The network layer: routing

The network layer: routing

CS168, Fall 2014Sylvia Ratnasamy

http://inst.eecs.berkeley.edu/~cs168/fa14/

Last Time

‣ Forwarding: “data plane” - Directing one data packet- Each router using local routing state

‣ Routing: “control plane” - Computing the forwarding tables that guide packets- Jointly computed by routers using a distributed ptotocol

‣ Routing will be our focus for the next ~2 lectures!

Last Time

‣ Two correctness conditions for routing state:- no deadends

- no loops

Outline

‣ Least-cost path routing

‣ Approach 1: link-state routing

‣ Approach 2: distance-vector routing

‣ Routing in the Internet (next lecture)

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Least-cost path routing

‣ Given: router graph & link costs

‣ Goal: find least-cost path

from each source router to each destination router

7

“Least Cost” Routes

‣ “Least cost” routes an easy way to avoid loops- No sensible cost metric is minimized by traversing a loop

‣ Least cost routes are also “destination-based”- i.e., do not depend on the source- Why is this?

‣ Least-cost paths form a spanning tree

Outline

‣ Least-cost path routing

‣ Approach 1: link-state routing

‣ Approach 2: distance-vector routing

‣ Routing in the Internet

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Routing algorithm for source u

‣ Input: router graph & link costs

‣ Output: least-cost path

from source router u to every other router

24

Dijkstra’s algorithm

‣ Source router considers every other router- starting from next “closest” neighbor

‣ Checks whether it can improve current paths- by using that router as an intermediate point

‣ Ends when all intermediaries have been considered

‣ See text / 61C notes for exact algorithm25

From routing algorithm to protocol

‣ Note: Dijkstra’s is a local computation! - computed by one node given complete network graph

‣ Possibilities:- Option#1: a separate machine runs the algorithm - Option#2: every router runs the algorithm

‣ The Internet currently uses Option#2

26

Link State Routing

‣ Every router knows its local “link state” - router u: “(u,v) with cost=2; (u,x) with cost=1”

‣ A router floods its link state to all other routers- does so periodically or when its link state changes

‣ Hence, every router learns the entire network graph- runs Dijkstra’s locally to compute its forwarding table

‣ OSPF is a link-state protocol (IETF RFC 2328 or 5340)- Berkeley runs OSPF internally!

Link State Routing

‣ Are loops possible?

A and D think that thisis the path to C

E thinks that thisis the path to C

A

ED

CB

FA

ED

CB

F

13

1

15

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55

5

Convergence

‣ All routers have consistent routing information- E.g., all nodes having the same link-state database

‣ Forwarding is consistent after convergence- All nodes have the same link-state database

- All nodes forward packets on same paths

Convergence Delay

‣ Time to achieve convergence

‣ Sources of convergence delay?- time to detect failure- time to flood link-state information- time to re-compute forwarding tables

‣ Performance during convergence period?- lost packets due to blackholes- looping packets- out-of-order packets reaching the destination

Link State Routing

‣ Are loops possible?- yes, until convergence

‣ Scalability?- O(NE) messages - O(N2) computation time - O(network diameter) convergence time - O(N) entries in forwarding table

‣ Do we have to use Dijkstra’s?

Outline

‣ Least-cost path routing

‣ Approach 1: link-state routing

‣ Approach 2: distance-vector routing

‣ Routing in the Internet

32

Experiment

‣ Your job: find the youngest person in the room

‣ Ground Rules- You may not leave your seat, nor shout loudly across the class - You may talk with your immediate neighbors

(hint: “exchange updates” with them)

‣ At the end of 5 minutes, I will pick a victim and ask: - who is the youngest person in the room? (name , date)- which one of your neighbors first told you this information?

Go!

Example of Distributed Computation

I am one hop away

I am one hop away

I am one hop away

I am two hops away

I am two hops away

I am two hops away

I am two hops awayI am three hops away

I am three hops away

DestinationI am three hops away

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Distance-vector routing

‣ Input to each router: local link costs & neighbor

messages

‣ Output of each router: least-cost path to every other

router

48

‣ Distributed algorithm‣ All routers run it “together”

- each router runs its own instance- neighbors exchange and react to each

other’s messages

49

Distance-vector routing

Bellman-Ford algorithm

‣ All neighbors exchange information- Each router checks whether it can improve current

paths by leveraging the new information‣ Ends when no improvement is possible

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min{

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cost(x,u) + du(z),

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for all neighbors n

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Bellman-Ford equation

Bellman-Ford equation

‣ Formalizes the following decision:

- pick as the next hop for destination z the neighbor that results in the least-cost path to z.

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count-to-infinity scenario

Problems with Bellman-Ford

‣ Routing loops- z routes through y, y routes through x

- y loses connectivity to x

- y decides to route through z

‣ Can take a very long time to resolve- Count-to-infinity scenario

68

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poisoned reverse

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∞poisoned reverse∞

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Solution

‣ Poisoned reverse- If z routes to x through y,

z advertises to y that its cost to x is infinite

- y never decides to route to x through z

‣ Often avoids the count-to-infinity problem

Distance Vector Routing

‣ Are loops possible?- yes, until convergence - convergence slower than in Link-State

‣ Scalability?- requires fewer messages than Link-State- O(N) update time on arrival of a new DV from neighbor- O(network diameter) convergence time - O(N) entries in forwarding table

‣ RIP is a protocol that implements DV (IETF RFC 2080)

Does Poison-Reverse Completely Solve the Count-to-Infinity Problem?

A C1

B

D

1

1 11 1

2 2

∞

∞ ∞

100

100 100

3∞

4

∞ 4

56

Outline

‣ Least-cost path routing

‣ Approach 1: link-state routing

‣ Approach 2: distance-vector routing

‣ Routing in the Internet (next time)