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Muhammed Shafin P
Muhammed Shafin P

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NDM-TCP vs TCP Cubic vs TCP Reno: High-Performance Fiber/Broadband Network Test

In this performance evaluation, we tested three congestion control algorithms—NDM-TCP (ML-based), TCP Cubic, and TCP Reno—under near-optimal network conditions that simulate high-quality fiber or broadband connections.

Test Configuration: Optimal Fiber/Broadband Simulation

To replicate high-performance wired network conditions, we configured the following network parameters using Linux traffic control (tc):

  • Base Latency: 15ms
  • Latency Variation: ±2ms (minimal jitter)
  • Packet Loss Rate: 0.1% (near-perfect reliability)

These parameters were randomly chosen to represent ideal conditions in modern fiber-optic or high-quality broadband networks, where users experience low latency, minimal jitter, and extremely low packet loss.

Test Results Overview

The following data was captured during a 10-second iperf3 performance test:

Metric NDM-TCP (ML Model) TCP Cubic TCP Reno
Total Transfer (Sender) 838 MBytes 825 MBytes 740 MBytes
Total Received (Receiver) 835 MBytes 824 MBytes 738 MBytes
Average Bitrate (Sender) 702 Mbits/sec 692 Mbits/sec 620 Mbits/sec
Receiver Bitrate 698 Mbits/sec 689 Mbits/sec 617 Mbits/sec
Total Retransmissions 10 20 22
Test Duration (Receiver) 10.03 sec 10.03 sec 10.03 sec

Detailed Interval Analysis

NDM-TCP Performance Over Time

Interval (sec) Transfer Bitrate Retr Cwnd
0.00-1.00 99.4 MBytes 833 Mbits/sec 2 21.4 MBytes
1.00-2.00 116 MBytes 975 Mbits/sec 1 7.31 MBytes
2.00-3.00 117 MBytes 984 Mbits/sec 0 7.81 MBytes
3.00-4.00 102 MBytes 853 Mbits/sec 1 3.31 MBytes
4.00-5.00 60.5 MBytes 508 Mbits/sec 1 1.94 MBytes
5.00-6.00 81.8 MBytes 686 Mbits/sec 0 3.06 MBytes
6.00-7.00 86.6 MBytes 727 Mbits/sec 2 1.50 MBytes
7.00-8.00 68.1 MBytes 571 Mbits/sec 0 2.62 MBytes
8.00-9.00 61.1 MBytes 513 Mbits/sec 1 1.62 MBytes
9.00-10.00 43.6 MBytes 365 Mbits/sec 2 1.19 MBytes

TCP Cubic Performance Over Time

Interval (sec) Transfer Bitrate Retr Cwnd
0.00-1.00 95.8 MBytes 802 Mbits/sec 3 5.81 MBytes
1.00-2.00 94.2 MBytes 790 Mbits/sec 4 2.37 MBytes
2.00-3.00 67.4 MBytes 565 Mbits/sec 4 1.62 MBytes
3.00-4.00 59.1 MBytes 496 Mbits/sec 1 1.94 MBytes
4.00-5.00 80.9 MBytes 679 Mbits/sec 0 3.00 MBytes
5.00-6.00 88.9 MBytes 746 Mbits/sec 1 2.94 MBytes
6.00-7.00 108 MBytes 905 Mbits/sec 0 4.00 MBytes
7.00-8.00 103 MBytes 863 Mbits/sec 1 3.62 MBytes
8.00-9.00 61.4 MBytes 515 Mbits/sec 3 1.75 MBytes
9.00-10.00 66.5 MBytes 557 Mbits/sec 3 1.94 MBytes

TCP Reno Performance Over Time

Interval (sec) Transfer Bitrate Retr Cwnd
0.00-1.00 88.8 MBytes 743 Mbits/sec 4 1.56 MBytes
1.00-2.00 74.1 MBytes 622 Mbits/sec 3 1.31 MBytes
2.00-3.00 48.8 MBytes 409 Mbits/sec 2 2.31 MBytes
3.00-4.00 75.2 MBytes 631 Mbits/sec 1 2.56 MBytes
4.00-5.00 56.2 MBytes 472 Mbits/sec 3 1.75 MBytes
5.00-6.00 79.9 MBytes 670 Mbits/sec 2 1.87 MBytes
6.00-7.00 79.9 MBytes 670 Mbits/sec 1 2.00 MBytes
7.00-8.00 85.6 MBytes 718 Mbits/sec 2 2.00 MBytes
8.00-9.00 93.6 MBytes 785 Mbits/sec 0 4.00 MBytes
9.00-10.00 57.4 MBytes 481 Mbits/sec 4 1.31 MBytes

