TCP congestion control

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Short description: Techniques to improve network performance over Transmission Control Protocol


Transmission Control Protocol (TCP) uses a congestion control algorithm that includes various aspects of an additive increase/multiplicative decrease (AIMD) scheme, along with other schemes including slow start[1] and congestion window (CWND), to achieve congestion avoidance. The TCP congestion-avoidance algorithm is the primary basis for congestion control in the Internet.[2][3][4] Per the end-to-end principle, congestion control is largely a function of internet hosts, not the network itself. There are several variations and versions of the algorithm implemented in protocol stacks of operating systems of computers that connect to the Internet.

To avoid congestive collapse, TCP uses multi-faceted congestion-control strategy. For each connection, TCP maintains a CWND, limiting the total number of unacknowledged packets that may be in transit end-to-end. This is somewhat analogous to TCP's sliding window used for flow control.

Additive increase/multiplicative decrease

The additive increase/multiplicative decrease (AIMD) algorithm is a closed-loop control algorithm. AIMD combines linear growth of the congestion window with an exponential reduction when a congestion takes place. Multiple flows using AIMD congestion control will eventually converge to use equal amounts of a contended link.[5]

This is the algorithm that is described in RFC 5681 for the "congestion avoidance" state.[6]

Congestion window

In TCP, the congestion window (CWND) is one of the factors that determines the number of bytes that can be sent out at any time. The congestion window is maintained by the sender and is a means of stopping a link between the sender and the receiver from becoming overloaded with too much traffic. This should not be confused with the sliding window maintained by the sender which exists to prevent the receiver from becoming overloaded. The congestion window is calculated by estimating how much congestion there is on the link.

When a connection is set up, the congestion window, a value maintained independently at each host, is set to a small multiple of the maximum segment size (MSS) allowed on that connection. Further variance in the congestion window is dictated by an additive increase/multiplicative decrease (AIMD) approach. This means that if all segments are received and the acknowledgments reach the sender on time, some constant is added to the window size. It will follow different algorithms.

A system administrator may adjust the maximum window size limit, or adjust the constant added during additive increase, as part of TCP tuning.

The flow of data over a TCP connection is also controlled by the use of the receive window advertised by the receiver. A sender can send data less than its own congestion window and the receive window.

Slow start

Slow start, defined by RFC 5681.[7] is part of the congestion control strategy used by TCP in conjunction with other algorithms to avoid sending more data than the network is capable of forwarding, that is, to avoid causing network congestion.

Slow start begins initially with a congestion window size (CWND) of 1, 2, 4 or 10 MSS.[8][3]:1 The value for the congestion window size can be increased by 1 MSS with each acknowledgement (ACK) received, effectively doubling the window size each RTT.[lower-alpha 1]

The transmission rate will be increased by the slow-start algorithm until either a packet loss is detected, the receiver's advertised window (rwnd) becomes the limiting factor, or slow start threshold (ssthresh) is reached, which is used to determine whether the slow start or congestion avoidance algorithm is used, a value set to limit slow start.

If the CWND reaches ssthresh, TCP switches to the congestion avoidance algorithm. It should be increased by up to 1 MSS for each RTT. A common formula is that each new ACK increases the CWND by MSS * MSS / CWND. It increases almost linearly and provides an acceptable approximation.

If a loss event occurs, TCP assumes that it is due to network congestion and takes steps to reduce the offered load on the network. These measures depend on the exact TCP congestion avoidance algorithm used.

When a TCP sender detects segment loss using the retransmission timer and the given segment has not yet been resent, the value of ssthresh must be set to no more than half of the amount of data that has been sent but not yet cumulatively acknowledged or 2 * MSS, whichever value is greater.

TCP Tahoe
When a loss occurs, retransmit is sent, half of the current CWND is saved as ssthresh and slow start begins again from its initial CWND.
TCP Reno
A fast retransmit is sent, half of the current CWND is saved as ssthresh and as new CWND, thus skipping slow start and going directly to the congestion avoidance algorithm. The overall algorithm here is called fast recovery.

Slow start assumes that unacknowledged segments are due to network congestion. While this is an acceptable assumption for many networks, segments may be lost for other reasons, such as poor data link layer transmission quality. Thus, slow start can perform poorly in situations with poor reception, such as wireless networks.

The slow start protocol also performs badly for short-lived connections. Older web browsers would create many consecutive short-lived connections to the web server, and would open and close the connection for each file requested. This kept most connections in the slow start mode, which resulted in poor response time. To avoid this problem, modern browsers either open multiple connections simultaneously or reuse one connection for all files requested from a particular web server. Connections, however, cannot be reused for the multiple third-party servers used by web sites to implement web advertising, sharing features of social networking services,[9] and counter scripts of web analytics.

