Comparing flow-oblivious and flow-aware adaptive routing Sara Oueslati and Jim Roberts France Telecom R&D CISS 2006 Princeton March 2006

Motivation s utility is not a function of instantaneous rate Q flows are finite and utility is a function of their duration Q utility(rate) maximization can lead to suboptimal performance s but fairness turns out to be a reasonable objective for wired networks Q utility maximization has informed the design of efficient congestion control s network imposed fairness may be preferred to relying on user cooperation Q fair queueing is scalable, max-min is as good as proportional fair,... s but congestion control also allows adaptive multipath routing Q bringing improved performance and greater resilience to failures s can we achieve the same results using flow-aware netwoking?

Bandwidth sharing: think of flows as boxes... duration rate duration s streaming flows Q audio, vidéo applications Q QoS = low packet delay Q intrinsic rate and duration s elastic flows Q file transfers Q of given size (bytes) Q QoS = low response time Q an exogenous peak rate duration rate variations rate

Q low rate flows Q offered load < capacity Q excellent quality for all overall rate 1. a "transparent" regime Bandwidth sharing: 3 traffic regimes

2. an "elastic" regime Q some high rate flows Q offered load < capacity Q need to control sharing Bandwidth sharing: 3 traffic regimes

3. an "overload" regime Q offered load > capacity Q poor quality for all Q need for overload control

Realizing user quality requirements s perform controlled sharing in the elastic regime Q sharing bandwidth "fairly" between bottlenecked flows Q assuring low latency for streaming flow packets s avoid "congestion collapse" due to overload Q by applying flow level admission control Q or by some other means (??) s classical approaches (Intserv, Diffserv,...) don't work! Q need enhanced congestion control... Q...or flow-aware networking

QoS via end-to-end congestion control s "a self-managed Internet" (F. Kelly) Q fair sharing for elastic flows ("maximum utility") Q negligible delays for streaming flows (by AQM) s but can we design and introduce a packet-based protocol? Q that is (nearly) equivalent to the fluid model Q and fair to legacy TCP s can we rely on user cooperation? Q in implementing the right rate adjustments s how can we control overloads? Q without being flow-aware (and applying admission control)

QoS via flow-aware networking s flow identified by packet header fields Q eg, flow label) in IPv6 s per-flow fair queueing in router queues Q this is scalable and feasible s flow-by-flow implicit admission control Q reject new flows if necessary to protect ongoing flows Q by selective packet discard Q needs a large flow table – but this is feasible s fair queueing imposes max-min fairness Q equivalent performance to other kinds of fairness Q independently of end-to-end protocol (TCP, HSTCP,...) s admission control is a component of adaptive routing Q if first attempt blocked, try another path

Adaptive and multipath routing A s shortest path may be congested or may fail s alternative or multipath routing improves performance s can choose path by randomized load balancing: Q router offers several paths Q path for flow determined by hash on   flow label) Q user tests different paths by changing flow label B

Multipath routing by congestion control (Kelly) s converges to fair allocation (Han et al, Voice) Q even on non-disjoint paths s ideal behaviour in dynamic traffic (Key & Massoulié) Q spreads traffic over all paths in low load Q concentrates on best (lowest price) paths in heavy load Q maximizes the region of stability s but...

Multipath routing by congestion control (Kelly) s converges to fair allocation (Han et al, Voice) Q even on non-disjoint paths s ideal behaviour in dynamic traffic (Key & Massoulié) Q spreads traffic over all paths in low load Q concentrates on best (lowesit prce) paths in heavy load Q maximizes the region of stability s but Q can we design and introduce a packet-based protocol? Q can we rely on user cooperation? Q how can we control overloads?

s using fair queueing and admission control Q to approximate the performance of multipath congestion control s can choose path by randomized load balancing: Q router offers several paths Q path for flow determined by hash on   flow label) Q user tests different paths by changing flow label Flow-aware multipath routing

s using fair queueing and admission control Q to approximate the performance of multipath congestion control s can choose path by randomized load balancing: Q router offers several paths Q path for flow determined by hash on   flow label) Q user tests different paths by changing flow label s to allow non-disjoint paths Q flow label = label 1  label 2 Q change label 2 to test paths, use label 1 only for fair queueing Flow-aware multipath routing

s trunk reservation is discriminatory admission control Q eg, in the phone network, reject calls on links of long paths when fewer than 5% of trunks remain available Q these trunks are "reserved" for calls on the short paths of other routes s to limit use of long paths in heavy load  accept on short path if available rate >  d  capacity (eg,  d = 1%)  accept on long path if available rate >  r  capacity (  r   d )  eg,  r = 5% or 20% Approximate ideal behaviour using "trunk reservation"

Simulation results s a triangular test network s proportional fair allocation derived analytically Q use shortest path unless number of flows on one route greater than sum of flows on the other two routes s admission control applied to avoid instability  flows rejected if available rate <  d  capacity simple test network: 3 links 3 routes 2 paths / route same link capacity traffic characteristics Poisson arrivals exponential size all elastic flows no exogenous rate limit

Multi-path performance: symmetric traffic a 1 = a 2 = a 3 parallel paths capacity=1 Pr [blocking]E [throughput] proportional fair trunk reservation,  r =.05 trunk reservation,  r =.20  a i

Multi-path performance: asymmetric traffic a 1 = 2a 2 = 2a 3 capacity=1 Pr [blocking] – class 1E [throughput] – class 1 proportional fair trunk reservation,  r =.20  a i trunk reservation,  r =.05

Conclusion: flow-aware multipath routing is feasible s multi-path congestion control realizes optimal adaptive routing, provided... Q... a packet based protocol can be designed and introduced Q... and users can be trusted (or policed) Q... and there is an overload control s flow-aware adaptive routing is a viable alternative, provided... Q... trunk reservation is employed to limit over use of long paths Q... and vendors implement per-flow fair queueing and implicit admission control !