on selfish routing in internet-like evironments
DESCRIPTION
On Selfish Routing In Internet-Like Evironments. Lili Qiu (Microsoft Research) Yang Richard Yang (Yale University) Yin Zhang (AT&T Research) Scott Shenker (ICSI). Motivation. Practical front A recent trend: end hosts choose routes Source routing (e.g., Nimrod) - PowerPoint PPT PresentationTRANSCRIPT
System & Network Reading Group
On Selfish Routing In Internet-Like Evironments
Lili Qiu (Microsoft Research)Yang Richard Yang (Yale University)
Yin Zhang (AT&T Research)Scott Shenker (ICSI)
System & Network Reading Group
Motivation
• Practical front– A recent trend: end hosts choose routes
• Source routing (e.g., Nimrod)• Overlay routing (e.g., Detour or RON)
– Characteristics of routing by end hosts• Improve over today’s IP routing (e.g., delay, loss rate)• Selfish by nature (i.e., optimize user-centric
performance without considering system-wide criteria)
• Theory front– Roughgarden et al. showed selfish routing can
result in serious performance degradation due to lack of cooperation
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Example: Selfish Routing May Yield Sub-Optimal Performance
• Selfish routing– All traffic go through the lower link– Total latency = 1
• Optimal routing (i.e., minimize total latency)– Traffic split equally between the two links– Total latency = ¾
• The performance degradation can be unbounded for non-linear latency functions
src dest
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Open Issues• How does selfish routing perform in Internet-like
environments?– Realistic network topologies– Realistic traffic demands– Realistic network delay functions
• How does selfish overlay routing perform?• How does selfish traffic co-exist with the
remaining traffic that uses traditional routing protocols?
• How does users’ selfish routing interact with underlying network control process (e.g., traffic engineering)
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Outline
• Overview• Related work• Network model• Approach to compute traffic equilibria• Performance results
– Physical routing– Overlay routing– Multiple overlays– Interaction with traffic engineering
• Summary and future work
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Overview
• Approach– Use a game-theoretic approach to
answer the above open issues– Focus on intra-domain scenarios
• Recent advances in topology mapping and traffic estimation
• Compare with theoretical results
– Focus on equilibrium behavior• Compare the performance of Nash
Equilibria with the global optima based on realistic topologies, traffic demands, latency functions
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Some of Key Results• Formulate and evaluate selfish overlay routing• Unlike the theoretical worst cases, selfish routing
in Internet-like environments yields close to optimal latency– The above result is true for both source
routing and overlay routing– Selfish routing can achieve good performance
without hurting the traffic that is using default routing
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Some of Key Results (Cont.)
• Mismatch between selfish routing and traffic engineering– Different objectives
• Selfish routing: minimize e2e delay• Traffic engineering: aim to balance load
– Selfish routing reduces latency at the cost of increased congestion
– The adaptive nature of selfish routing makes traffic demands less predictable and reduces the effectiveness of traffic engineering
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Related Work
• Measurement results– Detour and RON projects showed that
default routing path is often sub-optimal in terms of latency, loss rate, and TCP throughput
– Possible causes of routing inefficiency• Routing hierarchy• Routing policy• Different routing objectives used by ISPs• Stability problem in routing protocols, such
as BGP• …
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Related Work (Cont.)
• Theory results– Koutsoupias and Papadimitriou compared the
worst-case Nash equilibrium with a global optimal in a two-node network
– Price of anarchy (i.e., worst-case ratio between the total latency of a Nash equilibrium and that of the global optimal) can be unbounded [Roughgarden00]
– The performance degradation due to selfish routing can be compensated for by doubling the bandwidth on all links [Roughgarden01]
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Network Model• Physical network
– Directed graph G=(V,E)– Latency of each edge is a function of its load
(e.g., M/M/1)
• Demands– demand(i,j): the amount of traffic from a source i
to a destination j
• Overlays– A set of overlay nodes and a set of demands– Consider mesh-like overlay topologies
• Users– Each user decides how its traffic should be routed
to optimize performance (e.g., min latency)
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Network Model (Cont.)