Fast retransmit

Fast retransmit is an enhancement to TCP that reduces the time a sender waits before retransmitting a lost segment. A TCP sender normally uses a simple timer to recognize lost segments. If an acknowledgment is not received for a particular segment within a specified time (a function of the estimated round-trip delay time), the sender will assume the segment was lost in the network and will retransmit the segment.

Duplicate acknowledgment is the basis for the fast retransmit mechanism. After receiving a packet an acknowledgement is sent for the last in-order byte of data received. For an in-order packet, this is effectively the last packet's sequence number plus the current packet's payload length. If the next packet in the sequence is lost but a third packet in the sequence is received, then the receiver can only acknowledge the last in-order byte of data, which is the same value as was acknowledged for the first packet. The second packet is lost and the third packet is not in order, so the last in-order byte of data remains the same as before. Thus a Duplicate acknowledgment occurs. The sender continues to send packets, and a fourth and fifth packet are received by the receiver. Again, the second packet is missing from the sequence, so the last in-order byte has not changed. Duplicate acknowledgments are sent for both of these packets.

When a sender receives three duplicate acknowledgments, it can be reasonably confident that the segment carrying the data that followed the last in-order byte specified in the acknowledgment was lost. A sender with fast retransmit will then retransmit this packet immediately without waiting for its timeout. On receipt of the retransmitted segment, the receiver can acknowledge the last in-order byte of data received. In the above example, this would acknowledge to the end of the payload of the fifth packet. There is no need to acknowledge intermediate packets since TCP uses cumulative acknowledgments by default.

Algorithms

The naming convention for congestion control algorithms (CCAs) may have originated in a 1996 paper by Kevin Fall and Sally Floyd.[10][failed verification]

The following is one possible classification according to the following properties:

  1. the type and amount of feedback received from the network
  2. incremental deployability on the current Internet
  3. the aspect of performance it aims to improve: high bandwidth-delay product networks (B); lossy links (L); fairness (F); advantage to short flows (S); variable-rate links (V); speed of convergence (C)
  4. the fairness criterion it uses

Some well-known congestion avoidance mechanisms are classified by this scheme as follows:

Variant Feedback Required changes Benefits Fairness
(New) Reno Loss — — Delay
Vegas Delay Sender Less loss Proportional
High Speed Loss Sender High bandwidth
BIC Loss Sender High bandwidth
CUBIC Loss Sender High bandwidth
C2TCP[11][12] Loss/Delay Sender Ultra-low latency and high bandwidth
NATCP[13] Multi-bit signal Sender Near Optimal Performance
Elastic-TCP Loss/Delay Sender High bandwidth/short & long-distance
Agile-TCP Loss Sender High bandwidth/short-distance
H-TCP Loss Sender High bandwidth
FAST Delay Sender High bandwidth Proportional
Compound TCP Loss/Delay Sender High bandwidth Proportional
Westwood Loss/Delay Sender Lossy links
Jersey Loss/Delay Sender Lossy links
BBR[14] Delay Sender BLVC, Bufferbloat
CLAMP Multi-bit signal Receiver, Router Variable-rate links Max-min
TFRC Loss Sender, Receiver No Retransmission Minimum delay
XCP Multi-bit signal Sender, Receiver, Router BLFC Max-min
VCP 2-bit signal Sender, Receiver, Router BLF Proportional
MaxNet Multi-bit signal Sender, Receiver, Router BLFSC Max-min
JetMax Multi-bit signal Sender, Receiver, Router High bandwidth Max-min
RED Loss Router Reduced delay
ECN Single-bit signal Sender, Receiver, Router Reduced loss

TCP Tahoe and Reno

TCP Tahoe and Reno algorithms were retrospectively named after the versions or flavours of the 4.3BSD operating system in which each first appeared (which were themselves named after Lake Tahoe and the nearby city of Reno, Nevada). The Tahoe algorithm first appeared in 4.3BSD-Tahoe (which was made to support the CCI Power 6/32 "Tahoe" minicomputer), and was later made available to non-AT&T licensees as part of the 4.3BSD Networking Release 1; this ensured its wide distribution and implementation. Improvements were made in 4.3BSD-Reno and subsequently released to the public as Networking Release 2 and later 4.4BSD-Lite.

While both consider retransmission timeout (RTO) and duplicate ACKs as packet loss events, the behavior of Tahoe and Reno differ primarily in how they react to duplicate ACKs:

  • Tahoe: if three duplicate ACKs are received (i.e. four ACKs acknowledging the same packet, which are not piggybacked on data and do not change the receiver's advertised window), Tahoe performs a fast retransmit, sets the slow start threshold to half of the current congestion window, reduces the congestion window to 1 MSS, and resets to slow start state.[15]
  • Reno: if three duplicate ACKs are received, Reno will perform a fast retransmit and skip the slow start phase by instead halving the congestion window (instead of setting it to 1 MSS like Tahoe), setting the ssthresh equal to the new congestion window, and enter a phase called fast recovery.[16]

In both Tahoe and Reno, if an ACK times out (RTO timeout), slow start is used, and both algorithms reduce the congestion window to 1 MSS.[citation needed]

TCP New Reno

TCP New Reno, defined by RFC 6582 (which obsolesces previous definitions in RFC 3782 and RFC 2582), improves retransmission during the fast-recovery phase of TCP Reno.

