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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 MeetingD32 contribution: Multipath Load adaptative routing in OBS networks Telefónica I+D NOBEL Turin meeting
Index • Introduction • Multipath Routing with Dynamic Variance Overview • MRDV over OBS • Simulation • Conclusions and future work NOBEL Turin meeting
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
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
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
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
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
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
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
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
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
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
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
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
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
Loss Probability evolution by node NOBEL Turin meeting
Load in each node NOBEL Turin meeting
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
Backup Slides NOBEL Turin meeting
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
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