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Building a Strong Foundation for a Future Internet Jennifer Rexford ’91 Computer Science Department (and Electrical Engineering and the Center for IT Policy)

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Presentation on theme: "Building a Strong Foundation for a Future Internet Jennifer Rexford ’91 Computer Science Department (and Electrical Engineering and the Center for IT Policy)"— Presentation transcript:

1 Building a Strong Foundation for a Future Internet Jennifer Rexford ’91 Computer Science Department (and Electrical Engineering and the Center for IT Policy) http://www.cs.princeton.edu/~jrex

2 2 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

3 3 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, …) ?

4 4 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

5 Game Theory: Applied to Interdomain Routing + $$$ = ???

6 6 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

7 7 Conflicting Policies Cause Oscillation 0 1 2 3 1 2 0 1 0 2 3 0 2 0 3 1 0 3 0 Pick the highest-ranked path consistent with your neighbors’ choices. Only choice! Top choice! Only choice! Better choice! Only choice! Better choice!

8 8 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 ensures a stable system! 2 3 1 d 4 5

9 9 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?

10 Optimization Theory: Applied to Traffic Management

11 11 Traffic Management Today How much traffic should traverse each path? End hosts: Congestion control Operator: Traffic engineering Routers: Compute paths

12 12 Rethinking Traffic Management What should be the objective of the system? Source rate x i U i (x i ) Maximize User Utility Link utilization u l f(u l ) Minimize Link Congestion Goal: max ∑ i U i (x i ) - w∑ l f(u l )

13 13 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 s s s

14 14 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!

15 15 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


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