During fast recovery, to keep the transmit window full, for every duplicate ACK that is returned, a new unsent packet from the end of the congestion window is sent.

The difference from Reno is that New Reno does not halve ssthresh immediately which may reduce the window too much if multiple packet losses occur. It does not exit fast-recovery and reset ssthresh until it acknowledges all of the data.

After retransmission, newly acknowledged data have two cases:

  • Full acknowledgments: The ACK acknowledges all the intermediate segments sent, the ssthresh can be not changed, cwnd can be set to ssthresh
  • Partial acknowledgments: The ACK does not acknowledge all data. It means another loss may occur, retransmit the first unacknowledged segment if permitted

It uses a variable called "recover" to record how much data needs to be recovered. After a retransmit timeout, it records the highest sequence number transmitted in the recover variable and exits the fast recovery procedure. If this sequence number is acknowledged, TCP returns to the congestion avoidance state.

A problem occurs with New Reno when there are no packet losses but instead, packets are reordered by more than 3 packet sequence numbers. In this case, New Reno mistakenly enters fast recovery. When the reordered packet is delivered, duplicate and needless retransmissions are immediately sent.

New Reno performs as well as SACK at low packet error rates and substantially outperforms Reno at high error rates.[17]

TCP Vegas

Until the mid-1990s, all of TCP's set timeouts and measured round-trip delays were based upon only the last transmitted packet in the transmit buffer. University of Arizona researchers Larry Peterson and Lawrence Brakmo introduced TCP Vegas in which timeouts were set and round-trip delays were measured for every packet in the transmit buffer. In addition, TCP Vegas uses additive increases in the congestion window. In a comparison study of various TCP CCAs, TCP Vegas appeared to be the smoothest followed by TCP CUBIC.[18]

TCP Vegas was not widely deployed outside Peterson's laboratory but was selected as the default congestion control method for DD-WRT firmware v24 SP2.[19]

TCP Hybla

TCP Hybla[20][21] aims to eliminate penalties to TCP connections that use high-latency terrestrial or satellite radio links. Hybla improvements are based on analytical evaluation of the congestion window dynamics.[22]

TCP BIC

Binary Increase Congestion control (BIC) is a TCP implementation with an optimized CCA for high-speed networks with high latency, known as long fat networks (LFNs).[23] BIC is used by default in Linux kernels 2.6.8 through 2.6.18.[citation needed]

TCP CUBIC

CUBIC is a less aggressive and more systematic derivative of BIC, in which the window is a cubic function of time since the last congestion event, with the inflection point set to the window prior to the event. CUBIC is used by default in Linux kernels since version 2.6.19.

Agile-SD TCP

Agile-SD is a Linux-based CCA which is designed for the real Linux kernel. It is a receiver-side algorithm that employs a loss-based approach using a novel mechanism, called agility factor (AF). to increase the bandwidth utilization over high-speed and short-distance networks (low bandwidth-delay product networks) such as local area networks or fiber-optic network, especially when the applied buffer size is small.[24] It has been evaluated by comparing its performance to Compound TCP (the default CCA in MS Windows) and CUBIC (the default of Linux) using NS-2 simulator. It improves the total performance up to 55% in term of average throughput.

TCP Westwood+

Westwood+ is a sender-only modification of TCP Reno that optimizes the performance of TCP congestion control over both wired and wireless networks. TCP Westwood+ is based on end-to-end bandwidth estimation to set the congestion window and slow-start threshold after a congestion episode, that is, after three duplicate acknowledgments or a timeout. The bandwidth is estimated by averaging the rate of returning acknowledgment packets. In contrast with TCP Reno, which blindly halves the congestion window after three duplicate ACKs, TCP Westwood+ adaptively sets a slow-start threshold and a congestion window that takes into account an estimate of bandwidth available at the time congestion is experienced. Compared to Reno and New Reno, Westwood+ significantly increases throughput over wireless links and improves fairness in wired networks.[citation needed]

Compound TCP

Compound TCP is a Microsoft implementation of TCP which maintains two different congestion windows simultaneously, with the goal of achieving good performance on LFNs while not impairing fairness. It has been widely deployed in Windows versions since Microsoft Windows Vista and Windows Server 2008 and has been ported to older Microsoft Windows versions as well as Linux.

