Cubic-Friendliness Experiment
To be deployable, new congestion control algorithms (CCAs) have to be able to compete against established CCAs. Cubic is nowadays the most widespread algorithm that is used by all major operating systems as the default.
In the Cubic-friendliness experiment, it is evaluated if a CCA is fair towards Cubic. Newly proposed CCAs should be reasonably fair to Cubic, i.e., when they compete against Cubic the bandwidth should be distributed fairly.
Scenario
In the Cubic-friendliness experiment, multiple flows operate in a
static dumbbell network. Each flow generates greedy source traffic and
uses either the CCA under test or Cubic. The experiment has one
parameter k, which sets the number of flows. Half of the
flows (rounded down) use the CCA under test, whereas the other half
(rounded up) use Cubic.
To summarize the experiment setup:
Topology: Dumbbell topology (\(K>1\)) with static network parameters
Flows: Multiple flows (\(K>1\)) that use either the CCA under test or Cubic
Traffic Generation Model: Greedy source traffic
Experiment Results
Experiment #82
Parameters
Command: ns3-dev-ccperf-static-dumbbell-default --experiment-name=cubic_fairness --db-path=benchmark_TcpNewReno.db '--parameters={aut:TcpNewReno,k:2}' --aut=TcpNewReno --stop-time=15s --seed=42 --bw=32Mbps --loss=0.0 --qlen=40p --qdisc=FifoQueueDisc --rtts=15ms,15ms --sources=src_0,src_1 --destinations=dst_0,dst_1 --protocols=TCP,TCP --algs=TcpNewReno,TcpCubic --recoveries=TcpPrrRecovery,TcpPrrRecovery --start-times=0s,0s --stop-times=15s,15s '--traffic-models=Greedy(bytes=0),Greedy(bytes=0)'
Flows
| src | dst | transport_protocol | cca | cc_recovery_alg | traffic_model | start_time | stop_time |
|---|---|---|---|---|---|---|---|
| src_0 | dst_0 | TCP | TcpNewReno | TcpPrrRecovery | Greedy(bytes=0) | 0.00 | 15.00 |
| src_1 | dst_1 | TCP | TcpCubic | TcpPrrRecovery | Greedy(bytes=0) | 0.00 | 15.00 |
Metrics
The following tables list the flow, link, and network metrics of experiment #82. Refer to the the metrics page for definitions of the listed metrics.
Flow Metrics
Flow metrics capture the performance of an individual flow. They are measured at the endpoints of a network path at either the source, the receiver, or both. Bold values indicate which flow achieved the best performance.
| Metric | flow_1 | flow_2 |
|---|---|---|
| cov_in_flight_l4 | 0.24 | 0.13 |
| cov_throughput_l4 | 0.19 | 0.16 |
| flow_completion_time_l4 | 14.99 | 15.00 |
| mean_cwnd_l4 | 32.22 | 38.33 |
| mean_delivery_rate_l4 | 13.82 | 16.95 |
| mean_est_qdelay_l4 | 11.17 | 11.18 |
| mean_idt_ewma_l4 | 0.71 | 0.60 |
| mean_in_flight_l4 | 31.74 | 38.32 |
| mean_network_power_l4 | 531.02 | 660.58 |
| mean_one_way_delay_l7 | 2152.18 | 1739.57 |
| mean_recovery_time_l4 | 32.95 | 33.23 |
| mean_sending_rate_l4 | 13.90 | 17.02 |
| mean_sending_rate_l7 | 15.95 | 19.09 |
| mean_srtt_l4 | 26.17 | 26.18 |
| mean_throughput_l4 | 13.83 | 16.96 |
| mean_throughput_l7 | 13.83 | 16.96 |
| mean_utility_mpdf_l4 | -0.08 | -0.06 |
| mean_utility_pf_l4 | 2.61 | 2.82 |
| mean_utilization_bdp_l4 | 0.83 | 1.00 |
| mean_utilization_bw_l4 | 0.43 | 0.53 |
| total_retransmissions_l4 | 66.00 | 59.00 |
| total_rtos_l4 | 0.00 | 0.00 |
Link Metrics
Link metrics are recorded at the network links of interest, typically at bottlenecks. They include metrics that measure queue states. Bold values indicate which link achieved the best performance.
| Metric | btl_forward |
|---|---|
| mean_qdisc_delay_l2 | 10.03 |
| mean_qdisc_length_l2 | 27.83 |
| mean_sending_rate_l1 | 31.95 |
| total_qdisc_drops_l2 | 125.00 |
Network Metrics
Network metrics assess the entire network as a
whole by aggregating other metrics, e.g., the aggregated throughput of
all flows.
Hence, the network metrics has only one column named net.
| Metric | net |
|---|---|
| mean_agg_in_flight_l4 | 70.06 |
| mean_agg_throughput_l4 | 30.79 |
| mean_agg_utility_mpdf_l4 | -0.14 |
| mean_agg_utility_pf_l4 | 5.42 |
| mean_agg_utilization_bdp_l4 | 1.82 |
| mean_agg_utilization_bw_l4 | 0.96 |
| mean_entropy_fairness_throughput_l4 | 0.69 |
| mean_jains_fairness_throughput_l4 | 0.97 |
| mean_product_fairness_throughput_l4 | 227.96 |
Figures
The following figures show the results of the experiment #82.Time Series Plot of the Operating Point
Time series plot of the number of segments in flight, the smoothed round-trip time (sRTT), and the throughput at the transport layer.
Distribution of the Operating Point
The empirical cumulative distribution function (eCDF) of the throughput and smoothed round-trip time (sRTT) at the transport layer of each flow.
In Flight vs Mean Operating Point
The mean throughput and mean smoothed round-trip time (sRTT) at the transport layer of each flow. The optimal operating point is highlighted with a star (magenta). The joint operating point is given by the aggregated throughput and the mean sRTT over all flows
