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1 EE 122:TCP Congestion Control Ion Stoica TAs: Junda Liu, DK Moon, David Zats (Materials with thanks to Vern Paxson,

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Presentation on theme: "1 EE 122:TCP Congestion Control Ion Stoica TAs: Junda Liu, DK Moon, David Zats (Materials with thanks to Vern Paxson,"— Presentation transcript:

1 1 EE 122:TCP Congestion Control Ion Stoica TAs: Junda Liu, DK Moon, David Zats http://inst.eecs.berkeley.edu/~ee122/ (Materials with thanks to Vern Paxson, Jennifer Rexford, and colleagues at UC Berkeley)

2 2 Goals of Today’s Lecture Principles of congestion control Learning that congestion is occurring Adapting to alleviate the congestion TCP congestion control Additive-increase, multiplicative-decrease (AIMD) How to begin transmitting: Slow Start

3 3 What We Know We know: How to process packets in a switch How to route packets in the network How to send packets reliably We don’t know: How fast to send

4 4 It’s Not Just The Sender & Receiver Flow control keeps one fast sender from overwhelming a slow receiver Congestion control keeps a set of senders from overloading the network Three congestion control problems: Adjusting to bottleneck bandwidth Without any a priori knowledge Could be a Gbps link; could be a modem Adjusting to variations in bandwidth Sharing bandwidth between flows

5 5 Congestion is Unavoidable Two packets arrive at the same time The node can only transmit one … and either buffers or drops the other If many packets arrive in a short period of time The node cannot keep up with the arriving traffic … and the buffer may eventually overflow

6 6 Congestion Collapse Definition: Increase in network load results in a decrease of useful work done Due to: Undelivered packets Packets consume resources and are dropped later in network Spurious retransmissions of packets still in flight Unnecessary retransmissions lead to more load! Pouring gasoline on a fire Mid-1980s: Internet grinds to a halt Until Jacobson/Karels (Berkeley!) devise TCP congestion control

7 7 View from a Single Flow Knee – point after which Throughput increases very slowly Delay increases quickly Cliff – point after which Throughput starts to decrease very fast to zero (congestion collapse) Delay approaches infinity Load Throughput Delay kneecliff congestion collapse packet loss

8 8 General Approaches Send without care Many packet drops (1) Reservations Pre-arrange bandwidth allocations Requires negotiation before sending packets Low utilization (2) Pricing Don’t drop packets for the high-bidders Requires payment model

9 9 General Approaches (cont’d) (3) Dynamic Adjustment Probe network to test level of congestion Speed up when no congestion Slow down when congestion Suboptimal, messy dynamics, simple to implement All three techniques have their place But for generic Internet usage, dynamic adjustment is the most appropriate Due to pricing structure, traffic characteristics, and good citizenship

10 10 TCP Congestion Control TCP connection has window Controls number of unacknowledged packets Sending rate: ~Window/RTT Vary window size to control sending rate

11 11 Sizing the Windows cwnd (Congestion Windows) How many bytes can be sent without overflowing routers Computed by congestion control algorithm AdvertisedWindow How many bytes can be sent without overflowing the sender Determined by the receiver

12 12 EffectiveWindow Limits how much data can be in transit Implemented as # of bytes Described as # packets (segments) in this lecture EffectiveWindow = MaxWindow – (LastByteSent – LastByteAcked) MaxWindow = min(cwnd, AdvertisedWindow) LastByteAcked LastByteSent sequence number increases MaxWindow EffectiveWindow

13 13 Two Basic Components Detecting congestion Rate adjustment algorithm Depends on congestion or not Three subproblems within adjustment problem Finding fixed bandwidth Adjusting to bandwidth variations Sharing bandwidth

14 14 Detecting Congestion Packet dropping is best sign of congestion Delay-based methods are hard and risky How do you detect packet drops? ACKs TCP uses ACKs to signal receipt of data ACK denotes last contiguous byte received Actually, ACKs indicate next segment expected Two signs of packet drops No ACK after certain time interval: time-out Several duplicate ACKs (ignore for now)

15 15 Rate Adjustment Basic structure: Upon receipt of ACK (of new data): increase rate Upon detection of loss: decrease rate But what increase/decrease functions should we use? Depends on what problem we are solving

16 16 Problem #1: Single Flow, Fixed BW Want to get a first-order estimate of the available bandwidth Assume bandwidth is fixed Ignore presence of other flows Want to start slow, but rapidly increase rate until packet drop occurs (“slow-start”) Adjustment: cwnd initially set to 1 cwnd++ upon receipt of ACK

17 17 Slow-Start cwnd increases exponentially: cwnd doubles every time a full cwnd of packets has been sent Each ACK releases two packets Slow-start is called “slow” because of starting point segment 1 cwnd = 1 cwnd = 2 segment 2 segment 3 cwnd = 4 segment 4 segment 5 segment 6 segment 7 cwnd = 8 cwnd = 3

18 18 5 Minute Break Questions Before We Proceed?