TCP Proportional Rate Reduction

TCP Proportional Rate Reduction (PRR)[25] is an algorithm designed to improve the accuracy of data sent during recovery. The algorithm ensures that the window size after recovery is as close as possible to the slow start threshold. In tests performed by Google, PRR resulted in a 3–10% reduction in average latency and recovery timeouts were reduced by 5%.[26] PRR is available in Linux kernels since version 3.2.[27]

TCP BBR

Bottleneck Bandwidth and Round-trip propagation time (BBR) is a CCA developed at Google in 2016.[28] While most CCAs are loss-based, in that they rely on packet loss to detect congestion and lower rates of transmission, BBR, like TCP Vegas, is model-based. The algorithm uses the maximum bandwidth and round-trip time at which the network delivered the most recent flight of outbound data packets to build a model of the network. Each cumulative or selective acknowledgment of packet delivery produces a rate sample that records the amount of data delivered over the time interval between the transmission of a data packet and the acknowledgment of that packet.[29]

When implemented at YouTube, BBRv1 yielded an average of 4% higher network throughput and up to 14% in some countries.[30] BBR has been available for Linux TCP since Linux 4.9.[31] It is also available for QUIC.[32]

BBR version 1 (BBRv1) fairness to non-BBR streams is disputed. While Google's presentation shows BBRv1 co-existing well with CUBIC,[28] researchers like Geoff Huston and Hock, Bless and Zitterbart found it unfair to other streams and not scalable.[33] Hock et al. also found "some severe inherent issues such as increased queuing delays, unfairness, and massive packet loss" in the BBR implementation of Linux 4.9.[34] Soheil Abbasloo et al. (authors of C2TCP) show that BBRv1 doesn't perform well in dynamic environments such as cellular networks.[11][12] They have also shown that BBR has an unfairness issue. For instance, when a CUBIC flow (which is the default TCP implementation in Linux, Android, and MacOS) coexists with a BBR flow in the network, the BBR flow can dominate the CUBIC flow and get the whole link bandwidth from it (see figure 16 in [11]).

Version 2 attempts to deal with the issue of unfairness when operating alongside loss-based congestion management such as CUBIC.[35] In BBRv2 the model used by BBRv1 is augmented to include information about packet loss and information from Explicit Congestion Notification (ECN).[36] Whilst BBRv2 may at times have lower throughput than BBRv1 it is generally considered to have better goodput.[citation needed]

Version 3 (BBRv3) fixes two bugs in BBRv2 (premature end of bandwidth probing, bandwidth convergence) and performs some performance tuning. There is also a variant, termed BBR.Swift, optimized for datacenter-internal links: it uses network_RTT (excluding receiver delay) as the main congestion control signal.[36]

C2TCP

Cellular Controlled Delay TCP (C2TCP)[11][12] was motivated by the lack of a flexible end-to-end TCP approach that can satisfy various QoS requirements for different applications without requiring any changes in the network devices. C2TCP aims to satisfy ultra-low latency and high-bandwidth requirements of applications such as virtual reality, video conferencing, online gaming, vehicular communication systems, etc. in a highly dynamic environment such as current LTE and future 5G cellular networks. C2TCP works as an add-on on top of loss-based TCP (e.g. Reno, NewReno, CUBIC, BIC, ...), it is only required to be installed on the server-side and makes the average delay of packets bounded to the desired delays set by the applications.

Researchers at NYU[37] showed that C2TCP outperforms the delay and delay-variation performance of various state-of-the-art TCP schemes. For instance, they showed that compared to BBR, CUBIC, and Westwood on average, C2TCP decreases the average delay of packets by about 250%, 900%, and 700% respectively on various cellular network environments.[11]

Elastic-TCP

Elastic-TCP was proposed in February 2019 to increase bandwidth utilization over high-BDP networks in support of cloud computing. It is a Linux-based CCA that is designed for the Linux kernel. It is a receiver-side algorithm that employs a loss-delay-based approach using a novel mechanism called a window-correlated weighting function (WWF). It has a high level of elasticity to deal with different network characteristics without the need for human tuning. It has been evaluated by comparing its performance to Compound TCP (the default CCA in MS Windows), CUBIC (the default for Linux) and TCP-BBR (the default of Linux 4.9 used by Google) using the NS-2 simulator and testbed. Elastic-TCP significantly improves the total performance in terms of average throughput, loss ratio, and delay.[38]

NATCP

Soheil Abbasloo et al. proposed NATCP (Network-Assisted TCP)[13] a controversial[according to whom?] TCP design targeting multi-access edge computing (MEC). The key idea of NATCP is that if the characteristics of the network were known beforehand, TCP would have been designed differently. Therefore, NATCP employs the available features and properties in the current MEC-based cellular architectures to push the performance of TCP close to the optimal performance. NATCP uses out-of-band feedback from the network to the servers located nearby. The feedback from the network, which includes the capacity of the cellular access link and the minimum RTT of the network, guides the servers to adjust their sending rates. As preliminary results show, NATCP outperforms the state-of-the-art TCP schemes.[13][39]

