# CUBIC TCP

CUBIC is an implementation of TCP with an optimized congestion control algorithm for high bandwidth networks with high latency (LFN: long fat networks).[1][2]

CUBIC TCP is implemented and used by default in Linux kernels 2.6.19 and above, as well as Windows 10.1709 Fall Creators Update, and Windows Server 2016 1709 update.[3]

## Characteristics

It is a less aggressive and more systematic derivative of BIC TCP, in which the window size is a cubic function of time since the last congestion event, with the inflection point set to the window size prior to the event. Because it is a cubic function, there are two components to window growth. The first is a concave portion where the window size quickly ramps up to the size before the last congestion event. Next is the convex growth where CUBIC probes for more bandwidth, slowly at first then very rapidly. CUBIC spends a lot of time at a plateau between the concave and convex growth region which allows the network to stabilize before CUBIC begins looking for more bandwidth.[4]

Another major difference between CUBIC and standard TCP flavors is that it does not rely on the cadence of RTTs to increase the window size.[5] CUBIC's window size is dependent only on the last congestion event. With standard TCP, flows with very short round-trip delay times (RTTs) will receive ACKs faster and therefore have their congestion windows grow faster than other flows with longer RTTs. CUBIC allows for more fairness between flows since the window growth is independent of RTT.

## Algorithm

CUBIC increases its window to be real-time dependent, not RTT dependent like BIC. The calculation for cwnd (congestion window) is simpler than BIC, too.

Define the following variables:

 β:     Multiplicative decrease factor
wmax:   Window size just before the last reduction
T:     Time elapsed since the last window reduction
C:     A Scaling constant
cwnd:  The congestion window at the current time


Then cwnd can be modeled by:

${\displaystyle {\begin{array}{lcr}cwnd\ =\ C(T-K)^{3}+w_{max}\\where\ K={\sqrt[{3}]{\frac {w_{max}\beta }{C}}}\end{array}}}$