nomos-simulations/mixnet/ordering

Queuing Mechanism: Ordering Experiments

This directory contains the code for the Ordering Experiments, which is the part of the Queuing Mechanism Experiments.

Usages

cargo install --path ordering

ordering --exp-id 1 --session-id 1 --queue-type PureCoinFlipping --outdir $PWD/out --num-threads 4

• exp-id: Experiment ID (starting from 1)
• session-id: Session ID (starting from 1)
• queue-type: NonMix, PureCoinFlipping, PureRandomSampling, PermutedCoinFlipping, NoisyCoinFlipping, or NoisyCoinFlippingRandomRelease
• outdir: Output directory
• num-threads: The number of threads to run each iteration of the parameter sets of each experiment

Outputs

<outdir>/
  ordering_e1s1_PureCoinFlipping_2024-09-16T09:18:59.482141+00:00_0d0h0m10s/
    paramset_[1..P]/
      paramset.csv
      iteration_[0..I]_0d0h0m0s/
        topology.csv
        latency.csv
        data_msg_counts.csv
        sent_seq_[0..S].csv
        recv_seq_[0..R].csv

• paramset_[1..P]/: Each experiment consists of multiple parameter sets. The result of each parameter set is stored in a separate directory.
• paramset.csv: The detailed parameters of the parameter set.
• iteration_[0..I]_0d0h0m0s: The result of each iteration (with the elapsed time)
  • toplogy.csv: The randomly generated topology of the network
  • latency.csv: The latency for each message to be delivered from the sender to the receiver
  • data_msg_counts.csv: The number of data messages staying in each queue in each time window
  • sent_seq_[0..S].csv: The sequence of sent messages by the sender
  • sent_seq_[0..R].csv: The sequence of received messages by the receiver

Aggregation Tools

Since the ordering experiments are heavy, the aggregation tools are provided separately to aggregate the results of all experiments ans parameter sets after the experiments are done.

Latency Aggregation

This tool reads all **/iteration_*/latency.csv files and aggregates all latencies into a single CSV file: **/paramset_[1..P]/latency_stats.csv, as below.

min,median,mean,std,max
0,93.0,123.07003891050584,109.38605760356785,527

Data Message Counts Aggregation

This tool reads all **/iteration_*/data_msg_counts.csv files and aggregates all counts into a single CSV file: **/paramset_[1..P]/data_msg_counts_stats.csv, as below.

min,median,mean,std,max
0,1.0,9.231619223429988,31.290104671648148,289

Ordering Coefficient Calculation

This tool is not an aggregation tool, but it calculates the strong/casual/weak ordering coefficients from the **/iteration_*/sent_seq_*.csv and **/iteration_*/recv_seq_*.csv files. The result is stored in CSV files: **/iteration_*/coeffs_[sender_id]_[receiver_id].csv, as below.

sender,receiver,strong,casual,weak
0,1,0,1,4

Ordering Coefficient Aggregation

This tool reads all **/iteration_*/coeffs_*_*.csv files (calculated above) and aggregates all coefficients into three CSV file: **/paramset_[1..P]/[strong|casual|weak]_coeff_stats.csv, as below.

min,median,mean,std,max
0,0.0,0.25,0.4442616583193193,1

Final Aggregation Across All Experiments

This tool reads all of the following files:

• **/latency_stats.csv
• **/data_msg_counts_stats.csv
• **/[strong|casual|weak]_coeff_stats.csv and aggregates them into a single CSV file: aggregated.csv, as below.

paramset,num_mixes,num_paths,random_topology,peering_degree,min_queue_size,transmission_rate,num_senders,num_sender_msgs,sender_data_msg_prob,mix_data_msg_prob,queue_type,num_iterations,data_msg_count_min,data_msg_count_median,data_msg_count_mean,data_msg_count_std,data_msg_count_max,latency_min,latency_median,latency_mean,latency_std,latency_max,strong_coeff_min,strong_coeff_median,strong_coeff_mean,strong_coeff_std,strong_coeff_max,casual_coeff_min,casual_coeff_median,casual_coeff_mean,casual_coeff_std,casual_coeff_max,weak_coeff_min,weak_coeff_median,weak_coeff_mean,weak_coeff_std,weak_coeff_max
1,8,0,true,2,10,1,1,10000,0.01,0.0625,NoisyCoinFlipping,10,0,1.0,9.231619223429988,31.290104671648148,289,0,93.0,123.07003891050584,109.38605760356785,527,0,0.0,0.25,0.4442616583193193,1,0,0.0,0.45,0.6863327411532597,2,0,2.0,1.85,1.5312533566021211,5
...

This aggregated.csv file can be analyzed by the analysis tools.