Other TCP congestion avoidance algorithms

TCP New Reno was the most commonly implemented algorithm,[citation needed] SACK support is very common[citation needed] and is an extension to Reno/New Reno. Most others are competing proposals that still need evaluation. Starting with 2.6.8 the Linux kernel switched the default implementation from New Reno to BIC. The default implementation was again changed to CUBIC in the 2.6.19 version. FreeBSD from version 14.X onwards also uses CUBIC as the default algorithm.[51] Previous version used New Reno. However, FreeBSD supports a number of other choices.[52]

When the per-flow product of bandwidth and latency increases, regardless of the queuing scheme, TCP becomes inefficient and prone to instability. This becomes increasingly important as the Internet evolves to incorporate very high-bandwidth optical links.

TCP Interactive (iTCP)[53] allows applications to subscribe to TCP events and respond accordingly enabling various functional extensions to TCP from outside TCP layer. Most TCP congestion schemes work internally. iTCP additionally enables advanced applications to directly participate in congestion control such as to control the source generation rate.

Zeta-TCP detects congestion from both latency and loss rate measures. To maximize the goodput Zeta-TCP and applies different congestion window backoff strategies based on the likelihood of congestion. It also has other improvements to accurately detect packet losses, avoiding retransmission timeout retransmission; and accelerate and control the inbound (download) traffic.[54]

Classification by network awareness

CCAs may be classified in relation to network awareness, meaning the extent to which these algorithms are aware of the state of the network. This consist of three primary categories: black box, grey box, and green box.[55]

Black box algorithms offer blind methods of congestion control. They operate only on the binary feedback received upon congestion and do not assume any knowledge concerning the state of the networks which they manage.

Grey box algorithms use time-instances[clarification needed] in order to obtain measurements and estimations of bandwidth, flow contention, and other knowledge of network conditions.

Green box algorithms offer bimodal methods of congestion control which measures the fair share of total bandwidth which should be allocated for each flow, at any point, during the system's execution.

Black box

  • Highspeed-TCP[56]
  • BIC TCP (Binary Increase Congestion Control Protocol) uses a concave increase of the sources rate after each congestion event until the window is equal to that before the event, in order to maximize the time that the network is fully utilized. After that, it probes aggressively.
  • CUBIC TCP – a less aggressive and more systematic derivative of BIC, in which the window is a cubic function of time since the last congestion event, with the inflection point set to the window prior to the event.
  • AIMD-FC (additive increase multiplicative decrease with fast convergence), an improvement of AIMD.[57]
  • Binomial Mechanisms
  • SIMD Protocol
  • GAIMD

Grey box

  • TCP Vegas – estimates the queuing delay, and linearly increases or decreases the window so that a constant number of packets per flow are queued in the network. Vegas implements proportional fairness.
  • FAST TCP – achieves the same equilibrium as Vegas, but uses proportional control instead of linear increase, and intentionally scales the gain down as the bandwidth increases with the aim of ensuring stability.
  • TCP BBR – estimates the queuing delay but uses exponential increase. Intentionally slows down periodically for fairness and decreased delay.
  • TCP-Westwood (TCPW) – a loss causes the window to be reset to the sender's estimate of the bandwidth-delay product (the smallest measured RTT multiplied by the observed rate of receiving ACKs).[58]
  • C2TCP[12][11]
  • TFRC[59]
  • TCP-Real
  • TCP-Jersey

Green box

  • Bimodal Mechanism – Bimodal Congestion Avoidance and Control mechanism.
  • Signalling methods implemented by routers
    • Random Early Detection (RED) randomly drops packets in proportion to the router's queue size, triggering multiplicative decrease in some flows.
    • Explicit Congestion Notification (ECN)
  • Network-Assisted Congestion Control
    • NATCP[13] - Network-Assisted TCP uses out-of-band explicit feedback indicating minimum RTT of the network and capacity of the cellular access link.
    • The variable-structure congestion control protocol (VCP) uses two ECN bits to explicitly feedback the network state of congestion. It includes an end host side algorithm as well.[citation needed]

The following algorithms require custom fields to be added to the TCP packet structure:

  • Explicit Control Protocol (XCP) – XCP packets carry a congestion header with a feedback field, indicating the increase or decrease of the sender's congestion window. XCP routers set the feedback value explicitly for efficiency and fairness.[60]
  • MaxNet – Uses a single header field, which carries the maximum congestion level of any router on a flow's path. The rate is set as a function of this maximum congestion, resulting in max-min fairness.[61]
  • JetMax, like MaxNet, responds only to the maximum congestion signal, but also carries other overhead fields.