• Route controller– Uses network-level routing
• OSPF/IS-IS: shortest-path with equal-weight splitting, with the following weight settings
– Hop-count– Random-weight– Optimized-compliant weight: minimize network
cost when assuming all traffic is compliant (i.e., following the routes determined by the network
• MPLS: general multi-commodity flow routing
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Different Routing Schemes
• Physical routing– Source routing (i.e., selfish routing studied in
previous theoretical work)– Optimal routing
• Overlay routing– Overlay source routing (i.e., selfish routing
with routing constraints)– Overlay optimal routing
• Compliant routing (i.e., normal Internet routing)
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Approach to Computing the Traffic Equilibria
• General approach– Simulation-based: too expensive to derive traffic equilibria– We use a game-theoretic approach to compute the traffic
equilibria directly
• Computing the equilibria of physical routing– linear-approximation algorithm, a variant of Frank-Wolfe
algorithm
• Computing the equilibria of overlay routing– Symmetric: Modified linear approximation algorithm – Asymmetric: Jacob’s relaxation algorithm
• Computing the equilibria of multiple overlays– Use the relaxation algorithm to guarantee the
convergence
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Evaluation Methodology• Network topology
– A large tier-1 ISP topology– Rocketfuel topologies– Random power-law topologies
• Traffic demands– Real traffic demands from the ISP– Synthetic traffic demands
• Link latency functions– M/M/1, M/D/1, P/M/1, P/D/1, BPR
• Performance metrics– Average latency– Maximum link utilization– Network costs: piece-wise linear, increasing, convex
function [FRT02]
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Outline
• Overview• Related work• Network model• Approach to compute traffic equilibrium• Performance Evaluation
– Source routing– Overlay routing– Multiple overlays– Interaction with traffic engineering
• Summary and future work
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Selfish Source Routing
• Questions– Are Internet-like environments among the
worst-case?– What is the system-wide cost for selfish
source routing?
• Dimensions – Performance metrics: latency & network load– Effects of network topologies– Effects of network load– Effects of latency functions
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Selfish Source Routing: Latency
• Effects of network topologies
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Selfish Source Routing: Network Load
• Effects of network topologies
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Selfish routing tends to overload links.
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Summary: Selfish Source Routing
• The performance is qualitatively the same as we vary latency functions and network load
• Unlike the theoretical worst cases, selfish source routing yields close to optimal latency
• Selfish routing tends to overload links on the shortest paths
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Outline
• Overview• Related work• Network model• Approach to compute traffic equilibrium• Performance results
– Source routing– Overlay routing– Multiple overlays– Interaction with traffic engineering
• Conclusion and future work
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Selfish Overlay Routing
• Questions– Does selfish overlay routing perform
well?– How does the coverage of overlay
network affect the performance?
• Dimensions– Effects of network topologies– Effects of amount of overlay coverage– Effects of how overlay nodes are
selected (e.g., random or edge nodes)
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Difference between Source Routing and Overlay Routing
• Even if the overlay includes all network nodes, routing on an overlay is still different – Network-level routing can prevent any overlay
traffic from using a link by setting the corresponding entry in routing matrix to 0 (in OSPF this is achieved by assigning a large weight)
– Certain physical routes cannot be implemented by any overlay routing
• Routing flexibility is further reduced when only a fraction of nodes belong to an overlay
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Selfish Overlay Routing (Full Overlay Coverage)
• Direct Link Shortest [DLS]– For any physically adjacent nodes A and B, all the
traffic from A to B is routed through the direct link AB without involving any other links. (e.g., hop-count-based OSPF)
• For an overlay that covers all network nodes and satisfies DLS– routing on the overlay = routing on the underlay
• Hop-count-based OSPF and optimized OSPF weights satisfy DLS they perform similarly as source routing
• Random OSPF weights violate DLS some links are pruned, and performance degrades
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Selfish Overlay Routing (Partial Overlay Coverage)
• Overlay is formed from all edge nodes in ISPTopo
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Summary: Selfish Overlay Routing
• For full overlay coverage– Overlay has full routing control when the
underlay satisfies DLS– The only way in which OSPF affects
overlay routing is by violating DLS, which reduces available network resources
– Overlay selfish routing reduces latency at the expense of higher network cost
• The effects of partial coverage are small in backbone topologies
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Outline
• Overview• Related work• Network model• Approach to compute traffic equilibrium• Performance results
– Source routing– Overlay routing– Multiple overlays– Interaction with traffic engineering
• Conclusion and future work
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Interactions among Competing Overlays
• Question– Can multiple overlays share network
resources fairly and effectively?• Dimensions
– Effects of network topologies– Effects of network-level routing
schemes– Effects of network load and traffic
distribution among overlays– Effects of the number of competing
overlays
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Interactions among Competing Overlays (Cont.)
