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Stochastic Fair Traffic Management for Efficient and Robust IP Networking

Stochastic Fair Traffic Management for Efficient and Robust IP Networking. Jae Chung Airvana Inc. Chelmsford, MA 01824 Mark Claypool, Robert Kinicki WPI Computer Science Department Worcester, MA 01609. 26 th IEEE International Performance Computing

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Stochastic Fair Traffic Management for Efficient and Robust IP Networking

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  1. Stochastic Fair Traffic Management for Efficient and Robust IP Networking Jae Chung Airvana Inc. Chelmsford, MA 01824 Mark Claypool, Robert Kinicki WPI Computer Science Department Worcester, MA 01609 26th IEEE International Performance Computing and Communications Conference (IPCCC) New Orleans, Louisiana, April 11, 2007

  2. Outline • Introduction • SFG Design • Configuration • Evaluation • Summary IPCCC April 11, 2007

  3. Internet Congestion Control • Current Architecture • TCP : Congestion responsive traffic sources using Additive Increase Multiplicative Decrease (AIMD) • Drop-Tail IP Router : Implicit congestion feedback controller (packet drop congestion signal) • Improve Congestion Feedback Control for TCP • Active Queue Management (AQM) at IP Router • Low queuing delay • Explicit congestion notification (ECN) • Fairness and Network Protection from non-TCP • Class-based Bandwidth Usage Control • Per-flow Bandwidth Usage Control IPCCC April 11, 2007

  4. Scheduling-based Approaches Preferential-based Packet Dropping Per-flow Management Pseudo Per-flow Management Edge-Core Architecture Statistical Flow Monitor Statistical Packet Filter SFG FQ, SFQ FRED CSFQ, RFQ RED-PD, SFB CHOKe Complex Scalable Light-weight Per-Flow Bandwidth Control IPCCC April 11, 2007

  5. IP Router Queue TCP TCP Network Protection Congestion Control TCP TCP drop drop In SFG Drop-Tail / AQM Filtered Out UDP UDP UDP UDP Stochastic Fairness Guardian IPCCC April 11, 2007

  6. Outline • Introduction • SFG Design • Configuration • Evaluation • Summary IPCCC April 11, 2007

  7. p = 0.05 … Bin1 p = 0.04 p = 0.03 … p(flow1) = 0.03 Bin2 … … … … p = 0.00 p = 0.06 p = 0.02 … BinN-1 p(flow2) = 0.02 p = 0.02 p = 0.00 … BinN p(flow3) = 0.00 Level1 Level2 LevelL-1 LevelL SFG Design Overview IPCCC April 11, 2007

  8. Multi-Level Hash Bins (1/2) • Use multiple hash functions (L) • Each function hashes flows into N bins • Each bin is assigned an equal share (1/N) of the outbound link capacity (C). • Every epoch (ds), update the forced packet drop probability for each bin (prob[i][j]): fori = 0 to L − 1 do forj = 0 to N − 1 do prob[i][j] = (bytes[i][j] − dsC/N) / bytes[i][j]; bytes[i][j] = 0; /* update drop p for all bins */ end for end for IPCCC April 11, 2007

  9. Multi-Level Hash Bins (2/2) • Each packet arrival, compute the per-flow forced drop probability (p) for the packet, and update bytes received for each hashed bins: p = 1; fori = 0 to L − 1 do j = hash(i, packet); p = min(p, prob[i][j]); /* min drop p seen so far */ bytes[i][j] = bytes[i][j] + sizeof(packet); end for • Drop the packet with the computed per-flow drop probability (p) IPCCC April 11, 2007

  10. Outline • Introduction • SFG Design • Configuration • Evaluation • Summary IPCCC April 11, 2007

  11. The Number of Hash Bins • Configure maximum and minimum Congestion Notification Probability (CNP) thresholds (mh, ml) to turn On/Off SFG if CNP  mh then Turn On SFG if CNP ml then Turn Off SFG • Find the number of bins (N) such that the capacity of each hash bin is equal to TCP-Friendly Rate (TTCP) at CNP = ml N = C / TTCP (ml, RTTsys) where, RTTsys : Estimated average system Round Trip Time IPCCC April 11, 2007

  12. The Number of Hash Levels • False Positive Probability (FPP) Analysis • Given the number of hash bins (N), the number of hash levels (L) and the estimated number of TCP-Unfriendly flows (B) • The false positive probability (Pfp) that a TCP-Friendly flow shares all the bins with TCP-Unfriendly flows: • Use FPP to determine the number of levels. IPCCC April 11, 2007

  13. SFG Configuration Example • Link Bandwidth = 10 Mbps, RTTsys = 300 ms • CNP Thresholds: mh = 0.02, ml = 0.01 • N = 20, B = 1~10, L = ? IPCCC April 11, 2007

  14. Unlucky TCP-Friendly Flows? • Problem : When hashed, an unlucky TCP-Friendly flow can always share all the bins with TCP-Unfriendly flows. • Solution : Use different hashing seed (increment by one) in the next measurement epoch. • Note : This solution also relaxes the low False Positive Probability (FPP) requirement for long-lived flows (i.e. large file transfer). IPCCC April 11, 2007

