1 # Copyright (c) 2016-2017 Intel Corporation
3 # Licensed under the Apache License, Version 2.0 (the "License");
4 # you may not use this file except in compliance with the License.
5 # You may obtain a copy of the License at
7 # http://www.apache.org/licenses/LICENSE-2.0
9 # Unless required by applicable law or agreed to in writing, software
10 # distributed under the License is distributed on an "AS IS" BASIS,
11 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
12 # See the License for the specific language governing permissions and
13 # limitations under the License.
14 """ Fixed traffic profile definitions """
16 from __future__ import absolute_import
22 from yardstick.network_services.traffic_profile.prox_profile import ProxProfile
23 from yardstick.network_services import constants
24 from yardstick.common import constants as overall_constants
26 LOG = logging.getLogger(__name__)
29 class ProxBinSearchProfile(ProxProfile):
31 This profile adds a single stream at the beginning of the traffic session
34 def __init__(self, tp_config):
35 super(ProxBinSearchProfile, self).__init__(tp_config)
36 self.current_lower = self.lower_bound
37 self.current_upper = self.upper_bound
41 return self.current_upper - self.current_lower
45 return (self.current_lower + self.current_upper) / 2
47 def bounds_iterator(self, logger=None):
48 self.current_lower = self.lower_bound
49 self.current_upper = self.upper_bound
51 test_value = self.current_upper
52 while abs(self.delta) >= self.precision:
54 logger.debug("New interval [%s, %s), precision: %d", self.current_lower,
55 self.current_upper, self.step_value)
56 logger.info("Testing with value %s", test_value)
59 test_value = self.mid_point
61 def run_test_with_pkt_size(self, traffic_gen, pkt_size, duration):
62 """Run the test for a single packet size.
64 :param traffic_gen: traffic generator instance
65 :type traffic_gen: TrafficGen
66 :param pkt_size: The packet size to test with.
68 :param duration: The duration for each try.
73 LOG.info("Testing with packet size %d", pkt_size)
75 # Binary search assumes the lower value of the interval is
76 # successful and the upper value is a failure.
77 # The first value that is tested, is the maximum value. If that
78 # succeeds, no more searching is needed. If it fails, a regular
79 # binary search is performed.
81 # The test_value used for the first iteration of binary search
82 # is adjusted so that the delta between this test_value and the
83 # upper bound is a power-of-2 multiple of precision. In the
84 # optimistic situation where this first test_value results in a
85 # success, the binary search will complete on an integer multiple
86 # of the precision, rather than on a fraction of it.
88 theor_max_thruput = actual_max_thruput = 0
97 # Store one time only value in influxdb
99 "test_duration": traffic_gen.scenario_helper.scenario_cfg["runner"]["duration"],
100 "test_precision": self.params["traffic_profile"]["test_precision"],
101 "tolerated_loss": self.params["traffic_profile"]["tolerated_loss"],
104 self.queue.put(single_samples)
105 self.prev_time = time.time()
107 # throughput and packet loss from the most recent successful test
108 successful_pkt_loss = 0.0
109 line_speed = traffic_gen.scenario_helper.all_options.get(
110 "interface_speed_gbps", constants.NIC_GBPS_DEFAULT) * constants.ONE_GIGABIT_IN_BITS
112 ok_retry = traffic_gen.scenario_helper.scenario_cfg["runner"].get("confirmation", 0)
113 for test_value in self.bounds_iterator(LOG):
118 rate_samples["MAX_Rate"] = self.current_upper
119 rate_samples["MIN_Rate"] = self.current_lower
120 rate_samples["Test_Rate"] = test_value
121 self.queue.put(rate_samples, True, overall_constants.QUEUE_PUT_TIMEOUT)
122 LOG.info("Checking MAX %s MIN %s TEST %s",
123 self.current_upper, self.lower_bound, test_value)
124 while (pos_retry <= ok_retry) and (neg_retry <= ok_retry):
126 total_retry = total_retry + 1
127 result, port_samples = self._profile_helper.run_test(pkt_size, duration,
131 if (total_retry > (ok_retry * 3)) and (ok_retry is not 0):
132 LOG.info("Failure.!! .. RETRY EXCEEDED ... decrease lower bound")
134 successful_pkt_loss = result.pkt_loss
135 samples = result.get_samples(pkt_size, successful_pkt_loss, port_samples)
137 self.current_upper = test_value
138 neg_retry = total_retry
140 if (pos_retry < ok_retry) and (ok_retry is not 0):
142 LOG.info("Success! ... confirm retry")
144 successful_pkt_loss = result.pkt_loss
145 samples = result.get_samples(pkt_size, successful_pkt_loss, port_samples)
148 LOG.info("Success! Increasing lower bound")
149 self.current_lower = test_value
151 successful_pkt_loss = result.pkt_loss
152 samples = result.get_samples(pkt_size, successful_pkt_loss, port_samples)
154 # store results with success tag in influxdb
156 {'Success_' + key: value for key, value in samples.items()}
158 success_samples["Success_rx_total"] = int(result.rx_total)
159 success_samples["Success_tx_total"] = int(result.tx_total)
160 success_samples["Success_can_be_lost"] = int(result.can_be_lost)
161 success_samples["Success_drop_total"] = int(result.drop_total)
162 success_samples["Success_RxThroughput"] = samples["RxThroughput"]
163 success_samples["Success_RxThroughput_gbps"] = \
164 (samples["RxThroughput"] / 1000) * ((pkt_size + 20)* 8)
165 LOG.info(">>>##>>Collect SUCCESS TG KPIs %s %s",
166 datetime.datetime.now(), success_samples)
167 self.queue.put(success_samples, True, overall_constants.QUEUE_PUT_TIMEOUT)
169 # Store Actual throughput for result samples
170 actual_max_thruput = success_samples["Success_RxThroughput"]
172 pos_retry = pos_retry + 1
175 if (neg_retry < ok_retry) and (ok_retry is not 0):
178 LOG.info("failure! ... confirm retry")
180 LOG.info("Failure... Decreasing upper bound")
181 self.current_upper = test_value
183 neg_retry = neg_retry + 1
184 samples = result.get_samples(pkt_size, successful_pkt_loss, port_samples)
186 if theor_max_thruput < samples["TxThroughput"]:
187 theor_max_thruput = samples['TxThroughput']
188 self.queue.put({'theor_max_throughput': theor_max_thruput})
190 LOG.info(">>>##>>Collect TG KPIs %s %s", datetime.datetime.now(), samples)
191 self.queue.put(samples, True, overall_constants.QUEUE_PUT_TIMEOUT)
193 LOG.info(">>>##>> Result Reached PktSize %s Theor_Max_Thruput %s Actual_throughput %s",
194 pkt_size, theor_max_thruput, actual_max_thruput)
195 result_samples["Result_pktSize"] = pkt_size
196 result_samples["Result_theor_max_throughput"] = theor_max_thruput
197 result_samples["Result_Actual_throughput"] = actual_max_thruput
198 self.queue.put(result_samples)