• Effects of network-level routing load scale factor = 1
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Summary: Interactions among Competing Overlays
• With reasonable OSPF weights (e.g., hop-count)– Different routing schemes co-exist
without hurting each other
• With bad OSPF weights– Selfish overlay improves both for
themselves and for compliant traffic
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Outline
• Overview• Related work• Network model• Approach to compute traffic equilibrium• Performance results
– Source routing– Overlay routing– Multiple overlays– Interactions with traffic engineering
• Conclusion and future work
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Selfish Routing vs. Traffic Engineering
• So far we assume network is dumb (i.e., static underlay routing)
• In practice, the network is smart due to traffic engineering (i.e., underlay routing adapts to varying traffic)
• Question– Will the system reach a state with both low
latency and low network cost, as selfish routing and traffic engineering each tries to optimize their objective by adapting to the other process?
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Specification of Vertical Interactions
• Interactive process between two players– Traffic engineering
• Given traffic matrix Tt, where Tt(s,d) denotes traffic from source s to destination d in time slot t
• Compute routing matrix Rt for the underlay
– Selfish routing• Given routing matrix Rt for the underlay
• Produce new traffic matrix Tt
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One Round during Vertical Interaction
T(t) = Traffic matrix when routing matrix is R(t-1)
R(t) = OptimizedRoutingMatrix(T(t))Traffic engineering installs R(t) to networkSelfish routing redistributes traffic to form
T(t+1)
Note that different from traditional games
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Vertical Interaction with OSPF Optimizations
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OSPF route optimization interacts poorly with selfish routing
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Vertical Interaction with MPLS Optimization
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MPLS optimization interacts with selfish routing more effectively
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Summary: Selfish Routing vs. Traffic Engineering
• OSPF route optimization interacts poorly with selfish routing
• MPLS interacts with selfish routing more effectively
• Despite the encouraging results from MPLS, several challenges exist– How to estimate traffic matrices accurately in
presence of adaptive selfish traffic?– Large optimization problems
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Conclusion
• When the network-level routing is static, selfish routing achieves close to optimal latency
• The good latency achieved in selfish-routing comes at the cost of increased congestion
• When selfish routing and traffic engineering each tries to minimize its own cost by adapting to the other process, the resulted performance could be much worse
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Future Work
• Study impacts of multi-AS nature of the Internet
• Study dynamics of selfish routing (i.e., how traffic equilibria are reached?)
• Improve the interactions between selfish routing and traffic engineering
• Study other selfish routing objectives (e.g., loss and throughput)
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Interactions among Competing Overlays (Cont.)
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Interactions among Competing Overlays (Cont.)
• Effects of network load and traffic distribution among overlays
optimal compliant OSPF weights (LSF=1)
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Interactions among Competing Overlays (Cont.)
• Effects of the number of overlays
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Summary: Selfish Routing vs. Traffic Engineering
• OSPF route optimization interacts poorly with selfish routing
• MPLS interacts with selfish routing more effectively
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Selfish Source Routing: Latency
• Effects of network load
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Selfish Source Routing: Latency (Cont.)
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Selfish Source Routing: network load
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Selfish Source Routing: network load (Cont.)
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Selfish Overlay Routing (Full Overlay Coverage)
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Selfish Overlay Routing (Full Overlay Coverage)
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Selfish Overlay Routing (Partial Overlay Coverage)
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