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Cubic
- 1. CUBIC: A NewTCP- Friendly High-Speed TCP Variant S Ha, I Rhee, L Xu - ACM SIGOPS Operating Systems Review, 2008 Presenter: Deawoo Kim LANADA. KAIST 1
- 2. TCP Congestion control •TCP seeks to • Achieve high utilization • Without congestion • Source calculates cwnd from indication of network congestion • Congestion indications • Losses • Delay • Marks 2
- 3. Window Flow Control •W packets transmitted per RTT • Source rate = • If W too small, then rate « capacity • If W too big, then rate > capacity => congestion 3
- 4. TCP Reno (Jacobson1990) 4
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- 6. Wikipedia: CUBIC TCP •CUBIC is an implementation of TCP with an optimized congestion control algorithm for high bandwidth networks with high latency 1. … the window is a cubic function of time since the last congestion event. Scalable, stable 2. CUBIC does not rely on the receipt of ACKs to increase the window size. CUBIC's window size is dependent only on the last congestion event. • Standard TCP, flows with very short 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. 6
- 7. Bandwidth and DelayProduct (BDP) • Network feature – BW, delay product (BDP) • Total number of packet needed in flight while keeping the BW fully utilized • BDP(capacity in bits) = path bandwidth (bps) * round-trip time(s) • Internet evolves to include many very high speed and long distance network paths • These networks are characterized by large BDP Source Destination Delay (RTT) Bandwidth Fully-utilized Under-utilized BDP 7
- 8. Under-utilization in LargeBDP (example) • Network environment • BW : 10 Gbps • RTT : 100ms • Packet : 1250 bytes • BDP of the path : 100,000 packets • TCP grow its window from mid-point of BDP (50,000 packets) • After 50,000 RTT, fully-utilized (100,000packets) (5,000 sec, 1.4hour) • If flow finish before 1.4 hour then under-utilization 8
- 9. Legacy TCP • 1.Multiplicative decrease • 2. Growth of CWND depends on RTT Time cwnd CA TD ssthresh TD TD TD Wm CA CA CA Large RTT 9
- 10. Related work • STCP(Scalable TCP) • Recovery time from loss events be constant regardless of the window size -> scalable • HSTCP (HighSpeed TCP) • 기본적으로 AIMD • Window size가 특정 threshold 넘으면, increase factor 증가, decrease factor 감소 • TCP-Vegas • δ < 𝛼 : path is not congested -> increase sending rate • δ > 𝛽 : congestion -> reduce sending rate • δ : difference btw expected throughput and actual throughput • 𝛼 : low threshold • 𝛽 : upper threshold • HTCP • Growth function is function of elapsed time (indep. RTT) • Decrease factor is adjusted to be proportional to the queue size 10
- 11. Abstract • CUBIC • Congestioncontrol protocol for TCP • Default TCP algorithm in Linux • Modify linear window growth function -> cubic function • Goal 1. Improve the scalability of TCP over fast and long distance networks 2. Equitable BW allocation among flows with different RTT 3. Stable : keep the CW much longer at the saturation point 4. TCP friendliness 11
- 12. BIC-TCP • Window growthfunction : simply a logarithmic concave function • Stable and Scalable • How does it work? • Binary search • Window grows to the mid-point of max and min • Additive increasing • Max probing • Feature • Far from the saturation point : aggressive increase CWND • Close to saturation point : slowly increase CWND • Overshoot occurs very small 12
- 13. BIC-TCP Algorithm Packet loss event Wmax Wmin= β*Wmax midpoint = (Wmin + Wmax)/2 Wmin – midpoint > Smax Wmin + SmaxWmin midpoint = (Wmin + Wmax)/2 Wmin + Smax Wmin Additive Increase midpoint = (Wmin + Wmax)/2 Wmin + Smin Wmin (Wmin – midpoint) < Smin Binary Search Wmax + Smin Wmax + Smin Wmax +Smax Slow Start Wmax + 2Smax Wmax + 3Smax Additive Inc. Max Probing 13
- 14. BIC-TCP • Additive increasing •Jumping to the midpoint can be too much increase within one RTT • Binary search algorithm • Stable • Max probing • Find the new saturation point if it has increased 14
- 15. New Window GrowthFunction • BIC-TCP • 장점 • Scalability in high speed networks • Stability with low window oscillations • 단점 • Growth function can be too aggressive for TCP for short RTT or low speed networks (RTT-fairness) • Difference phase (binary search, max probing, 𝑆 𝑚𝑎𝑥, 𝑆 𝑚𝑖𝑛) complexity • New window growth function 필요 • BIC-TCP 장점 취함 • Simple • TCP friendliness • RTT-fairness 15