Linux usage

  • BIC is used by default in Linux kernels 2.6.8 through 2.6.18. (August 2004 – September 2006)
  • CUBIC is used by default in Linux kernels since version 2.6.19. (November 2006)
  • PRR is incorporated in Linux kernels to improve loss recovery since version 3.2. (January 2012)
  • BBRv1 is incorporated in Linux kernels to enable model-based congestion control since version 4.9. (December 2016)

See also

Notes

  1. ↑ Even if, actually, the receiver may delay its ACKs, typically sending one ACK for every two segments that it receives[2]

References

  1. ↑ Jacobson & Karels 1988.
  2. ↑ 2.0 2.1 W. Stevens (January 1997), TCP Slow Start, Congestion Avoidance, Fast Retransmit, and Fast Recovery Algorithms, doi:10.17487/RFC2001, RFC 2001, https://tools.ietf.org/html/rfc2001 
  3. ↑ 3.0 3.1 M. Allman; S. Floyd; C. Partridge (October 2002), Increasing TCP's Initial Window, doi:10.17487/RFC3390, RFC 3390, https://tools.ietf.org/html/rfc3390 
  4. ↑ "TCP Congestion Avoidance Explained via a Sequence Diagram". http://www.eventhelix.com/RealtimeMantra/Networking/TCP_Congestion_Avoidance.pdf. 
  5. ↑ Chiu, Dah-Ming; Raj Jain (1989). "Analysis of increase and decrease algorithms for congestion avoidance in computer networks". Computer Networks and ISDN Systems 17: 1–14. doi:10.1016/0169-7552(89)90019-6. 
  6. ↑ Allman, M.; Paxson, V. (September 2009), TCP Congestion Control, IETF, sec. 3.1, doi:10.17487/RFC5681, RFC 5681, https://tools.ietf.org/html/rfc5681#section-3.1, retrieved March 4, 2021 
  7. ↑ Blanton, Ethan; Paxson, Vern; Allman, Mark (September 2009). TCP Congestion Control. https://datatracker.ietf.org/doc/rfc5681/. 
  8. ↑ Corbet, Jonathan. "Increasing the TCP initial congestion window". LWN. https://lwn.net/Articles/427104/. 
  9. ↑ Nick O'Neill. "What's Making Your Site Go Slow? Could Be The Like Button". AllFacebook, 10 November 2010. Retrieved on 12 September 2012.
  10. ↑ Fall, Kevin; Sally Floyd (July 1996). "Simulation-based Comparisons of Tahoe, Reno and SACK TCP". Computer Communications Review 26 (3): 5–21. doi:10.1145/235160.235162. https://www.icir.org/floyd/papers/sacks.pdf. 
  11. ↑ 11.0 11.1 11.2 11.3 11.4 11.5 Abbasloo, S.; Xu, Y.; Chao, H. J. (2019). "C2TCP: A Flexible Cellular TCP to Meet Stringent Delay Requirements". IEEE Journal on Selected Areas in Communications 37 (4): 918–932. doi:10.1109/JSAC.2019.2898758. ISSN 0733-8716. 
  12. ↑ 12.0 12.1 12.2 12.3 Abbasloo, S.; Li, T.; Xu, Y.; Chao, H. J. (May 2018). "Cellular Controlled Delay TCP (C2TCP)". 2018 IFIP Networking Conference (IFIP Networking) and Workshops. pp. 118–126. doi:10.23919/IFIPNetworking.2018.8696844. ISBN 978-3-903176-08-9. Bibcode: 2018arXiv180702689A. 
  13. ↑ 13.0 13.1 13.2 13.3 Abbasloo et al. 2019.
  14. ↑ Cardwell, Neal; Cheng, Yuchung; Gunn, C. Stephen; Yeganeh, Soheil Hassas; Jacobson, Van (2016). "BBR: Congestion-Based Congestion Control". Queue 14 (5): 20–53. doi:10.1145/3012426.3022184. 
  15. ↑ Kurose & Ross 2008, p. 284.
  16. ↑ Kurose & Ross 2012, p. 277.
  17. ↑ VasanthiN., V.; SinghM., Ajith; Kumar, Romen; Hemalatha, M. (2011). "Evaluation of Protocols and Algorithms for Improving the Performance of TCP over Wireless/Wired Network". in Das, Vinu V; Thankachan, Nessy. Computational Intelligence and Information Technology. Communications in Computer and Information Science. 250. Springer. pp. 693–697. doi:10.1007/978-3-642-25734-6_120. ISBN 978-3-642-25733-9. 
  18. ↑ "Performance Analysis of TCP Congestion Control Algorithms". http://www.wseas.us/journals/cc/cc-27.pdf. 
