ISCC2002 July 4, Adaptive Explicit Congestion Notification (AECN) Zici Zheng and Robert Kinicki Worcester Polytechnic Institute Computer Science Department Worcester, MA USA

ISCC2002 July 4, Outline Motivation for AECNMotivation for AECN Performance MetricsPerformance Metrics Random Early Detection (RED) and ECN RoutersRandom Early Detection (RED) and ECN Routers Topology and Experimental ProceduresTopology and Experimental Procedures RED and ECN ResultsRED and ECN Results AECN ResultsAECN Results ConclusionsConclusions

ISCC2002 July 4, Motivation for Adaptive ECN Congestion is still an Internet problem.Congestion is still an Internet problem. Researchers advocate Active Queue Management (AQM) techniques such as RED and ECN for congestion control.Researchers advocate Active Queue Management (AQM) techniques such as RED and ECN for congestion control. RED is difficult to tune and unfair.RED is difficult to tune and unfair. ECN is better when it marks.ECN is better when it marks.

ISCC2002 July 4, Motivation for Adaptive ECN Is ECN also unfair to heterogeneous flows?Is ECN also unfair to heterogeneous flows? What happens when there are many flows?What happens when there are many flows? Previously shown that ECN performs better with a higher mark probability when there are many flows.Previously shown that ECN performs better with a higher mark probability when there are many flows. Adaptive ECN can improve goodput and fairness.Adaptive ECN can improve goodput and fairness.

ISCC2002 July 4, Performance Metrics throughput (Mbps) - the aggregate rate of packets generated by all sources.throughput (Mbps) - the aggregate rate of packets generated by all sources. goodput (Mbps) - the rate at which packets arrive at the receiver. Goodput differs from throughput in that retransmissions are excluded from goodput.goodput (Mbps) - the rate at which packets arrive at the receiver. Goodput differs from throughput in that retransmissions are excluded from goodput. delay (sec) - the time required to transmit a packet from source node to receiver node.delay (sec) - the time required to transmit a packet from source node to receiver node.

ISCC2002 July 4, Performance Metrics Jain’s fairnessJain’s fairness –For any given set of user throughputs (), the fairness index to the set is defined: –For any given set of user throughputs (x 1, x 2, …, x n ), the fairness index to the set is defined: f (x 1, x 2, …, x n ) = f (x 1, x 2, …, x n ) = max-min fairnessmax-min fairness –A flow rate x is max-min fair if any rate x cannot be increased without decreasing some y which is smaller than or equal to x. To satisfy the min-max fairness criteria, the smallest throughput rate must be as large as possible. “visual” max-min fairness“visual” max-min fairness –the visual gap between the smallest and the largest goodput

ISCC2002 July 4, RED Routers Random Early Detection (RED) detects congestion “early” by maintaining an exponentially-weighted average queue size.Random Early Detection (RED) detects congestion “early” by maintaining an exponentially-weighted average queue size. RED probabilistically drops packets before the queue overflows to signal congestion to TCP sources.RED probabilistically drops packets before the queue overflows to signal congestion to TCP sources. RED attempts to avoid global synchronization and bursty packet drops.RED attempts to avoid global synchronization and bursty packet drops.

ISCC2002 July 4, ECN Routers Explicit Congestion Notification (ECN), a RED variant, marks packets to signal congestion.Explicit Congestion Notification (ECN), a RED variant, marks packets to signal congestion. ECN must be supported by both TCP senders and receivers.ECN must be supported by both TCP senders and receivers. ECN-compliant TCP senders initiate their congestion avoidance algorithm after receiving marked ACK packets from the TCP receiver.ECN-compliant TCP senders initiate their congestion avoidance algorithm after receiving marked ACK packets from the TCP receiver. Packets from non-ECN compliant flows are treated by the RED mechanism in the ECN router.Packets from non-ECN compliant flows are treated by the RED mechanism in the ECN router.

ISCC2002 July 4, RED and ECN Router Parameters avg q :: average queue size avg = (1-w) * avg + w* instantaneous queue size avg q = (1-w q ) * avg q + w q * instantaneous queue size w q :: weighting factor <= w q <= min th :: average queue length threshold for triggering probabilistic drops/marks. max th :: average queue length threshold for triggering forced drops max p :: maximum dropping/marking probability p b = max p * (avg – min th ) / (max th – min th ) p b = max p * (avg q – min th ) / (max th – min th ) p a = p b / (1 – count * p b ) p a = p b / (1 – count * p b ) buffer_size :: the size of the router queue in packets

ISCC2002 July 4, RED/ECN Router Mechanism 1 0 Min-threshold Max-threshold Dropping/Marking Probability Queue Size max p Average Queue Length (avg q )

ISCC2002 July 4, Simulation Topology 10mbps, 5ms 20 m s 45ms : Source : Sink Router F1F1 FmFm A1A1 AmAm R1R1 RmRm ms 90 Mbps RTTs: (200ms, 100ms, 50ms)

