Texas A & M University1 Impact of bandwidth-delay product and non-responsive flows on the performance of queue management schemes Zhili ZhaoA.L.NarasimhaReddy Department of Electrical Engineering Texas A&M University June , ICC

Texas A & M University2 Agenda  Motivation Performance Evaluation Results & Analysis Discussion

Texas A & M University3 Current Network Workload Traffic composition in current network –~60% Long-term TCP (LTRFs), ~30% Short- term TCP (STFs), ~10% Long-term UDP (LTNRFs) Nonresponsive traffic is increasing –STF + LTNRF Link capacities are increasing What is the consequence?

Texas A & M University4 The Trends Long-term UDP traffic increases –Multimedia applications –Impact on TCP applications from the non- responsive UDP traffic UDP arrival rate UDP Goodput TCP Goodput

Texas A & M University5 The Trends (cont’d) Link capacity increases –Larger buffer memory required if current rules followed (buffer = BW * delay product) Increasing queuing delay Larger memories constrain router speeds What if smaller buffers used in the future?

Texas A & M University6 Overview of Paper Study buffer management policies in the light of –Increasing Non-responsive loads –Increasing link speeds Policies studied –Droptail –RED –RED with ECN

Texas A & M University7 Queue Management Schemes RED RED-ECN (RED w/ ECN enabled) Droptail P P max Min th 1 Max th AvgQlen P1P1 Q1Q1 0

Texas A & M University8 Agenda Motivations  Performance Evaluation Results & Analysis Discussion

Texas A & M University9 Performance Evaluation Different workloads w/ higher non- responsive loads: 60% Different link capacities: 5Mb, 35Mb, 100Mb Different buffer sizes: 1/3 or 1 or 3 * 1 BWDP * Buffer size is in the unit of packet (1 packet = 1000 bytes) Multiple of BWDP Link Capacity (Mb) /

Texas A & M University10 Workload Characteristics TCP(FTP): LTRFs UDP(CBR): LTNRFs –60%, 55%, 30% –1Mbps or 0.5Mbps Short-term TCP: STFs –0%, 5%, 30% –10packets/10s on average

Texas A & M University11 Number of flows under 35Mb link contributing to 60% non-responsive load * Each LTRNF sends at 1Mbps * Numbers of flows under 5Mb and 100Mb links are scaled accordingly Workload Characteristics (cont’d) STF Load 35 Mb Link # of LTRFs# of STFs# of LTNRFs 0% % %

Texas A & M University12 Performance Metrics Realized TCP throughput Average queuing delay Link utilization Standard deviation of queuing delay

Texas A & M University13 Simulation Setup Simulation Topology R1R2 TCPs CBRs TCP Sinks CBR Sinks RED/DT, T p =50ms

Texas A & M University14 Link Characteristics Capacities between R1 and R2: 5Mb, 35Mb, 100Mb Total round-trip propagation delay: 120ms Queue management schemes deployed between R1 and R2: RED/RED-ECN/ Droptail

Texas A & M University15 Agenda Motivations Performance Evaluation Simulation Setup  Results & Analysis Discussion

Texas A & M University16 Sets of Simulations Changing buffer sizes Changing link capacities Changing STF loads

Texas A & M University17 Set 1: Changing Buffer Sizes Correlation between average queuing delay & BWDP DropTail RED/RED-ECN

Texas A & M University18 Realized TCP Throughput 30% STF load –Changing buffer size from 1/3 to 3 BWDPs 5Mb Link 100Mb Link

Texas A & M University19 Realized TCP Throughput (cont’d) TCP Throughput higher with DropTail Difference decreases with larger buffer sizes Avg. Qdelay from REDs much smaller than that from Droptail RED-ECN marginally improves throughput over RED

Texas A & M University20 Link Utilization 30% STF load Droptail has higher utilization with smaller buffers Difference decreases with larger buffers Multiple of BWDP 5Mb Link35Mb Link 100Mb Link RED RED- ECN DTRED RED- ECN DTRED RED- ECN DT 1/

Texas A & M University21 Std. Dev. Of Queuing Delay 30% STF + 30% ON/OFF LTNRF load 5Mb Link100Mb Link

Texas A & M University22 Std. Dev. Of Queuing Delay (cont’d) Droptail has comparable deviation at 5Mb link capacity REDs have less deviation under higher buffer sizes and higher bandwidths REDs are more suitable for jitter sensitive applications

Texas A & M University23 Set 2: Changing Link Capacities 30% STF load Relative Avg Queuing Delay = Avg Queuing Delay/RT Propagation Delay ECN DisabledECN Enabled

Texas A & M University24 Relative Avg Queuing Delay Droptail has Relative Avg Queuing Delay close to the buffer size (x * BWDP) REDs has significantly smaller Avg Queuing Delay (~1/3 of DropTail) Changing link capacities have almost no impact

Texas A & M University25 Drop/Marking Rate 30% STF load, 1 BWDP 1 Format: Drop Rate 2 Format: Drop Rate/Marking Rate QM Type of Flow Link Capacity (Mb) RED LTRF LTNRF RED- ECN LTRF / / / LTNRF DT LTRF LTNRF

Texas A & M University26 Set 3: Changing STF Loads 1 BWDP Normalized TCP throughput = TCP throughput / (UDP+TCP) throughput ECN Disabled ECN Enabled

Texas A & M University27 Comparison of Throughputs STF throughputs are almost constant over 3 queue management schemes Difference of TCP throughputs decreases while STF load increases STF Load REDRED-ECN DT LTRFSTFLTNRFLTRFSTFLTNRFLTRFSTFLTNRF 0% % %

Texas A & M University28 Agenda Motivations Performance Evaluation Simulation Setup Results & Analysis  Discussion

Texas A & M University29 Discussion Performance metrics of REDs comparable to or prevailing over DT w/ the existence of STF load and in high BWDP cases Marginal improvement of long-term TCP throughput from RED-ECN with TCP-Sack compared to RED

Texas A & M University30 Discussion (cont’d) Minor impact on Avg Queuing Delay or TCP throughput by changing either link capacities or STF loads With the existence of STFs: BWDPChoose?TCP ThroughputAvg QDelay & Jitter << 1 BWDP (small bw/buffer, low-delay link) DroptailBetterComparable >= 1 BWDP (large bw/buffer, high-delay link) RED/RED- ECN ComparableSignificantly lower

Texas A & M University31 Thank you June, 2004

Texas A & M University32 Related Work S. Floyd et. al. “Internet needs better models” C. Diot et. al. “Aggregated Traffic Performance with Active Queue Management and Drop from Tail” & “Reasons not to deploy RED” K. Jeffay et. al. “Tuning RED for Web Traffic”