  15. Measurement Epoch Length • The epoch length should be • Large enough to avoid control error due to insufficient control data acquisition • Larger than the effective congestion feedback control system response time to minimize congestion control interference. • We recommend two seconds for SFG epoch • Approximately twice the upper-bound average RTT seen on the Internet (1 second) [Choi, INFOCOM 2004] • The large epoch length, hence slow response time, is acceptable considering the long flow lifetimes of potentially misbehaving flows. IPCCC April 11, 2007

  16. Outline • Introduction • SFG Design • Configuration • Evaluation • Summary IPCCC April 11, 2007

  17. Evaluation Overview • Evaluation Subjects • Drop-Tail Queue (Baseline) • PI Controller (Hollot+, INFOCOM 2001) • RED-PD (Mahajan+, ICNP 2001), • SFB (Feng+, INFOCOM 2001) • CHOKe (Mitra+, INFOCOM 2000) • SFG, SFG-PI • Evaluation Objectives • TCP performance • Protection performance • Queuing delay and jitter • Web performance IPCCC April 11, 2007

  18. s d s d Q = 500 pkts r1 r2 C = 10 Mbps s d s d Network Topology and Scenario • C = 10 Mbps • Q = 500 Kbytes • RTLD = [60, 1000] ms • Nweb = 300 (Loadoffered = 0.25) • Web session setting (H-Campos+, MASCOTS 2003) Sizeavg= 5KB, Shape = 1.2, Tavg_think = 7sec (expo distribution) • Nftp_bw = 50 • Nftp_fw = 10  50  100  200  400 (every 200 sec) 400  200  100  50  10 (every 200 sec) • Ncbr = 5 • 2 Mbps CBR (1.2 Mbps VBR) from 100 to 1700 sec • Simulation time = 2000 sec IPCCC April 11, 2007

  19. Queue Configurations (1/2) • RED-PD • RED : qmin = 50, qmax= 300, pmax= 0.15, wq= 0.002 • PD : RTTtarget = 100 ms, Windowflow_monitor_history = 5, Tflow_unmonitor = 15 sec, Ratedrop_threshold = 0.005, pmax_inc_step = 0.05 • CHOKe • RED : Same as above • Packet Filter : Divide RED’s queue threshold range (qmax- qmin) into 5 even sub-regions and apply 2i+1 drop comparisons for an incoming packet, where i = {0, 1, 2 ,3, 4} is the sub-region ID. IPCCC April 11, 2007

  20. Queue Configurations (2/2) • SFB • BLUE (inside each SFB bin) : pinc_step = 0.005,pdec_step = 0.001,Tfreeze = 100 ms • Flow Monitor : L = 3, N = 20, punresp_detect = 0.98, Tpenalty_box = 15 ms, Thash_switch = 20 sec • SFG-PI • PI : KP = 0.71× 10−5, KI = 2.8116 × 10−5 • SFG : L = 3, N = 20, mh = 0.02, ml = 0.01, ds = 2 sec IPCCC April 11, 2007

  21. # of FTP 10 50 100 200 400 400 200 100 50 10 Offered Load 1.7 1.0 1.1 1.2 1.4 1.7 1.4 1.2 1.1 1.0 System Throughput IPCCC April 11, 2007

  22. # of FTP 10 50 100 200 400 400 200 100 50 10 Offered Load 1.7 1.0 1.1 1.2 1.4 1.7 1.4 1.2 1.1 1.0 Unresponsive CBR Throughput IPCCC April 11, 2007

  23. # of FTP 10 50 100 200 400 400 200 100 50 10 Offered Load 1.7 1.0 1.1 1.2 1.4 1.7 1.4 1.2 1.1 1.0 Queuing Delay and Jitter IPCCC April 11, 2007

  24. # of FTP 10 50 100 200 400 400 200 100 50 10 Offered Load 1.7 1.0 1.1 1.2 1.4 1.7 1.4 1.2 1.1 1.0 Web Object Service Time IPCCC April 11, 2007

  25. Outline • Introduction • SFG Design • Configuration • Evaluation • Summary IPCCC April 11, 2007

  26. Summary • IP Router Queue Management Taxonomy • Stochastic Fairness Guardian (SFG) • A lightweight Statistical Packet Filter • Flexible deployment with Drop-Tail or AQM • Practical configuration guidelines • Performs comparable to or better than complex flow monitoring mechanisms (RED-PD, SFB). IPCCC April 11, 2007

  27. Additional Contribution • Confirms [Le+, SIGCOMM 2003] result that ECN degrades Web service time at a high offered load (1.2). This is because the congestion notification probability (CNP) is significantly higher than that of packet drop congestion notification system, causing more TCP SYN packet drops. IPCCC April 11, 2007

  28. Stochastic Fair Traffic Management for Efficient and Robust IP Networking Jae Chung Airvana Inc. Chelmsford, MA 01824 Mark Claypool, Robert Kinicki WPI Computer Science Department Worcester, MA 01609 26th IEEE International Performance Computing and Communications Conference (IPCCC) New Orleans, Louisiana, April 11, 2007

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