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NOBEL Turin Meeting D32 contribution: Multipath Load adaptative routing in OBS networks

NOBEL Turin Meeting D32 contribution: Multipath Load adaptative routing in OBS networks. Telefónica I+D. Index. Introduction Multipath Routing with Dynamic Variance Overview MRDV over OBS Simulation Conclusions and future work. Introduction.

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NOBEL Turin Meeting D32 contribution: Multipath Load adaptative routing in OBS networks

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  1. NOBEL Turin MeetingD32 contribution: Multipath Load adaptative routing in OBS networks Telefónica I+D NOBEL Turin meeting

  2. Index • Introduction • Multipath Routing with Dynamic Variance Overview • MRDV over OBS • Simulation • Conclusions and future work NOBEL Turin meeting

  3. Introduction • MRDV Objective: Efficient use of network resources • Requirement: Better policies and mechanisms • IP routing plays a major role • Current IP routing is: • ... distributed: routing decissions are taken hop by hop • ... static: independent from occupation in links • This approach has important advantages... • Simple • Highly scalable • Compatible! • ... but it also has problems: • Non-autonomous. It cannot react to sudden changes in demand autonomously. • Inefficient. Traffic concentrates on few links • Routers “see” the same costs • Little control over performance of individual flows NOBEL Turin meeting

  4. Introduction • Loss probability in OBS networks increases exponentially when network load is high. • SP routing saturates better routes, that affects loss probability to a large extend. • MRDV uses not only the optimum path, it should avoid the exponentially increment of loss probability. • Objective: • Study the MRDV behaviour in OBS networks. • Comparison among SP, ECMP and MRDV in different scenarios. • Propose parameters adaptation for OBS networks. • Detect the influence of MRDV parameters. NOBEL Turin meeting

  5. Multipath Routing with Variance Dynamic Routing Protocols +  Variance = F(first-hop occupation) Nº feasible paths = F(link occupation) MRDV Algorithm Overview (I) • Objective: • Basically: • Parameters: • Variance: Associated to interfaces • Occupation: Interface is the first-hop of an optimal path • Behaviour: • Low load in first-hop  very low variance  1 route • High load in first-hop  higher variance  Several routes • Distribution of traffic (when multipath): • Cost (i.e. +BWbottleneck)  + % of traffic NOBEL Turin meeting

  6. Demand Path Costi MMAXPath+ Nº Hops = BWMAX = M i BWi Time B Routing tableSrc. A  Dst. D D 50 A 100 25 Next-hop Path cost 10 50 B 4 C 6 C MRDV Algorithm Overview (II) NOBEL Turin meeting

  7. Path Costi MMAXPath+ Nº Hops = BWMAX = M i BWi B D A C MRDV Algorithm Overview (III) Demand Time 100% of demand Routing tableSrc. A  Dst. D  = 0.4 50 100 Next-hop Path cost B 4 25 10 50 6 C  = 0 Vab(40%) < 1.5  No. Pathsad=1 NOBEL Turin meeting Mi<V*Mmin V < 6/4=1.5

  8. Path Costi MMAXPath+ Nº Hops = BWMAX = M i BWi B D A C MRDV Algorithm Overview (IV) Demand Time 100% of demand Routing tableSrc. A  Dst. D  = 0.75 50 100 Next-hop Path cost B 4 25 10 50 6 C  = 0 Vab(75%) > 1.5  No. Pathsad=2 NOBEL Turin meeting

  9. Path Costi MMAXPath+ Nº Hops = BWMAX = M i BWi B D A C MRDV Algorithm Overview (V) Demand Time 60% of demand Routing tableSrc. A  Dst. D  = 0.5 50 100 Next-hop Path cost B 4 25 10 50 6 C 40% of demand Vab(50%) > 1.5  No. Pathsad=2 1-6/(6+4)=0.4 NOBEL Turin meeting