Key Findings and Analysis

1. NDM-TCP: Aggressive and Efficient Leader

In this high-quality network environment, the ML-driven NDM-TCP demonstrated optimal performance:

  • Highest Throughput: Achieved 702 Mbits/sec, outperforming both Cubic and Reno
  • Best Efficiency: Only 10 retransmissions—half that of Cubic and less than half of Reno
  • Massive Windows: Reached peak congestion windows up to 21.4 MBytes, demonstrating the ML model's ability to exploit high-bandwidth, low-loss conditions
  • Peak Performance: Hit 984 Mbits/sec in the 2-3 second interval with zero retransmissions

2. TCP Cubic: Close Second with More Overhead

TCP Cubic performed competitively but couldn't match NDM-TCP's efficiency:

  • Strong Throughput: Achieved 692 Mbits/sec, just 1.4% behind NDM-TCP
  • Double the Retransmissions: 20 retransmissions versus NDM-TCP's 10
  • Moderate Windows: Peak congestion window of 5.81 MBytes—significantly smaller than NDM-TCP's aggressive scaling
  • Consistent Mid-Range Performance: Maintained steady performance in the 500-900 Mbits/sec range

3. TCP Reno: Falling Behind in High-Speed Networks

TCP Reno showed its age in this high-performance scenario:

  • Lowest Throughput: Achieved only 620 Mbits/sec, 13% behind NDM-TCP
  • High Retransmissions: 22 retransmissions, the worst among all three
  • Conservative Windows: Maximum congestion window of 4.00 MBytes
  • High Variability: Performance ranged from 409 to 785 Mbits/sec with significant fluctuations

Performance Comparison

Throughput Rankings

  1. NDM-TCP: 702 Mbits/sec (+1.4% vs Cubic, +13% vs Reno)
  2. TCP Cubic: 692 Mbits/sec (+12% vs Reno)
  3. TCP Reno: 620 Mbits/sec

Reliability Rankings (Lower is Better)

  1. NDM-TCP: 10 retransmissions (Best efficiency)
  2. TCP Cubic: 20 retransmissions (50% more than NDM-TCP)
  3. TCP Reno: 22 retransmissions (120% more than NDM-TCP)

Efficiency Metric: Data per Retransmission

  • NDM-TCP: 83.8 MBytes per retransmission (Most efficient)
  • TCP Cubic: 41.2 MBytes per retransmission
  • TCP Reno: 33.6 MBytes per retransmission (Least efficient)

Peak Congestion Window Comparison

  • NDM-TCP: 21.4 MBytes (Largest, most aggressive scaling)
  • TCP Cubic: 5.81 MBytes
  • TCP Reno: 4.00 MBytes (Smallest, most conservative)

Conclusion: ML Advantage in High-Performance Networks

In optimal network conditions with minimal latency and packet loss, NDM-TCP demonstrates a clear advantage:

NDM-TCP excels in high-quality networks by aggressively scaling its congestion window to exploit available bandwidth while maintaining superior efficiency. The ML model's ability to recognize favorable network conditions allowed it to achieve:

  • Highest throughput (702 Mbits/sec)
  • Lowest retransmissions (10 total)
  • Most aggressive window scaling (21.4 MBytes peak)
  • Best data efficiency (83.8 MBytes per retransmission)

TCP Cubic remains competitive with 692 Mbits/sec throughput, making it a solid general-purpose choice. However, its doubled retransmission count indicates it's less efficient at exploiting optimal conditions.

TCP Reno struggles in high-bandwidth environments, constrained by its conservative congestion control designed for earlier network generations. Its 13% lower throughput and higher retransmission rate make it suboptimal for modern high-speed networks.

Key Insight: This test reveals that NDM-TCP's machine learning approach isn't just about conservative stability—it's about network awareness. In poor conditions, it prioritizes reliability; in excellent conditions, it aggressively maximizes throughput while maintaining superior efficiency. This adaptive intelligence gives it an edge across diverse network environments.

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