_dp_tx
                 delta_dp_rx = delta_rx -delta_non_dp_rx
                 delta_rx = t4_rx - t2_rx
                 delta_non_dp_rx = t4_non_dp_rx - t2_non_dp_rx
                 delta_tx = t4_tx - t2_tx
                 delta_non_dp_tx = t4_non_dp_tx - t2_non_dp_tx
                 delta_dp_tx = delta_tx -delta_non_dp_tx
                 delta_dp_rx = delta_rx -delta_non_dp_rx

-                dp_tx = delta_dp_tx
-                dp_rx = delta_dp_rx
-                tot_dp_drop += delta_dp_tx - delta_dp_rx
-                pps_req_tx = None
-                pps_tx = None
-                pps_sut_tx = None
-                pps_rx = None
-                drop_rate = 100.0*(dp_tx-dp_rx)/dp_tx
-                tot_core_measurement_duration = None
+                iteration_data['abs_tx'] = delta_dp_tx
+                iteration_data['abs_rx'] = delta_dp_rx
+                iteration_data['abs_dropped'] += delta_dp_tx - delta_dp_rx
+                iteration_data['pps_req_tx'] = None
+                iteration_data['pps_tx'] = None
+                iteration_data['pps_sut_tx'] = None
+                iteration_data['drop_rate'] = 100.0*(iteration_data['abs_tx']-iteration_data['abs_rx'])/iteration_data['abs_tx']
+                iteration_data['actual_duration'] = None

                 break ## Not really needed since the while loop will stop when evaluating the value of r
             else:
                 sample_count = 0
                 break ## Not really needed since the while loop will stop when evaluating the value of r
             else:
                 sample_count = 0

-                for percentile, bucket in enumerate(buckets_total,start=1):
+                for percentile, bucket in enumerate(iteration_data['buckets'],start=1):

                     sample_count += bucket
                     sample_count += bucket

-                    if sample_count > tot_lat_samples * LAT_PERCENTILE:
+                    if sample_count > sum(iteration_data['buckets']) * LAT_PERCENTILE:

                         break
                         break

-                percentile_max = (percentile == len(buckets_total))
-                percentile = percentile *  float(2 ** BUCKET_SIZE_EXP) / (old_div(float(lat_hz),float(10**6)))
-                pps_req_tx = (tot_tx + tot_drop - tot_rx)/tot_core_measurement_duration/1000000.0 # tot_drop is all packets dropped by all tasks. This includes packets dropped at the generator task + packets dropped by the nop task. In steady state, this equals to the number of packets received by this VM
-                pps_tx = tot_tx/tot_core_measurement_duration/1000000.0 # tot_tx is all generated packets actually accepted by the interface
-                pps_rx = tot_rx/tot_core_measurement_duration/1000000.0 # tot_rx is all packets received by the nop task = all packets received in the gen VM
+                iteration_data['lat_perc_max'] = (percentile == len(iteration_data['buckets']))
+                iteration_data['lat_perc'] = percentile *  iteration_data['bucket_size']
+                iteration_data['pps_req_tx'] = (tot_tx + tot_drop - tot_rx)/iteration_data['actual_duration']/1000000.0 # tot_drop is all packets dropped by all tasks. This includes packets dropped at the generator task + packets dropped by the nop task. In steady state, this equals to the number of packets received by this VM
+                iteration_data['pps_tx'] = tot_tx/iteration_data['actual_duration']/1000000.0 # tot_tx is all generated packets actually accepted by the interface
+                iteration_data['pps_rx'] = tot_rx/iteration_data['actual_duration']/1000000.0 # tot_rx is all packets received by the nop task = all packets received in the gen VM

                 if self.sut_machine != None and sut_avail:
                 if self.sut_machine != None and sut_avail:

-                    pps_sut_tx = tot_sut_tx / tot_sut_core_measurement_duration / 1000000.0
+                    iteration_data['pps_sut_tx'] = tot_sut_tx / tot_sut_core_measurement_duration / 1000000.0

                 else:
                 else:

-                    pps_sut_tx = None
-                dp_tx = (t4_tx - t1_tx) - (t4_non_dp_tx - t1_non_dp_tx)
-                dp_rx = (t4_rx - t1_rx) - (t4_non_dp_rx - t1_non_dp_rx)
-                tot_dp_drop = dp_tx - dp_rx
-                drop_rate = 100.0*tot_dp_drop/dp_tx
-                if ((drop_rate < self.test['drop_rate_threshold']) or (tot_dp_drop == self.test['drop_rate_threshold'] ==0) or (tot_dp_drop > self.test['maxz'])):
+                    iteration_data['pps_sut_tx'] = None
+                iteration_data['abs_tx'] = (t4_tx - t1_tx) - (t4_non_dp_tx - t1_non_dp_tx)
+                iteration_data['abs_rx'] = (t4_rx - t1_rx) - (t4_non_dp_rx - t1_non_dp_rx)
+                iteration_data['abs_dropped'] = iteration_data['abs_tx'] - iteration_data['abs_rx']
+                iteration_data['drop_rate'] = 100.0*iteration_data['abs_dropped']/iteration_data['abs_tx']
+                if ((iteration_data['drop_rate'] < self.test['drop_rate_threshold']) or (iteration_data['abs_dropped'] == self.test['drop_rate_threshold'] ==0) or (iteration_data['abs_dropped'] > self.test['maxz'])):

                     break
                     break

-        return(pps_req_tx,pps_tx,pps_sut_tx,pps_rx,lat_avg,percentile,percentile_max,lat_max,dp_tx,dp_rx,tot_dp_drop,(t4_tx_fail - t1_tx_fail),drop_rate,lat_min,used_avg,r,tot_core_measurement_duration)
+            self.gen_machine.stop_latency_cores()
+        iteration_data['abs_tx_fail'] = t4_tx_fail - t1_tx_fail
+        return (iteration_data)