Building a Strong Foundation for a Future Internet

Jennifer Rexford ’91Computer Science Department

(and Electrical Engineering and the Center for IT Policy)

http://www.cs.princeton.edu/~jrex

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Clean-Slate Network Architecture

• Clean-slate architecture–Without constraints of today’s artifacts–To have a stronger intellectual foundation–And move beyond the incremental fixes

• Still, some constraints inevitably remain–Resource limitations (CPU, memory, bandwidth)–Time delays between nodes–Independent economic entities–Malicious parties–The need to evolve over time

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An Open Research Challenge

Distributed Protocols(decentralized coordination

between many hosts, routers)

Autonomous Actors(autonomous parties, with

different economic objectives)

Global Properties (stability, scalability, reliability,

security, privacy, managability, …)

?

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Two Forays into a Theory of Networks

• Example topic: Internet routing–What paths should carry the traffic?–How should these paths be computed?–How much traffic should traverse each path?

• Two theoretical approaches–Game theory

Interdomain routing driven by economic incentives

–Optimization theory Protocol as an implicit solution to optimization problem

Game Theory: Applied to Interdomain Routing

+ $$$ = ???

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What is an Internet?

• A “network of networks”–Networks run by different institutions

• Autonomous System (AS)–Routers run by a single institution–With a local routing policy

• ASes have different goals–Different views of which paths are good

• Interdomain routing reconciles those views–Computes end-to-end paths through the Internet

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Conflicting Policies Cause Oscillation

0

1

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1 2 01 0

2 3 02 0

3 1 03 0

Pick the highest-ranked path consistent with your neighbors’ choices.

Only choice!

Top choice!

Only choice!

Better choice!

Only choice!

Better choice!

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Economic Incentives Save the Day

• Two common business relationships– Customer-provider (e.g., Princeton and USLEC)– Peer-peer (e.g., AT&T and Sprint)

• Three economic incentives– No “transit service” for peers and providers– An AS is not its own

indirect customer– Prefer routes through

paying customers

• Provably ensuresa stable system!

2 3

1

d

4

5

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Moving Beyond the Original Model

• How might business relationships evolve?–Backup routes–Siblings

• How might economic incentives evolve?–Desire to attract traffic from others–Accidental and malicious behavior

• How much can we rely on incentives?–Are we willing to rely on economic incentives to

assure the most basic properties of the Internet?–Do we really have a choice?

Optimization Theory: Applied to Traffic Management

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Traffic Management Today

• How much traffic should traverse each path?

End hosts:Congestion control

Operator: Traffic engineering

Routers:Compute paths

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Rethinking Traffic Management

• What should be the objective of the system?

Source rate xi

Ui(xi)

Maximize User Utility

Link utilization ul

f(ul

)

Minimize Link Congestion

Goal: max ∑i Ui(xi) - w∑l

f(ul)

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Routers: Compute link “prices”

Distributed Solutions

• Protocols as distributed optimizers–Link prices: higher as load approaches capacity–Path rates: sending traffic over cheaper paths

Edge nodes: Adjust path sending rates

ss

s

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Moving Beyond the Original Model

• Evaluating protocols in practice–Speed of convergence to optimal flow of traffic–Sensitivity to tunable parameters

• Considering other objectives–E.g., minimizing end-to-end delay

• Supporting multiple classes of traffic–Mix of throughput-sensitive and delay-sensitive–Dynamically adapting the sharing of bandwidth

• Deploying the protocols in real networks!

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Conclusion

• Computer networks are key infrastructure–The stakes are very high–Designs that are worthy of society’s trust

• Inherently an interdisciplinary problem–Game theory, optimization theory, control theory,

cryptography, computer science, coding theory–Domain knowledge and an experimental mindset

• We are making real progress–On creating a “science of computer networks”–And on building and deploying new solutions