- 16. Introduction • CUBIC • Nextversion of BIC-TCP • Window growth -> cubic function • cubic function – Incidental, out of convenience • In mathematics, a cubic function is a function of the form • The window growth function of CUBIC • 𝐶 : CUBIC parameter • 𝑡 : elapsed time from the last window reduction • 𝐾 : time period take to 𝑊𝑚𝑎𝑥 16
- 17. TCP CUBIC Packet loss event Time SteadyState Behavior Max Probing Wmax Around Wmax, window growth almost becomes zeroFast growth upon reduction Cubic starts probing for more Bandwidth 17
- 18. RTT-fairness • Window growthdepends only on the real time(congestion epoch) between two consecutive congestion events • Independent of RTT BIC-TCPCUBIC Large RTT Small RTT 18
- 19. TCP-friendliness • Short RTT– window growth rate slower than TCP standards • Current wnd in CUBIC < window size of standard TCP at time 𝑡 • Set cwnd as Wtcp(t) (Standard TCP) • Improve convergence speed of CUBIC • New flow join -> existing flow give up BW • 𝑊𝐿𝑎𝑠𝑡 𝑚𝑎𝑥 > 𝑐𝑤𝑛𝑑 -> reducing 𝑊𝑚𝑎𝑥 further 19 Fast Convergence
- 20. CUBIC window growthfunction • Congestion avoidance basic • Compute the window growth rate during next RTT period • Set 𝑊(𝑡 + 𝑅𝑇𝑇) as target congestion window • 3 modes • TCP-friendly region • Concave region • Convex region • Multiplicative decrease of cwnd factor of 𝛽 20
- 21. TCP Cubic Advantages •Good RTT fairness • Growth dominated by t, competing flows have same t after synchronized packet loss • Real-time dependent • Similar to BIC but linear increases are time dependent • Does not depend on ACK’s like TCP/ Reno • Scalability and stability • Cubic increases window to Wmax quickly and keeps it there longer • High utilization in large BDP • Scalability • Independent RTT 21
- 22. TCP Cubic Drawbacks •The speed to react • It can be sluggish to find the new saturation point if the saturation point has increased far beyond the last one • Slow Convergence • Flows with higher cwnd are more aggressive initially • Prolonged unfairness between flows 22
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- 24. Fairness to standard TCP •Standard TCP performs well • Small BDP • Short RTT 24
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- 26. BIC Algorithm while (cwnd!= Wmax){ If ((Wmin – midpoint) > Smax) cwnd = cwnd + Smax else If ((Wmin – midpoint) < Smin) cwnd = Wmax else cwnd = midpoint If (no packet loss) Wmin = cwnd else Wmin = β*cwnd Wmax = cwnd midpoint = (Wmax + Wmin)/2 } (Additive Increase) (Binary Search) 26 while (cwnd >= Wmax){ If (cwnd < Wmax + Smax) cwnd = cwnd + Smin else cwnd = cwnd + Smax If (packet loss) Wmin = β*cwnd Wmax = cwnd } Max Probing
- 27. CUBIC window growthfunction • Window growth function of CUBIC is a cubic function • CUBIC use both concave and convex for window size • Details of CUBIC • Loss event • Register 𝑊𝑚𝑎𝑥 loss 발생한 지점 • Multiplicative decrease of cwnd factor of 𝛽 (decrease constant) • Start to increase the window using concave profile of the cubic function • Plateau at 𝑊𝑚𝑎𝑥, concave growth continue until the window size becomes 𝑊𝑚𝑎𝑥 • Cubic function turn into convex profile (max probing) 27
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- 30. TCP Reno (Jacobson1988) Fast Recovery • Motivation: prevent ‘pipe’ from emptying after fast retransmit • Idea: each dupACKrepresents a packet having left the pipe • Enter CA after 3 dupACKs(Fast Retransmit/Fast Recovery) • Set ssthresh←cwnd/2 • Set cwnd←ssthresh • Enter SS after timeout • Set ssthresh←cwnd/2 • Set cwnd←1 30
Editor's Notes
- #9 (Length of flows is much shorter than the time TCP grows its windows to the full size of the BDP of a path)
- #12 CUBIC Congestion control protocol for TCP Default TCP algorithm in Linux 특징 : Modify linear window growth function -> cubic function (뭘 어떻게 왜 바꾸겠다는거지?) 목적 : improve the scalability of TCP over fast and long distance networks (-얘네들 특징이 뭐길래?) -> BDP가 크다 -> under-utilzation Equitable BW allocation among flows with different RTT 어떻게? Window growth – independent of RTT (이건 무슨말?) Flow grow congestion window at the same rate Saturation point 다가가기 전엔 aggressive increase window size, 다가가면 slowly Scalable – when BW and delay is large (왜그럼?) Stable fair