Announcement

Project 2 due next week! Homework 3 available soon, will put it

online Recitation tomorrow on Minet and project

2

Outline

Introduction and Network Service Models

Routing Principles Link State Algorithm Distance Vector Algorithm

Network layer functions

transport packet from sending to receiving hosts

network layer protocols in every host, router

three important functions: path determination: route

taken by packets from source to dest. Routing algorithms

forwarding: move packets from router’s input to appropriate router output

call setup: some network architectures require router call setup along path before data flows

networkdata linkphysical

networkdata linkphysical

networkdata linkphysical

networkdata linkphysical

networkdata linkphysical

networkdata linkphysical

networkdata linkphysical

networkdata linkphysical

application

transportnetworkdata linkphysical

application

transportnetworkdata linkphysical

Virtual circuits

call setup, teardown for each call before data can flow

each packet carries VC identifier (not destination host ID)

every router on source-dest path maintains “state” for each passing connection

“source-to-dest path behaves much like telephone circuit” performance-wise network actions along source-to-dest path

Virtual circuits: signaling protocols

used to setup, maintain teardown VC used in ATM, frame-relay, X.25 not used in today’s Internet

application

transportnetworkdata linkphysical

application

transportnetworkdata linkphysical

1. Initiate call 2. incoming call

3. Accept call4. Call connected5. Data flow begins 6. Receive data

Datagram networks: the Internet model no call setup at network layer routers: no state about end-to-end connections

no network-level concept of “connection”

packets forwarded using destination host address packets between same source-dest pair may take

different paths

application

transportnetworkdata linkphysical

application

transportnetworkdata linkphysical

1. Send data 2. Receive data

Datagram or VC network: why?

Internet data exchange among

computers “elastic” service, no

strict timing req. “smart” end systems

(computers) can adapt, perform

control, error recovery simple inside network,

complexity at “edge” many link types

different characteristics uniform service difficult

ATM evolved from telephony human conversation:

strict timing, reliability requirements

“dumb” end systems telephones complexity inside

network

Outline

Introduction and Network Service Models

Routing Principles Link State Algorithm Distance Vector Algorithm

Router Architecture Overview

Two key router functions: run routing algorithms/protocol (RIP, OSPF, BGP) forwarding datagrams from incoming to outgoing link

u

yx

wv

z2

2

13

1

1

2

53

5

Graph: G = (N,E)

N = set of routers = { u, v, w, x, y, z }

E = set of links ={ (u,v), (u,x), (v,x), (v,w), (x,w), (x,y), (w,y), (w,z), (y,z) }

Graph abstraction

Remark: Graph abstraction is useful in other network contexts

Example: P2P, where N is set of peers and E is set of TCP connections

Graph abstraction: costs

u

yx

wv

z2

2

13

1

1

2

53

5 • c(x,x’) = cost of link (x,x’)

- e.g., c(w,z) = 5

• cost could always be 1, or inversely related to bandwidth,or inversely related to congestion

Cost of path (x1, x2, x3,…, xp) = c(x1,x2) + c(x2,x3) + … + c(xp-1,xp)

Question: What’s the least-cost path between u and z ?

Routing algorithm: algorithm that finds least-cost path

Routing Algorithm classification

Global or decentralized information?

Global: all routers have complete

topology, link cost info “link state” algorithmsDecentralized: router knows physically-

connected neighbors, link costs to neighbors

iterative process of computation, exchange of info with neighbors

“distance vector” algorithms

Static or dynamic?Static: routes change slowly

over timeDynamic: routes change more

quickly periodic update in response to link

cost changes

A Link-State Routing Algorithm

Dijkstra’s algorithm net topology, link costs

known to all nodes accomplished via “link

state broadcast” all nodes have same

info computes least cost paths

from one node (‘source”) to all other nodes gives routing table for

that node iterative: after k iterations,

know least cost path to k dest.’s

Notation: c(i,j): link cost from node

i to j. cost infinite if not direct neighbors

D(v): current value of cost of path from source to dest. V

p(v): predecessor node along path from source to v, that is next v

N: set of nodes whose least cost path definitively known

Dijsktra’s Algorithm

1 Initialization: 2 N' = {u} 3 for all nodes v 4 if v adjacent to u 5 then D(v) = c(u,v) 6 else D(v) = ∞ 7 8 Loop 9 find w not in N' such that D(w) is a minimum 10 add w to N' 11 update D(v) for all v adjacent to w and not in N' : 12 D(v) = min( D(v), D(w) + c(w,v) ) 13 /* new cost to v is either old cost to v or known 14 shortest path cost to w plus cost from w to v */ 15 until all nodes in N'

Dijkstra’s algorithm: example

Step012345

N'u

uxuxy

uxyvuxyvw

uxyvwz

D(v),p(v)2,u2,u2,u

D(w),p(w)5,u4,x3,y3,y

D(x),p(x)1,u

D(y),p(y)∞

2,x

D(z),p(z)∞ ∞

4,y4,y4,y

u

yx

wv

z2

2

13

1

1

2

53

5

Dijkstra’s algorithm: example (2)

u

yx

wv

z

Resulting shortest-path tree from u:

vx

y

w

z

(u,v)(u,x)

(u,x)

(u,x)

(u,x)

destination link

Resulting forwarding table in u:

Dijkstra’s algorithm, discussionAlgorithm complexity: n nodes each iteration: need to check all nodes, w, not in N n*(n+1)/2 comparisons: O(n^2) more efficient implementations possible: O(nlogn)

