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Ion Stoica,Scott Shenker, and Hui Zhang SIGCOMM’99, Vancouver, August 1999

Core-Stateless Fair Queueing: Achieving Approximately Fair Bandwidth Allocations in High Speed Networks. Ion Stoica,Scott Shenker, and Hui Zhang SIGCOMM’99, Vancouver, August 1999 Presented by Bob Kinicki. Outline. Introduction CSFQ Architecture Flow Arrival Rate

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Ion Stoica,Scott Shenker, and Hui Zhang SIGCOMM’99, Vancouver, August 1999

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  1. Core-Stateless Fair Queueing: Achieving Approximately Fair Bandwidth Allocations in High Speed Networks Ion Stoica,Scott Shenker, and Hui Zhang SIGCOMM’99, Vancouver, August 1999 Presented by Bob Kinicki

  2. Outline • Introduction • CSFQ Architecture • Flow Arrival Rate • Link Fair Share Rate Estimation • Many Simulations • Conclusions Advanced Computer Networks : CSFQ

  3. Introduction • This paper brings forward the concept of “fair” allocation. • The claim is that fair allocation inherently requires routers to maintain state and perform operations on a per flow basis. • They present an architecture and a set of algorithms that is “approximately fair” while using FIFO queueing at internal routers. Advanced Computer Networks : CSFQ

  4. An “Island” of Routers Destination Source Edge Router Core Router Destination Advanced Computer Networks : CSFQ

  5. Core-Stateless Fair Queueing • Ingress edge routers compute per-flow rate estimates and insert these estimates as labels into each packet header. • Labels are updated at each router based only on aggregate information. • FIFO queueing with probabilistic dropping of packets on input is employed at core routers. Advanced Computer Networks : CSFQ

  6. Edge – Core Router Architecture Advanced Computer Networks : CSFQ

  7. Model Variables and Parameters Router with output link capacity C. ri (t) :: ithflows arrival rate α(t) :: fair share rate In the fluid flow model, incoming bits of flow i at a core router are dropped with probability Max (0, 1 - α(t) / ri (t) ) Advanced Computer Networks : CSFQ

  8. Flow Arrival Rate At each edge router, use exponential averaging to estimate the rate of a flow. For flow i, let lik be the length of the kth packet. tik be the arrival time of the kth packet. Then the estimated rate of flow i, riis updated every time a new packet is received: rinew = (1-e-T/K)*L / T + e-T/K* riold where T = Tik = tik – tik-1 L = likand K is a constant Advanced Computer Networks : CSFQ

  9. Link Fair Rate Estimation Heuristic algorithm with aggregate state variables: alpha_hat :: fair share estimate Lambda_hat :: aggregate arrival rate estimate F_hat :: aggregate acceptance rate estimate Advanced Computer Networks : CSFQ

  10. Algorithm Idea When packet arrives, Lambda_hat is updated using exponential averaging. If the packet is dropped, F_hat remains the same. If the packet is not dropped, F_hat is updated using exponential averaging. Whenever “epoch” switches congested state, update alpha_hat: alpha_hatnew = alpha_hatold * C /F_hat Advanced Computer Networks : CSFQ

  11. Algorithm Idea (cont.) • Alpha_hat now feeds into next calculation of drop probability (p) as alpha: p = max ( 0 , 1 – alpha / label ) Advanced Computer Networks : CSFQ

  12. CSFQ Pseudo -Code Advanced Computer Networks : CSFQ

  13. Label Rewriting • At core routers, outgoing rate is merely the minimum between the incoming rate and the fair rate, α . • Hence, the packet label L can be rewritten by L new = min (L old , α ) Advanced Computer Networks : CSFQ

  14. Simulations • Major effort of the paper is to compare CSFQ to four algorithms via ns-2 simulations. • FIFO • RED • FRED (Flow Random Early Drop) • DRR (Deficit Round Robin) Advanced Computer Networks : CSFQ

  15. FRED (Flow Random Early Drop) • Maintains per flow state in router. • FRED preferentially drops a packet that has either: • Had many packets dropped in the past • A queue larger than the average queue size • Main goal : Fairness • FRED-2 guarantees to each flow a minimum number of buffers. Advanced Computer Networks : CSFQ

  16. DRR (Deficit Round Robin) • Represents an efficient implementation of WFQ. • A sophisticated per-flow queueing algorithm. • Scheme assumes that when router buffer is full the packet from the longest queue is dropped. • Can be viewed as “best case” algorithm with respect to fairness. Advanced Computer Networks : CSFQ

  17. Simulation Details • Use TCP, UDP, RLM and On-Off traffic sources in separate simulations. • Bottleneck link: 10 Mbps, 1ms latency, 64KB buffer • RED, FRED min max thresholds: 16KB, 32KB • Constants (K, , Kc ) : all 100 ms. Kα Advanced Computer Networks : CSFQ

