Pricing Networks with Selfish Routing Tim Roughgarden (Cornell) - - PowerPoint PPT Presentation

pricing networks with selfish routing
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Pricing Networks with Selfish Routing Tim Roughgarden (Cornell) - - PowerPoint PPT Presentation

Pricing Networks with Selfish Routing Tim Roughgarden (Cornell) Joint with Richard Cole (NYU) and Yevgeniy Dodis (NYU) Survey of papers in STOC 03 and EC 03 Selfish Routing a directed graph G = (V,E) a source s and a


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Pricing Networks with Selfish Routing

Tim Roughgarden (Cornell)

Joint with Richard Cole (NYU) and Yevgeniy Dodis (NYU) Survey of papers in STOC ’03 and EC ‘03

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Selfish Routing

  • a directed graph G = (V,E)
  • a source s and a destination t
  • one unit of traffic from s to t
  • for each edge e, a latency function ℓe(•)

– assumed continuous, nondecreasing, convex s t ℓ(x)=x

Flow = ½ Flow = ½

ℓ(x)=1 Example:

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Routings of Traffic

Traffic and Flows:

  • fP = fraction of traffic routed on s-t path P
  • flow vector f

routing of traffic Selfish routing: what flows arise as the routes chosen by many noncooperative agents?

s t

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Nash Flows

Some assumptions:

  • agents small relative to network
  • want to minimize personal latency

Def: A flow is at Nash equilibrium (or is a Nash flow) if all flow is routed on min-latency paths [given current edge congestion]

– have existence, uniqueness [Wardrop, Beckmann et al 50s]

x

s t

1

Flow = .5 Flow = .5

s t

1

Flow = 0 Flow = 1

x

Example:

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Inefficiency of Nash Flows

Our objective function: average latency

  • ⇒ Nash flows need not be optimal
  • observed informally by [Pigou 1920]
  • Average latency of Nash flow = 1•1 + 0•1 = 1
  • of optimal flow = ½•½ +½•1 = ¾

s t x 1

1

½ ½

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Marginal Cost Taxes

Goal: do better with taxes (one per edge)

– not addressing implementation

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Marginal Cost Taxes

Goal: do better with taxes (one per edge)

– not addressing implementation

Assume: all traffic minimizes time + money Def: the marginal cost tax of an edge (w.r.t.

a flow) is the extra delay to existing traffic caused by a marginal increase in traffic

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Marginal Cost Taxes

Goal: do better with taxes (one per edge)

– not addressing implementation

Assume: all traffic minimizes time + money Def: the marginal cost tax of an edge (w.r.t.

a flow) is the extra delay to existing traffic caused by a marginal increase in traffic

Thm: [folklore] marginal cost taxes w.r.t. the

  • pt flow induce the opt flow as a Nash eq.
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Why Homogeneous?

Problem: strong homogeneity assumption

– at odds with assumption of many users – are taxes still powerful without this?

Our assumption: agent a has objective function time + β(a) × money

– distribution function β assumed known

  • in aggregate sense
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Existence Theorem

Thm: can still induce opt flow as Nash eq,

even with arbitrary heterogeneous users.

– assumes only β measurable, bounded away from 0

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Existence Theorem

Thm: can still induce opt flow as Nash eq,

even with arbitrary heterogeneous users.

– assumes only β measurable, bounded away from 0

Pf Idea: Brouwer’s fixed-point thm.

– continuous fn on compact convex set has fixed pt – want OPT-inducing taxes fixed points

  • continuous map:

– given tax vector not inducing OPT, push vector in helpful direction (else fixed pt)

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Proof of Existence Theorem

  • continuous map: raise edge tax if Nash uses

edge more than OPT, lower tax if opposite

– OPT-inducing taxes fixed points

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Proof of Existence Theorem

  • continuous map: raise edge tax if Nash uses

edge more than OPT, lower tax if opposite

– OPT-inducing taxes fixed points

  • Problem: set of all taxes unbounded!
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Proof of Existence Theorem

  • continuous map: raise edge tax if Nash uses

edge more than OPT, lower tax if opposite

– OPT-inducing taxes fixed points

  • Problem: set of all taxes unbounded!
  • Solution: truncate to bounded hypercube

– do all fixed pts now give OPT-inducing taxes?

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Proof of Existence Theorem

  • continuous map: raise edge tax if Nash uses

edge more than OPT, lower tax if opposite

– OPT-inducing taxes fixed points

  • Problem: set of all taxes unbounded!
  • Solution: truncate to bounded hypercube

– do all fixed pts now give OPT-inducing taxes?

  • Key Lemma: for sufficiently large bound, yes!

– requires nontrivial proof (cf., Braess’s Paradox)

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Finding Taxes Efficiently

Thm: if β takes only finitely many values,

such taxes can be found in polynomial time.

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Finding Taxes Efficiently

Thm: if β takes only finitely many values,

such taxes can be found in polynomial time.

  • in fact, set of all such taxes described by

poly-sized list of linear inequalities

– based on [Bergendorff et al 97] – can optimize secondary linear objective

  • existence thm ⇒ there is a feasible point

– otherwise set might be empty

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When Taxes Cause Disutility

Problem #2 with MCT: min delay is holy

grail; exorbitant taxes ignored Question: are small taxes and min latency both possible?

– see also “frugal mechanisms” [Archer/Tardos]

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When Taxes Cause Disutility

Problem #2 with MCT: min delay is holy

grail; exorbitant taxes ignored Question: are small taxes and min latency both possible?

– see also “frugal mechanisms” [Archer/Tardos]

Thm: precise characterization of distribution functions β where both are always possible.

– strong condition, satisfied only with many misers

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When Taxes Cause Disutility

Problem: what about for homogeneous

traffic w/non-refundable taxes?

– e.g., when taxes are time delays

New Goal: minimize total disutility with non-

refundable taxes (delay + taxes paid)

– call new objective fn the cost – taxes can improve cost (Braess’s Paradox) – marginal cost taxes now not a good idea, e.g.: – Thm: w/linear latency fns, MCT never help.

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Taxes Are Powerful but Elusive

Thm: taxes can improve cost by a factor of

n/2 (n = |V|), but no more.

– same for edge removal [Roughgarden FOCS ‘01] – powerful, but can we compute them?

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Taxes Are Powerful but Elusive

Thm: taxes can improve cost by a factor of

n/2 (n = |V|), but no more.

– same for edge removal [Roughgarden FOCS ‘01] – powerful, but can we compute them?

Thm: no heuristic beats the trivial algorithm

  • f assigning no taxes as all (unless P=NP).

– in the worst case – complexity casts doubt on potential for taxes that minimize cost

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My Favorite Open Question

Question: what remains true in multicommodity flow networks?

Note: Existence and algorithmic theorems for taxing heterogeneous traffic will hold if truncation trick still works.

  • need “key lemma” that no bad fixed points exist