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Dual-resource TCP/AQM for processing-constrained networks

INFOCOM 2006, Barcelona, Apr. 25, 2006. Dual-resource TCP/AQM for processing-constrained networks. Minsu Shin and Song Chong Department of EECS, KAIST, Korea. Injong Rhee Department of CS, NC State Univ., USA. Outline. Motivation Processing-constrained network Dual-resource environment

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Dual-resource TCP/AQM for processing-constrained networks

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  1. INFOCOM 2006, Barcelona, Apr. 25, 2006 Dual-resource TCP/AQM for processing-constrained networks Minsu Shin and Song Chong Department of EECS, KAIST, Korea • Injong Rhee • Department of CS, • NC State Univ., USA

  2. Outline • Motivation • Processing-constrained network • Dual-resource environment • Objective • Dual-resource fair allocation • Dual-resource TCP/AQM (DRQ) • DRQ objective • DRQ implementation • Simulation results • Conclusion

  3. Processing-constrained network • Link bandwidth grows fast • Advancement in optical network technology • Over-provisioning as the solution to congestion • The rise of in-network applications Future network Virus detection Complexity increases Duplicate data suppression Data Transcoding VPN & IPSec Web-switching Firewall Network address translation Packet classification and filtering IP forwarding Traditional network

  4. Dual-resource environment • Both bandwidth and CPU can be a bottleneck • Can existing congestion control (TCP) be applied? Malicious user Congestion Switch CPU User What is fair and efficient resource allocation?

  5. Objective • To propose a dual-resource fairness criteria • Extend the proportional fairness to the dual-resource environment • Provide fair and efficient resource usages • To propose a dual-resource queue (DRQ) • Active queue management (AQM) strategy • Approximate dual-resource fairness for TCP sources • Scalable : Not maintaining per-flow states or queues • Incrementally deployable : No changes in TCP stacks

  6. Single-resource fairness Selection of [Mo 00] maximum throughput proportional fair max-min fair • Only considering link bandwidth constraint • Assume that network consists of L links rate r1 Output Link Tx rate rS Bl (Mbps) Maximization problem [Low 99]

  7. Dual-resource fairness Output Link CPU Tx B (Mbps) C (cycles/sec) Selection of : processing density Indicating required CPU cycles per bit Proportional fairness is weight of flow s • Considering both CPU and bandwidth constraint • Network consists of L links and K CPUs rate r1 rate rS Maximization problem

  8. Performance Output Link CPU Tx B (Mbps) C (cycles/sec) 40% utilization increases CPU fair share • Single link case rate r1 rate r4 w = [1, 2, 4, 8] Single-resource fair allocation Dual-resource fair allocation

  9. Dual-resource fair rate • Congestion price of resources • CPU price : θ, Link price : π • Increasing : demand > resource capacity • Decreasing : demand < resource capacity • Positive when the resource becomes a bottleneck • Zero when not a bottleneck • Fair rate • Inversely proportional to the aggregate price Weighted CPU price sum Link price sum

  10. Dual-resource TCP/AQM α TCP Sending rate ≈ • Extend dual-resource fairness to TCP network • DRQ modifies RED algorithm TCP Sender (w) TCP receiver Tx CPU Tx B1 (Mbps) B3 (Mbps) C2 (cycles/s) Packet drop with probability p1 p2 p3 Current TCP/AQM α TCP Sending rate ≈ Our Goal

  11. DRQ algorithm α TCP Sending rate ≈ Our Goal Each resource drops packet with p2 (link), or (wp)2 (CPU) TCP Sender (w) TCP receiver Tx CPU Tx B1 (Mbps) B3 (Mbps) C2 (cycles/s) packet drop with probability p1 p2 p3 Communication between resources is needed

  12. DRQ algorithm (link), or (CPU) : Intra-marking probability (link), or (CPU) : Inter-marking probability At link 1, mark packet with prob. At CPU 2, mark packet with prob. At link 3, mark packet with prob. If already marked, then drop packet! Red card! Yellow card! No explicit communication between resources!

  13. DRQ-ECN implementation • Three ECN cases • ECN = 00 : Initial state • ECN = 10 : Signaling-marked (No congestion notification) • ECN = 11 : Congestion-marked (TCP source decreases its window size by half) • DRQ’s ECN marking algorithm • When a packet arrives • if(ECN ≠ 11) set ECN to 11 with red-card probability • if(ECN == 00) set ECN to 10 with yellow-card probability • if(ECN == 10) set ECN to 11 with yellow-card probability

  14. Performance evaluation Output Link CPU Tx B (Mbps) C (cycles/sec) DRQ’s complexity : RED-RED but, DRQ’s performance : DRR-RED • Comparison partners • RED-RED : CPU and link queues use original RED • Very cheap. Most of current network system architecture • DRR-RED : Scheduling CPU using per-flow queue • Expensive approach. Similar architecture to current computing system RED RED DRR RED Output Link CPU Tx B (Mbps) C (cycles/sec)

  15. Single CPU and link case 40 TCP sources, which require different processing (0.25, 0.50, 1.00, 2.00) Varying CPU capacity In DRQ, each follows fair rates. Topology Average throughput of each source DRQ

  16. Single CPU and link case Efficiency improves ! • RED-RED has much lower bandwidth utilization • DRQ performance is comparable to DRR-RED Comparison of bandwidth utilization

  17. Impact of high processing flows Prevent CPU domination! Increase total throughput Insert a few high processing flows (w=10.0) DRQ and DRR-RED prevent their domination but RED-RED doesn’t

  18. Multiple-link simulation(1) Parking-lot topology, with various cross-traffic DRQ follows theoretic fair rates very well. Throughput of TCP/DRQ in multiple link simulations

  19. Partial deployment DRQ is implemented at only IE1 and EE1 • Network edge • Pushing complicated tasks to the edge of Internet • DRQ can be initially deployed to the edge system • Simulation topology Source groups SG1 : High processing SG2 : low processing Others : Negligible processing

  20. Partial deployment Increase throughput of IE1 Throughput of processing-constrained edge Partial deployment is also beneficial to improve efficiency

  21. Conclusion • Contribution of this paper • Finding an efficient and fair allocation policy in the dual-resource environment • Suggestion of the practical implementation guideline

  22. References [Kelly 98] “Rate control in communication networks: shadow prices, proportional fairness and stability", J. of the Operational Research Society, 1998 [Mo 00] “Fair end-to-end window-based congestion control", IEEE/ACM TON 2000 [Wolf 00] “Commbench – a telecommunications benchmark for network processors", ISPASS 2000 [Low 99] “Optimization flow control I : Basic algorithm and convergence", IEEE/ACM TON 1999 [Floyd 93] “Random early detection gateways for congestion avoidance", IEEE/ACM TON 1993 [Low 03] “A duality model of TCP and queue management algorithms", IEEE/ACM TON 2003 [Pappu 02] “Scheduling processing resources in programmable routers”, IEEE INFOCOM 2002

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