19 19 Problems with Slow-Start Slow-start can result in many losses Roughly the size of cwnd ~ BW*RTT Example: At some point, cwnd is enough to fill “pipe” After another RTT, cwnd is double its previous value All the excess packets are dropped! Need a more gentle adjustment algorithm once have rough estimate of bandwidth

20 20 Problem #2: Single Flow, Varying BW Want to be able to track available bandwidth, oscillating around its current value Possible variations: (in terms of RTTs) Multiplicative increase or decrease: cwnd  a*cwnd Additive increase or decrease: cwnd  cwnd + b Four alternatives: AIAD: gentle increase, gentle decrease AIMD: gentle increase, drastic decrease MIAD: drastic increase, gentle decrease (too many losses) MIMD: drastic increase and decrease

21 21 Problem #3: Multiple Flows Want steady state to be “fair” Many notions of fairness, but here all we require is that two identical flows end up with the same bandwidth This eliminates MIMD and AIAD AIMD is the only remaining solution!

22 22 Buffer and Window Dynamics No congestion  x increases by one packet/RTT every RTT Congestion  decrease x by factor 2 AB C = 50 pkts/RTT x

23 23 AIMD Sharing Dynamics AB x1x1 DE No congestion  rate increases by one packet/RTT every RTT Congestion  decrease rate by factor 2 Rates equalize  fair share x2x2

24 24 AIAD Sharing Dynamics AB x1x1 DE No congestion  x increases by one packet/RTT every RTT Congestion  decrease x by 1 x2x2

25 25 Efficient Allocation: Challenges of Congestion Control Too slow Fail to take advantage of available bandwidth  underload Too fast Overshoot knee  overload, high delay, loss Everyone’s doing it May all under/over shoot  large oscillations Optimal:  x i =X goal Efficiency = 1 - distance from efficiency line User 1: x 1 User 2: x 2 Efficiency line 2 user example overload underload

26 26 Example User 1: x 1 User 2: x 2 fairness line efficiency line 1 1 Total bandwidth 1 Inefficient: x 1 +x 2 =0.7 (0.2, 0.5) Congested: x 1 +x 2 =1.2 (0.7, 0.5) Efficient: x 1 +x 2 =1 Not fair (0.7, 0.3) Efficient: x 1 +x 2 =1 Fair (0.5, 0.5)

27 27 MIAD User 1: x 1 User 2: x 2 fairness line efficiency line (x 1h,x 2h ) (x 1h -a D,x 2h -a D ) (b I (x 1h -a D ), b I (x 2h -a D )) Increase: x*b I Decrease: x - a D Does not converge to fairness Does not converges to efficiency

28 28 AIAD User 1: x 1 User 2: x 2 fairness line efficiency line (x 1h,x 2h ) (x 1h -a D,x 2h -a D ) (x 1h -a D +a I ), x 2h -a D +a I )) Increase: x + a I Decrease: x - a D Does not converge to fairness Does not converge to efficiency

29 29 MIMD User 1: x 1 User 2: x 2 fairness line efficiency line (x 1h,x 2h ) (b d x 1h,b d x 2h ) (b I b D x 1h, b I b D x 2h ) Increase: x*b I Decrease: x*b D Does not converge to fairness Converges to efficiency iff

30 30 (b D x 1h +a I, b D x 2h +a I ) AIMD User 1: x 1 User 2: x 2 fairness line efficiency line (x 1h,x 2h ) (b D x 1h,b D x 2h ) Increase: x+a D Decrease: x*b D Converges to fairness Converges to efficiency Increments smaller as fairness increases

31 31 Implementing AIMD After each ACK Increment cwnd by 1/cwnd (cwnd += 1/cwnd) As a result, cwnd is increased by one only if all segments in a cwnd have been acknowledged But need to decide when to leave slow-start and enter AIMD  Use ssthresh variable

32 32 Slow Start/AIMD Pseudocode Initially: cwnd = 1; ssthresh = infinite; New ack received: if (cwnd < ssthresh) /* Slow Start*/ cwnd = cwnd + 1; else /* Congestion Avoidance */ cwnd = cwnd + 1/cwnd; Timeout: /* Multiplicative decrease */ ssthresh = cwnd/2; cwnd = 1;

33 33 The big picture (with timeouts) Time cwnd Timeout Slow Start AIMD ssthresh Timeout Slow Start AIMD

34 34 Summary Congestion is inevitable Internet does not reserve resources in advance TCP actively tries to grab capacity Congestion control critical for avoiding collapse AIMD: Additive Increase, Multiplicative Decrease Congestion detected via packet loss (fail-safe) Slow start to find initial sending rate & to restart after timeout Next class Advanced congestion control


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