  18. A Single Congested Link • First Experiment : 32 UDP flows • Each UDP flow is indexed from 0 to 31 with flow 0 sending at 0.3125 Mbps and each of the i subsequent flows sending (i+ 1) times its fair share of 0.3125 Mbps. • Second Experiment : 1 UDP flow, 31 TCP flows • UDP flow sends at 10 Mbps • 31 TCP flows share a single 10 Mbps link. Advanced Computer Networks : CSFQ

  19. Figure 3a: 32 UDP Flows Only CSFQ and DRR can contain UDP flows!! Advanced Computer Networks : CSFQ

  20. Figure 3b : One UDP Flow, 31 TCP Flows Only CSFQ and DRR can contain Flow 0 – the only UDP flow! Advanced Computer Networks : CSFQ

  21. A Single Congested Link • Third Experiment Set : 31 simulations • Each simulation has a different N, N = 2 … 32. • One TCP and N-1 UDP flows with each UDP flow sending at twice fair share rate of 10/N Mbps. Advanced Computer Networks : CSFQ

  22. Figure 4 : One TCP Flow, N-1 UDP Flows Normalized fair share throughput for TCP source DRR good for less than 22 flows. CSFQ better than DRR when a large number of flows. CSFQ beats FRED. Advanced Computer Networks : CSFQ

  23. Multiple Congested Links 1-10 K1-K10 UDP Sinks TCP/UDP-0 Source Router Router Router Router TCP/UDP-0 Sink UDP Sources 1 10 11 20 K1 K10 Advanced Computer Networks : CSFQ

  24. Figure 6a : UDP source Fraction of UDP-0 traffic forwarded versus the number of congested links. Advanced Computer Networks : CSFQ

  25. Figure 6b : TCP Source Fraction of TCP-0 traffic forwarded versus the number of congested links. Advanced Computer Networks : CSFQ

  26. Receiver-driven Layered Multicast • RLM is an adaptive scheme in which the source sends the information encoded in a number of layers. • Each layer represents a diferent multicast group. • Receivers join and leave multicast groups based on packet drop rates experienced. Advanced Computer Networks : CSFQ

  27. Receiver-driven Layered Multicast • Simulation of three RLM flows and one TCP flow. • Fair share for each is 1 Mbps. • Since router buffer set to 64 KB, K, Kc, and are set to 250 ms. Kα Advanced Computer Networks : CSFQ

  28. Figure 7a : DRR Advanced Computer Networks : CSFQ

  29. Figure 7b : CSFQ Advanced Computer Networks : CSFQ

  30. Figure 7c : FRED Advanced Computer Networks : CSFQ

  31. Figure 7d : RED Advanced Computer Networks : CSFQ

  32. Figure 7e : FIFO Advanced Computer Networks : CSFQ

  33. On-Off Flow Model • One approach to modeling interactive, Web traffic :: OFF represents “think time” • ON and OFF drawn from exponential distribution with means of 100 ms and 1900 ms respectively. • During ON period source sends at 10 Mbps. Advanced Computer Networks : CSFQ

  34. Table 1 : One On-Off Flow, 19 TCP Flows Advanced Computer Networks : CSFQ

  35. Web Traffic • A second approach to modeling Web traffic that uses Pareto Distribution to model the length of a TCP connection. • In this simulation 60 TCP flows whose inter-arrivals are exponentially distributed with mean 0.05 ms and Pareto distribution that yields a mean connection length of 20,1 KB packets. Advanced Computer Networks : CSFQ

  36. Table 2 : 60 Short TCP Flows, One UDP Flow Advanced Computer Networks : CSFQ

  37. Table 3 :19 TCP Flows, One UDP Flow with propagation delay of 100 ms. Advanced Computer Networks : CSFQ

  38. Packet Relabeling Sources 10 Mbps Flow 1 Link 1 10 Mbps Router 10 Mbps Link 2 10 Mbps Flow 2 Router Sink 10 Mbps Flow 3 Advanced Computer Networks : CSFQ

  39. Table 4 : UDP and TCP with Packet Relabeling Advanced Computer Networks : CSFQ

  40. Unfriendly Flows • Using TCP congestion control requires cooperation from other flows. • Three types cooperation violators: • Unresponsive flows (e.g., Real Audio) • Not TCP-friendly flows • Flows that lie to cheat. • This paper deals with unfriendly flows!! Advanced Computer Networks : CSFQ

  41. Conclusions • This paper presents Core Stateless Fair Queueing and offers many simulations to show how CSFQ provides better fairness than RED or FIFO. • They mention issue of “large latencies”. This is the robust versus fragile flow issue from FRED paper. • CSFQ ‘clobbers’ UDP flows! Advanced Computer Networks : CSFQ

  42. Significance • First paper to use hints from the edge of the subnet. • Deals with UDP. Many algorithms do not. • Makes a reasonable attempt to look at a variety of traffic types. Advanced Computer Networks : CSFQ

  43. Problems/ Weaknesses • “Epoch” is related to three constants in a way that can produce different results. • How does one set K constants for a variety of situations. • No discussion of algorithm “stability” Advanced Computer Networks : CSFQ

  44. Acknowledgments • Figures extracted from presentation by Nagaraj Shirali and Choong-Soo Lee in Spring 2002. Advanced Computer Networks : CSFQ

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