1. New designs for Internet congestion control Damon Wischik (UCL) http://www.cs.ucl.ac.uk/staff/D.Wischik

2. Some Internet History 1974: First draft of TCP/IP “A protocol for packet network interconnection”, Vint Cerf and Robert Kahn 1983: ARPANET switches on TCP/IP 1986: Congestion collapse 1988: Congestion control for TCP “Congestion avoidance and control”, Van Jacobson “A Brief History of the Internet”, the Internet Society

3. Sizing router buffers SIGCOMM 2004 Abstract. All Internet routers contain buffers to hold packets during times of congestion. Today, the size of the buffers is determined by the dynamics of TCP's congestion control algorithm. In particular, the goal is to make sure that when a link is congested, it is busy 100% of the time; which is equivalent to making sure its buffer never goes empty. A widely used rule-of-thumb states that each link needs a buffer of size B = RTT*C, where RTT is the average round-trip time of a flow passing across the link, and C is the data rate of the link. For example, a 10Gb/s router linecard needs approximately 250ms*10Gb/s = 2.5Gbits of buffers; and the amount of buffering grows linearly with the line-rate. Such large buffers are challenging for router manufacturers, who must use large, slow, off-chip DRAMs. And queueing delays can be long, have high variance, and may destabilize the congestion control algorithms. In this paper we argue that the rule-of-thumb (B = RTT*C) is now outdated and incorrect for backbone routers. This is because of the large number of flows (TCP connections) multiplexed together on a single backbone link. Using theory, simulation and experiments on a network of real routers, we show that a link with N flows requires no more than B = (RTT*C)/  N, for long-lived or short-lived TCP flows. The consequences on router design are enormous: A 2.5Gb/s link carrying 10,000 flows could reduce its buffers by 99% with negligible difference in throughput; and a 10Gb/s link carrying 50,000 flows requires only 10Mbits of buffering, which can easily be implemented using fast, on-chip SRAM. Guido AppenzellerIsaac KeslassyNick McKeown Stanford UniversityStanford UniversityStanford University http://tiny-tera.stanford.edu/~nickm/papers/index.html

4. TCP if (seqno > _last_acked) { if (!_in_fast_recovery) { _last_acked = seqno; _dupacks = 0; inflate_window(); send_packets(now); _last_sent_time = now; return; } if (seqno < _recover) { uint32_t new_data = seqno - _last_acked; _last_acked = seqno; if (new_data < _cwnd) _cwnd -= new_data; else _cwnd=0; _cwnd += _mss; retransmit_packet(now); send_packets(now); return; } uint32_t flightsize = _highest_sent - seqno; _cwnd = min(_ssthresh, flightsize + _mss); _last_acked = seqno; _dupacks = 0; _in_fast_recovery = false; send_packets(now); return; } if (_in_fast_recovery) { _cwnd += _mss; send_packets(now); return; } _dupacks++; if (_dupacks!=3) { send_packets(now); return; } _ssthresh = max(_cwnd/2, (uint32_t)(2 * _mss)); retransmit_packet(now); _cwnd = _ssthresh + 3 * _mss; _in_fast_recovery = true; _recover = _highest_sent; } time [0-8 sec] bandwidth [0-100 kB/sec]

5. How TCP shares capacity sum of flow bandwidths time available bandwidth individual flow bandwidths

6. Macroscopic description of TCP Let x be the mean bandwidth of a flow [pkts/sec] Let RTT be the flow’s round-trip time [sec] Let p be the packet loss probability The TCP algorithm increases x at rate 1/RTT 2 [pkts/sec] and reduces x by x/2 for every packet loss average increase in rate = average decrease in rate: 1/RTT 2 = (p x) x/2

7. Macroscopic description Let x be the mean bandwidth of a flow [pkts/sec] Let RTT be the flow’s round-trip time [sec] Let p be the packet loss probability The TCP algorithm increases x at rate 1/RTT 2 [pkts/sec] and reduces x by x/2 for every packet loss average increase in rate = average decrease in rate: 1/RTT 2 = (p x) x/2 Consider a link with N identical flows Let NC be the capacity of the link [pkts/sec] packet loss ratio = fraction of work that exceeds service rate: p = (Nx-NC) + /Nx = (x-C) + /x

8. Fixed-point analysis C*RTT=4 pkts C*RTT=20 pkts C*RTT=100 pkts traffic intensity x/C log 10 of pkt loss probability

9. Teleological description Consider several TCP flows sharing a single link Let x r be the mean bandwidth of flow r [pkts/sec] Let y be the total bandwidth of all flows [pkts/sec] Let C be the total available capacity [pkts/sec] TCP and the network act so as to solve maximise  r U(x r ) - P(y,C) over x r  0 where y=  r x r x U(x)U(x) y P(y,C) C