  19. ↑ "DD-WRT changelog". http://www.dd-wrt.com/wiki/index.php/Changelog. 
  20. ↑ "Hybla home page". http://hybla.deis.unibo.it/. 
  21. ↑ Caini, Carlo; Firrincieli, Rosario (2004). "TCP Hybla: a TCP enhancement for heterogeneous networks" (in en). International Journal of Satellite Communications and Networking 22 (5): 547–566. doi:10.1002/sat.799. ISSN 1542-0973. https://onlinelibrary.wiley.com/doi/10.1002/sat.799. 
  22. ↑ Caini, C.; Firrincieli, R.; Lacamera, D. (2009). "Comparative Performance Evaluation of TCP Variants on Satellite Environments". 2009 IEEE International Conference on Communications. pp. 1–5. doi:10.1109/ICC.2009.5198834. https://ieeexplore.ieee.org/document/5198834. 
  23. ↑ V., Jacobson; R.T., Braden, TCP extensions for long-delay paths, doi:10.17487/RFC1072, RFC 1072, https://tools.ietf.org/html/rfc1072 
  24. ↑ Alrshah, M.A.; Othman, M.; Ali, B.; Hanapi, Z.M. (September 2015). "Agile-SD: A Linux-based TCP congestion control algorithm for supporting high-speed and short-distance networks". Journal of Network and Computer Applications 55: 181–190. doi:10.1016/j.jnca.2015.05.011. 
  25. ↑ Mathis, M.; Dukkipati, N.; Cheng, Y. (2013), Proportional Rate Reduction for TCP, doi:10.17487/RFC6937, RFC 6937, https://tools.ietf.org/html/rfc6937 
  26. ↑ Corbet, Jonathan. "LPC: Making the net go faster". https://lwn.net/Articles/458610/. 
  27. ↑ "Linux 3.2 - Linux Kernel Newbies". http://kernelnewbies.org/Linux_3.2#head-1c3e71416a9fdc2f59c1c251a97963f165302b6e. 
  28. ↑ 28.0 28.1 "BBR: Congestion-Based Congestion Control". https://research.google.com/pubs/pub45646.html. 
  29. ↑ Cheng, Yuchung; Cardwell, Neal; Yeganeh, Soheil Hassas; Jacobson, Van (3 July 2017). Delivery Rate Estimation. https://tools.ietf.org/html/draft-cheng-iccrg-delivery-rate-estimation-00#section-2.2. Retrieved 25 August 2017. 
  30. ↑ "TCP BBR congestion control comes to GCP – your Internet just got faster". https://cloudplatform.googleblog.com/2017/07/TCP-BBR-congestion-control-comes-to-GCP-your-Internet-just-got-faster.html. 
  31. ↑ "BBR congestion control [LWN.net"]. https://lwn.net/Articles/701165/. 
  32. ↑ "BBR update". https://datatracker.ietf.org/meeting/100/materials/slides-100-iccrg-a-quick-bbr-update-bbr-in-shallow-buffers. 
  33. ↑ "TCP and BBR". https://ripe76.ripe.net/presentations/10-2018-05-15-bbr.pdf. 
  34. ↑ "Experimental Evaluation of BBR Congestion Control". https://doc.tm.uka.de/2017-kit-icnp-bbr-authors-copy.pdf. 
  35. ↑ "A Performance Evaluation of TCP BBRv2". https://www.researchgate.net/publication/341781089. 
  36. ↑ 36.0 36.1 ((Google TCP BBR team)); ((Google QUIC BBR team)) (Jul 26, 2023). "BBRv3: Algorithm Bug Fixes and Public Internet Deployment". IETF 117: San Francisco. https://datatracker.ietf.org/meeting/117/materials/slides-117-ccwg-bbrv3-algorithm-bug-fixes-and-public-internet-deployment-00. 
  37. ↑ "Cellular Controlled Delay TCP (C2TCP)". https://wp.nyu.edu/c2tcp/. 
  38. ↑ Alrshah, M.A.; Al-Maqri, M.A.; Othman, M. (June 2019). "Elastic-TCP: Flexible Congestion Control Algorithm to Adapt for High-BDP Networks". IEEE Systems Journal 13 (2): 1336–1346. doi:10.1109/JSYST.2019.2896195. Bibcode: 2019ISysJ..13.1336A. 
  39. ↑ Abbasloo, Soheil (2019-06-03), GitHub - Soheil-ab/natcp, https://github.com/Soheil-ab/natcp, retrieved 2019-08-05 
  40. ↑ Yuan, Cao; Tan, Liansheng; Andrew, Lachlan L. H.; Zhang, Wei; Zukerman, Moshe (6 June 2008). "A generalized FAST TCP scheme". Computer Communications 31 (14): 3242–3249. doi:10.1016/j.comcom.2008.05.028. https://resolver.caltech.edu/CaltechAUTHORS:YUAcc08. 