ISCC2002 July 4, Experimental Procedures and Parameter Settings Experimental Procedures and Parameter Settings 100 second ns-2 simulations100 second ns-2 simulations n flows divided equally among three flow types (fragile, average, robust) (n = 3m)n flows divided equally among three flow types (fragile, average, robust) (n = 3m) aggregate flow capacity fixed at 90 Mbpsaggregate flow capacity fixed at 90 Mbps staggered start of half the flows (0 sec, 2 sec)staggered start of half the flows (0 sec, 2 sec) fixed RED/ECN/AECN and TCP parameters for all runsfixed RED/ECN/AECN and TCP parameters for all runs –w q = –min th = 10 ; max th = 30 ; –buffer_size = 50 packets –TCP max_send_window_size = 64 packets

ISCC2002 July 4, Figure 2: RED and ECN Goodput

ISCC2002 July 4, Figure 3: RED and ECN Fairness

ISCC2002 July 4, Figure 4: RED and ECN Goodput 60 flows, max p = 0.5

ISCC2002 July 4, Flows, max p = 0.5 ECN Marks ECN Drops RED Drops ECN has almost no drops !!

ISCC2002 July 4, Flows, max p = 0.5 ECN Marks ECN Drops RED Drops ECN drops are now significant!

ISCC2002 July 4, RED/ECN Conclusions ECN better than RED especially if ECN max p set higher.ECN better than RED especially if ECN max p set higher. RED/ECN unfair to fragile and average flows => adaptive max p needed.RED/ECN unfair to fragile and average flows => adaptive max p needed. ECN needs to avoid drops when there are many flows.ECN needs to avoid drops when there are many flows.

ISCC2002 July 4, Adaptive ECN flow queues Packet de-queue Packet en-queue Router Queue Router Queue Robust flow Queue Robust flow Queue Average flow Queue Average flow Queue Fragile flow Queue Fragile flow Queue Robust packet Average packetFragile packet

ISCC2002 July 4, AECN Algorithm If avg q >= max th, drop incoming packet ; {same as ECN} If avg q is below max th, Add incoming packet to the router queue ; Add incoming packet to the router queue ; Determine whether flow is robust, fragile or average Determine whether flow is robust, fragile or average and add to the appropriate flow queue ; and add to the appropriate flow queue ; If avg q is between min th and max th, Determine mark probability (max p ) Determine mark probability (max p ) and probabilistically mark the first unmarked packet and probabilistically mark the first unmarked packet at the front of the appropriate flow queue ; at the front of the appropriate flow queue ;

ISCC2002 July 4, Determine Mark Probability (max p ) Robust Flow:max p = min{ (base-max p *  ), 1}; Average Flow:max p = base-max p ; Fragile Flow: max p = base-max p /  ;

ISCC2002 July 4, How to choose  and  ? For this research, assume  = For this research, assume  =  Goal: achieve fairness for fragile and average flowsGoal: achieve fairness for fragile and average flows Pay attention to number of flowsPay attention to number of flows

ISCC2002 July 4, Figure 5: AECN Goodput 60 flows, base_max p = 0.5 Alpha = 2.5 is fairest !!

ISCC2002 July 4, Figure 6: AECN Jain’s Fairness 60 flows, base_max p = 0.5 Alpha = 2.5 is fairest !!

ISCC2002 July 4, Figure 7: AECN Goodput 120 flows, base_max p = 0.8

ISCC2002 July 4, Figure 8: AECN Jain’s Fairness 120 flows, base_max p = 0.8 Alpha = 2.5 is fairest !!

ISCC2002 July 4, Figure 9: AECN Goodput base_max p = 0.5,  =  = 2.5

ISCC2002 July 4, Figure 10: AECN Goodput base_max p = 0.8,  =  = 2.5

ISCC2002 July 4, Figure 11: Jain’s Fairness base_max p = 0.5,  =  = 2.5

ISCC2002 July 4, Figure 12: Jain’s Fairness base_max p = 0.8,  =  = 2.5

ISCC2002 July 4, AECN Conclusions AECN provides higher goodput when there are a larger number of flows.AECN provides higher goodput when there are a larger number of flows. Both “visual max-min fairness” and Jain’s fairness are better for AECN.Both “visual max-min fairness” and Jain’s fairness are better for AECN. Adapting to both RTT and number of flows is shown to be important.Adapting to both RTT and number of flows is shown to be important.  =  = 2.5 good settings for these experiments.  =  = 2.5 good settings for these experiments.

ISCC2002 July 4, Future Work Find method to adjust max p as function of RTT “source hint” to eliminate flow classes => see Chablis paper (Choong-Soo Lee, Mark Claypool, and Robert Kinicki. Chablis - Achieving Fair Bandwidth Allocation with Priority Dropping Based on Round Trip Time, WPI-CS-TR-02-19, May 2002, ftp://ftp.cs.wpi.edu/pub/techreports/02-19.ps.gz )Find method to adjust max p as function of RTT “source hint” to eliminate flow classes => see Chablis paper (Choong-Soo Lee, Mark Claypool, and Robert Kinicki. Chablis - Achieving Fair Bandwidth Allocation with Priority Dropping Based on Round Trip Time, WPI-CS-TR-02-19, May 2002, ftp://ftp.cs.wpi.edu/pub/techreports/02-19.ps.gz ) Include flow count at router in determining drop probability.Include flow count at router in determining drop probability. Avoid ECN drops when avg q gets close to max th.Avoid ECN drops when avg q gets close to max th.