# Store one time only value in influxdb
single_samples = {
- "test_duration" : traffic_gen.scenario_helper.scenario_cfg["runner"]["duration"],
- "test_precision" : self.params["traffic_profile"]["test_precision"],
- "tolerated_loss" : self.params["traffic_profile"]["tolerated_loss"],
- "duration" : duration
+ "test_duration": traffic_gen.scenario_helper.scenario_cfg["runner"]["duration"],
+ "test_precision": self.params["traffic_profile"]["test_precision"],
+ "tolerated_loss": self.params["traffic_profile"]["tolerated_loss"],
+ "duration": duration
}
self.queue.put(single_samples)
self.prev_time = time.time()
self.tolerated_loss,
line_speed)
self.curr_time = time.time()
- diff_time = self.curr_time - self.prev_time
self.prev_time = self.curr_time
if result.success:
self.current_lower = test_value
successful_pkt_loss = result.pkt_loss
samples = result.get_samples(pkt_size, successful_pkt_loss, port_samples)
- samples["TxThroughput"] = samples["TxThroughput"] * 1000 * 1000
# store results with success tag in influxdb
success_samples = {'Success_' + key: value for key, value in samples.items()}
- success_samples["Success_rx_total"] = int(result.rx_total / diff_time)
- success_samples["Success_tx_total"] = int(result.tx_total / diff_time)
- success_samples["Success_can_be_lost"] = int(result.can_be_lost / diff_time)
- success_samples["Success_drop_total"] = int(result.drop_total / diff_time)
+ # Store number of packets based statistics (we already have throughput)
+ success_samples["Success_rx_total"] = int(result.rx_total)
+ success_samples["Success_tx_total"] = int(result.tx_total)
+ success_samples["Success_can_be_lost"] = int(result.can_be_lost)
+ success_samples["Success_drop_total"] = int(result.drop_total)
self.queue.put(success_samples)
# Store Actual throughput for result samples
LOG.debug("Failure... Decreasing upper bound")
self.current_upper = test_value
samples = result.get_samples(pkt_size, successful_pkt_loss, port_samples)
+ # samples contains data such as Latency, Throughput, number of packets
+ # Hence they should not be divided by the time difference
- for k in samples:
- tmp = samples[k]
- if isinstance(tmp, dict):
- for k2 in tmp:
- samples[k][k2] = int(samples[k][k2] / diff_time)
-
- if theor_max_thruput < samples["TxThroughput"]:
- theor_max_thruput = samples['TxThroughput']
+ if theor_max_thruput < samples["RequestedTxThroughput"]:
+ theor_max_thruput = samples['RequestedTxThroughput']
self.queue.put({'theor_max_throughput': theor_max_thruput})
LOG.debug("Collect TG KPIs %s %s", datetime.datetime.now(), samples)
self.queue.put(samples)
result_samples["Result_pktSize"] = pkt_size
- result_samples["Result_theor_max_throughput"] = theor_max_thruput/ (1000 * 1000)
+ result_samples["Result_theor_max_throughput"] = theor_max_thruput
self.queue.put(result_samples)