  10. Path Costi MMAXPath+ Nº Hops = BWMAX = M i BWi B D A C MRDV Algorithm Overview (VI) Demand Time 60% of demand Routing tableSrc. A  Dst. D  = 0.27 50 100 Next-hop Path cost B 4 25 10 50 6 C  = 0.13 40% of demand Vab(27%) < 1.5  No. Pathsad=1 NOBEL Turin meeting

  11. Path Costi MMAXPath+ Nº Hops = BWMAX = M i BWi B D A C MRDV Algorithm Overview (VII) Demand Time 100% of demand Routing tableSrc. A  Dst. D  = 0.4 50 100 Next-hop Path cost B 4 25 10 50 6 C  = 0 Vab(40%) < 1.5  No. Pathsad=1 NOBEL Turin meeting

  12. MRDV over OBS • Development of a module to support OBS in ns-2 simulator: • Signalling protocol: JET • Scheduling algorithm: LAUC • Ns-2 MRDV module adaptation for OBS. • Problem of using MRDV over OBS: • Metric election • In D23, metric analysis, choosing the link load. • Offset election  Influence greatly in drop probability • Using SP or ECMP, the origin knows the number of hopes, but in MRDV not. • Options: • Network diameter. • Shortest path + margin. NOBEL Turin meeting

  13. Simulation • Scenario used is NSFNet • Traffic Characteristics • Each node send the same traffic to all nodes. • 0.5, 0.25, 0.1 and 0.01 Erlangs. • Burst length exponential. • Inter-arrivals time exponential. NOBEL Turin meeting

  14. Preliminar Results • First Simulation • Routing protocol: MRDV • Time: 60 s. • Load: 0,01 Erlangs • Processing time: 2,5 us • Switching time: 10 us • Burst length: 100 us • Lambda BW: 10 Gbps • Lambdas: 16 • Offset time: network diameter • MRDV uses 274 paths at the beginning, load is not high enough to active its mechanisms again. • Loss probability is due to drop probability. • We carried out the same simulation with SP and none burst was lost. NOBEL Turin meeting

  15. Preliminar Results • Second Simulation • Rounting protocol: MRDV • Time: 60 sg. • Load: 0,5 Erlangs • Procesing time: 2,5 us • Switching time: 10 us • Burst length: 100 us • Lambda BW: 10 Gbps • Lambdas: 16 • Offset time: network diameter • Load is high enough to active its mechanisms again at 30 seconds. • From 274 to 416 paths  loss probability increases quickly. • However, drop probability is the main reason.  Offset must be ajusted NOBEL Turin meeting

  16. Loss Probability evolution by node NOBEL Turin meeting

  17. Load in each node NOBEL Turin meeting

  18. Conclusions and future work • Offset needs to be ajusted. • Most of the blocking is due to droping because of lack of offset time • The other strategies have to be studied. • Add loop avoiding algorithm of MRDV (in this version it is not included) • Blocking probability depends strongly on scenarios. • Analyze situation in another scenarios. • Find optimal value for the variance and time between updates • Find how load is distruted • Fairness • Use different loads (ranging from 1 to 0.01 Erlangs per node and destiny) NOBEL Turin meeting

  19. Backup Slides NOBEL Turin meeting

  20. Prevention of instability • To prevent oscillations: • Costs of links are constant • Every router “sees” a diferent network • Hysteresis cycle for variance calculation • Hysteresis cycle: • Criterion: • Many other criteria are possible Relative increments in variance must be proportional to relative increments in average load Vmax=4 Kup=2 Kdn =0.5 NOBEL Turin meeting

  21. Other considerations • Choice of the update interval: • Design parameter • Tradeoff: Response time vs. Accuracy in measures • Stability: > 10 sec (at least) • Shorter time-scales: Diffserv • Packet disorder must be avoided! • Same flow should take same path (if nothing else changes) • SOLUTION: Hash function • Advantage: Simple and scalable • Compatible with currently deployed IP networks • Easy deployment: • Selective • Gradual Hash = F(source IP, destination IP) NOBEL Turin meeting

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