10. Rate control in communication networks: shadow prices, proportional fairness and stability Journal of the Operational Research Society, 1998 F.P.Kelly, A.K.Maulloo, D.K.H.Tan Statistical Laboratory, Cambridge Abstract. This paper analyses the stability and fairness of two classes of rate control algorithm for communication networks. The algorithms provide natural generalizations to large-scale networks of simple additive increase/multiplicative decrease schemes, and are shown to be stable about a system optimum characterized by a proportional fairness criterion. Stability is established by showing that, with an appropriate formulation of the overall optimization problem, the network's implicit objective function provides a Lyapunov function for the dynamical system defined by the rate control algorithm. The network's optimization problem may be cast in primal or dual form: this leads naturally to two classes of algorithm, which may be interpreted in terms of either congestion indication feedback signals or explicit rates based on shadow prices. Both classes of algorithm may be generalized to include routing control, and provide natural implementations of proportionally fair pricing. http://www.statslab.cam.ac.uk/~frank/rate.html

11. Teleological description x little extra valued attached to high- bandwidth flows severe penalty for allocating too little bandwidth x U(x)U(x)

12. Teleological description x U(x)U(x) flows with large RTT are satisfied with little bandwidth flows with small RTT want more bandwidth

13. Teleological description y P(y,C) C no penalty unless links are overloaded

14. Teleological description Is this what we want the Internet to optimize? Does it make good use of the network? Can it deliver high bandwidth and good quality? Is it a fair allocation? Can we design a better allocation? x U(x)U(x) y C

15. Teleology & dynamics The network acts to solve an optimization problem. –We can choose which optimization problem, by changing the router & TCP’s code. But the network may or may not attain the solution! –To understand this, we need a dynamical description of TCP x U(x)U(x) y C

16. Dynamical description Consider a link with N flows and capacity NC and buffer N 1/2 B Let x t be the average bandwidth at time t Let p t be the packet loss probability at time t As N  we believe a mean-field limit holds.

17. Dynamical description Fluid-based Analysis of a Network of AQM Routers Supporting TCP Flows with an Application to RED SIGCOMM 2000 Vishal Misra, Wei-Bo Gong, Don Towsley Rate-based versus queue-based models of congestion control ACM Sigmetrics 2004 Supratim Deb, R. Srikant Mean field convergence of a rate model of multiple TCP connections through a buffer implementing RED To appear in Annals of Applied Probability David McDonald, Julien Reynier

18. Dynamical stability/instability For some values of C and RTT, the dynamical system is stable For others it is unstable and there are oscillations (i.e. the flows are partially synchronized) G.Raina and W. (2005) time arrival rate x/C

19. Illustration of instability Standard TCP, single bottleneck link, no AQM, service C=60 pkts/sec/flow, buffer B=170pkts, RTT=200 ms, #flows N=200 queue size [0-170pkts] flow bandwidths [0-35pkts/RTT] time [80-90sec]

20. Instability plot C*RTT=4 pkts C*RTT=20 pkts C*RTT=100 pkts traffic intensity x/C log 10 of pkt loss probability

21. Alternative buffer-sizing rules Rule-of-thumb buffer size buffer = bandwidth*delay Rule-of-thumb buffer size, with RED buffer=bandwidth*delay, drop packets selectively before the buffer fills Small buffers buffer=50 pkts Small buffers, ScalableTCP buffer=50 pkts, revised rate-increase rule

22. Scalable TCP: improving performance in highspeed wide area networks SIGCOMM CCR 2003 Tom Kelly CERN -- IT division Abstract. TCP congestion control can perform badly in highspeed wide area networks because of its slow response with large congestion windows. The challenge for any alternative protocol is to better utilize networks with high bandwidth-delay products in a simple and robust manner without interacting badly with existing traffic. Scalable TCP is a simple sender-side alteration to the TCP congestion window update algorithm. It offers a robust mechanism to improve performance in highspeed wide area networks using traditional TCP receivers. Scalable TCP is designed to be incrementally deployable and behaves identically to traditional TCP stacks when small windows are sufficient. The performance of the scheme is evaluated through experimental results gathered using a Scalable TCP implementation for the Linux operating system and a gigabit transatlantic network. The preliminary results gathered suggest that the deployment of Scalable TCP would have negligible impact on existing network traffic at the same time as improving bulk transfer performance in highspeed wide area networks. http://www-lce.eng.cam.ac.uk/~ctk21/scalable/

23. Teleological description x U(x)U(x) y P(y,C) C ScalableTCP gives more weight to high- bandwidth flows With small buffers, the network likes to run with slightly lower utilization

24. Conclusion The network acts to solve an optimization problem. –We can choose which optimization problem, by choosing the right buffer size & changing TCP’s code. It might not attain the solution –In order to make sure the network is stable, we need to choose the buffer size & TCP code carefully. PROPOSAL –Buffers of size 20 packets in core routers keep utilization below 90%; eliminate delay and jitter –ScalableTCP able to deliver higher bandwidth than TCP