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1 Probabilistic Packet Scheduling (PPS) Ming Zhang, Randy Wang, Larry Peterson, Arvind Krishnamurthy Department of Computer Science Princeton University.

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Presentation on theme: "1 Probabilistic Packet Scheduling (PPS) Ming Zhang, Randy Wang, Larry Peterson, Arvind Krishnamurthy Department of Computer Science Princeton University."— Presentation transcript:

1 1 Probabilistic Packet Scheduling (PPS) Ming Zhang, Randy Wang, Larry Peterson, Arvind Krishnamurthy Department of Computer Science Princeton University

2 2 Motivation – Lottery Scheduling OS defines currency and assigns lottery tickets to processes Processes proportionally divide CPU cycles A Process can make local CPU allocation decision 900 OS P1P2 P4P5P3 300 10005001000

3 3 Proportional Bandwidth Allocation Router defines currency in tickets/s and assigns tickets to its inputs Link maintains currency exchange rate Bandwidth at bottleneck is proportional to ticket share Local bandwidth allocation decision and isolation 2Mb/s 900t/s 1Mb/s 300t/s B 10Mb/s 500t/s A 10Mb/s 1000t/s C 10Mb/s 1000t/s 1Mb/s 2000t/s S0 S1 S3 S2 S4 S5S6

4 4 Algorithm in Brief TCP source tags tickets on each packet Each router runs a variant of RED to decide whether to drop or accept a packet Relabel packets at each link based on currency exchange rate

5 5 Ticket Tagging OutTktRate – t/s assigned to a TCP source AvgRate - average throughput of a flow Tag OutTktRate / AvgRate onto each packet Tickets on packet are inversely proportional to the average throughput

6 6 Ticket-based RED (TRED) InTkt is the tickets on an incoming packet. ExpectTkt is the tickets “should” be on an incoming packet ExpectTkt is computed as average tickets on all incoming packets Bottlenecked flows put approximately ExpectTkt tickets on their packets If MinThresh < AvgQLen < MaxThresh compute probability p the same as in RED p’ = p * (ExpectTkt / InTkt) 3 drop the packet with probability p’

7 7 Exchange Rate A multi-hop flow may go through many routers Different routers have their own currencies Convert tickets between different currencies Exchange rate at each link XRate = OutTktRate / InTktRate Relabel packets according to exchange rate OutTkt = InTkt * XRate

8 8 Receiver-based Algorithm Controlling bandwidth allocation at receiver AckOutTktRate – t/s assigned to an output Tagging and relabeling of ACKs are similar Compute OutTktRate from tickets on ACKs OutTktRate = AckInTktRate

9 9 One-Hop Configuration 4.65Mb/s 26ms P 1 2 30 2 1 Q 100t/s 200t/s 3000t/s Simulations are run in NS-2 Sender-based and receiver-based

10 10 One-Hop Results

11 11 Multi-Hop Configuration 1.65Mb/s 26ms A1 A2 A10 P1 P2 P4S2 B1 B2 B10 P3 S1 S20 5500t/s 11000t/s 100t/s 200t/s 1000t/s 100t/s 200t/s 1000t/s

12 12 Multi-Hop Results

13 13 Fairly Share Unused Bandwidth

14 14 3600 S8 S9 2000 5Mb/s ? Mb/s 10 Mb/s 3Mb/s 10Mb/s B S0 S1 S4 S3 S5 S6S7 A 10Mb/s 1.2Mb/s 1000 S2 1400 700 C 10Mb/s 10Mb/s D 1200 Multiple Bottlenecks Configuration

15 15 Multiple Bottlenecks Results FlowMeasured (Mb/s) Expected (Mb/s) Measured (Mb/s) Expected (Mb/s) A0.560.600.740.80 B0.640.600.450.40 C0.230.200.690.67 D0.110.100.360.33

16 16 Comparison with CSFQ

17 17 One-Hop Configuration 4.65Mb/s 26ms P 1 2 30 2 1 Q 100t/s 200t/s 3000t/s

18 18 One-Hop Results

19 19 Related Work WFQ, IntServ DiffServ CSFQ User-share differentiation

20 20 Conclusion and Future Work Proportional bandwidth allocation A modified RED algorithm (TRED), no per-flow state, scalable Routers make local bandwidth allocation and isolation Sender-based and receiver-based Experiment with more realistic traffic load and complex topologies


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