  41. ↑ 41.0 41.1 "Rice Networks Group". http://www.ece.rice.edu/networks/TCP-LP/. 
  42. ↑ "TCP Veno: TCP Enhancement for Transmission over Wireless Access Networks". IEEE Journal on Selected Areas in Communication. https://www.ie.cuhk.edu.hk/fileadmin/staff_upload/soung/Journal/J3.pdf. 
  43. ↑ "XCP @ ISI". http://www.isi.edu/isi-xcp/. 
  44. ↑ "High speed TPC". http://www.csc.lsu.edu/~sjpark/cs7601/4-YeAH_TCP.pdf. 
  45. ↑ "Archived copy". http://media.cs.tsinghua.edu.cn/~multimedia/tcp-fit/. 
  46. ↑ Benaboud, H.; Berqia, A.; Mikou, N. (2002). "An analytical study of CANIT algorithm in TCP protocol". ACM SIGMETRICS Performance Evaluation Review 30 (3): 20. doi:10.1145/605521.605530. 
  47. ↑ Rouhani, Modjtaba (2010). "Nonlinear Neural Network Congestion Control Based on Genetic Algorithm for TCP/IP Networks". 2010 2nd International Conference on Computational Intelligence, Communication Systems and Networks. pp. 1–6. doi:10.1109/CICSyN.2010.21. ISBN 978-1-4244-7837-8. 
  48. ↑ Kanagarathinam, Madhan Raj; Singh, Sukhdeep; Sandeep, Irlanki; Roy, Abhishek; Saxena, Navrati (January 2018). "D-TCP: Dynamic TCP congestion control algorithm for next generation mobile networks". 2018 15th IEEE Annual Consumer Communications & Networking Conference (CCNC). pp. 1–6. doi:10.1109/CCNC.2018.8319185. ISBN 978-1-5386-4790-5. https://ieeexplore.ieee.org/document/8319185. 
  49. ↑ Kanagarathinam, Madhan Raj; Singh, Sukhdeep; Sandeep, Irlanki; Kim, Hanseok; Maheshwari, Mukesh Kumar; Hwang, Jaehyun; Roy, Abhishek; Saxena, Navrati (2020). "NexGen D-TCP: Next Generation Dynamic TCP Congestion Control Algorithm". IEEE Access 8: 164482–164496. doi:10.1109/ACCESS.2020.3022284. ISSN 2169-3536. Bibcode: 2020IEEEA...8p4482K. 
  50. ↑ Arun, Venkat; Balakrishnan, Hari (2018). "Copa: Practical Delay-Based Congestion Control for the Internet". 15th USENIX Symposium on Networked Systems Design and Implementation (NSDI 18): 329–342. ISBN 978-1-939133-01-4. https://www.usenix.org/conference/nsdi18/presentation/arun. 
  51. ↑ "tcp: make CUBIC the default congestion control mechanism". 13 September 2022. https://cgit.freebsd.org/src/commit/?id=bb1d472d79f7. 
  52. ↑ "Summary of Five New TCP Congestion Control Algorithms Project". 8 March 2011. http://forums.freebsd.org/showthread.php?t=22396. 
  53. ↑ "iTCP - Interactive Transport Protocol - Medianet Lab, Kent State University". http://www.medianet.kent.edu/itcp/main.html. 
  54. ↑ "Whitepaper: Zeta-TCP - Intelligent, Adaptive, Asymmetric TCP Acceleration". http://www.appexnetworks.com/Assets/PDF/ZetaTCP.pdf. 
  55. ↑ Lefteris Mamatas; Tobias Harks; Vassilis Tsaoussidis (January 2007). "Approaches to Congestion Control in Packet Networks". Journal of Internet Engineering 1 (1). http://utopia.duth.gr/~emamatas/jie2007.pdf. 
  56. ↑ "HighSpeed TCP". http://www.icir.org/floyd/hstcp.html. 
  57. ↑ "AIMD-FC Homepage". http://www.ccs.neu.edu/home/ladrian/abstract/aimdfc.html. 
  58. ↑ "Welcome to Network Research Lab". http://www.cs.ucla.edu/NRL/hpi/tcpw/. 
  59. ↑ "Equation-Based Congestion Control for Unicast Applications". http://www.icir.org/tfrc/. 
  60. ↑ Katabi, Dina; Handley, Mark; Rohrs, Charlie (2002). "Congestion control for high bandwidth-delay product networks". Proceedings of the 2002 conference on Applications, technologies, architectures, and protocols for computer communications. New York, New York, USA: ACM Press. p. 89. doi:10.1145/633025.633035. ISBN 1-58113-570-X. 
  61. ↑ "MaxNet -- Max-Min Fair, Stable Explicit Signalling Congestion Control". http://netlab.caltech.edu/maxnet/. 

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