Oscillations possible: e.g., link cost = amount of carried traffic

A

D

C

B1 1+e

e0

e

1 1

0 0

initially

A

D

C

B2+e 0

001+e1

… recomputerouting

A

D

C

B0 2+e

1+e10 0

… recompute

A

D

C

B2+e 0

e01+e1

… recompute

Distance Vector Algorithm

Bellman-Ford Equation (dynamic programming)

Definedx(y) := cost of least-cost path from x to y

Then

dx(y) = min {c(x,v) + dv(y) }

where min is taken over all neighbors v of x

v

Bellman-Ford example

u

yx

wv

z2

2

13

1

1

2

53

5Clearly, dv(z) = 5, dx(z) = 3, dw(z) = 3

du(z) = min { c(u,v) + dv(z), c(u,x) + dx(z), c(u,w) + dw(z) } = min {2 + 5, 1 + 3, 5 + 3} = 4

Node that achieves minimum is nexthop in shortest path ➜ forwarding table

B-F equation says:

Distance Vector Algorithm

Dx(y) = estimate of least cost from x to y

Distance vector: Dx = [Dx(y): y є N ] Node x knows cost to each neighbor v:

c(x,v) Node x maintains Dx = [Dx(y): y є N ] Node x also maintains its neighbors’

distance vectors For each neighbor v, x maintains

Dv = [Dv(y): y є N ]

Distance vector algorithm

Basic idea: Each node periodically sends its own distance

vector estimate to neighbors When a node x receives new DV estimate from

neighbor, it updates its own DV using B-F equation:

Dx(y) ← minv{c(x,v) + Dv(y)} for each node y ∊ N

Under minor, natural conditions, the estimate Dx(y) converge to the actual least cost dx(y)

Distance Vector Algorithm

Iterative, asynchronous: each local iteration caused by:

local link cost change DV update message from

neighbor

Distributed: each node notifies

neighbors only when its DV changes neighbors then notify

their neighbors if necessary

wait for (change in local link cost of msg from neighbor)

recompute estimates

if DV to any dest has

changed, notify neighbors

Each node:

x y z

xyz

0 2 7

∞ ∞ ∞∞ ∞ ∞

from

cost to

from

from

x y z

xyz

∞ ∞

∞ ∞ ∞

cost to

x y z

xyz

∞ ∞ ∞7 1 0

cost to

∞2 0 1

∞ ∞ ∞

x y z

xyz

0 2 3

from

cost to

x y z

xyz

0 2 3

from

cost to

x y z

xyz

0 2 3

from

cost to

2 0 13 1 0

2 0 1

3 1 0

2 0 1

3 1 0

time

x z12

7

y

node x table

node y table

node z table

Dx(y) = min{c(x,y) + Dy(y), c(x,z) + Dz(y)} = min{2+0 , 7+1} = 2

x y z

xyz

0 2 3

from

cost to

x y z

xyz

0 2 7

from

cost to

x y z

xyz

0 2 7

from

cost to

2 0 17 1 0

2 0 17 1 0

2 0 13 1 0

Dx(z) = min{c(x,y) + Dy(z), c(x,z) + Dz(z)} = min{2+1 , 7+0} = 3

Distance Vector: link cost changes

Link cost changes: node detects local link cost

change updates distance table (line 15) if cost change in least cost path,

notify neighbors (lines 23,24)

X Z14

50

Y1

algorithmterminates“good

news travelsfast”

Distance Vector: link cost changes

Link cost changes: good news travels fast bad news travels slow -

“count to infinity” problem! X Z14

50

Y60

algorithmcontinues

on!

Distance Vector: poisoned reverse

If Z routes through Y to get to X : Z tells Y its (Z’s) distance to X is infinite (so

Y won’t route to X via Z) will this completely solve count to infinity

problem? X Z

14

50

Y60

algorithmterminates

Comparison of LS and DV algorithms

Message complexity LS: with n nodes, E links,

O(nE) msgs sent each DV: exchange between

neighbors only convergence time varies

Speed of Convergence LS: O(n2) algorithm requires

O(nE) msgs may have oscillations

DV: convergence time varies may be routing loops count-to-infinity problem

Robustness: what happens if router malfunctions?

LS: node can advertise

incorrect link cost each node computes only

its own table

DV: DV node can advertise

incorrect path cost each node’s table used by

others • error propagate thru

network

Backup Slides

Distance Table: example

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CB7

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2

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D ()

A

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D

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D

5

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2

Ecost to destination via

dest

inat

ion

D (C,D)E

c(E,D) + min {D (C,w)}D

w== 2+2 = 4

D (A,D)E

c(E,D) + min {D (A,w)}D

w== 2+3 = 5

D (A,B)E

c(E,B) + min {D (A,w)}B

w== 8+6 = 14

loop!

loop!

Distance table gives routing table

D ()

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B

C

D

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1

7

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Ecost to destination via

dest

inat

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B

C

D

A,1

D,5

D,4

D,2

Outgoing link to use, cost

dest

inat

ion

Distance table Routing table

Distance Vector Algorithm:

1 Initialization: 2 for all adjacent nodes v: 3 D (*,v) = infinity /* the * operator means "for all rows" */ 4 D (v,v) = c(X,v) 5 for all destinations, y 6 send min D (y,w) to each neighbor /* w over all X's neighbors */

XX

Xw

At all nodes, X:

Distance Vector Algorithm (cont.):8 loop 9 wait (until I see a link cost change to neighbor V 10 or until I receive update from neighbor V) 11 12 if (c(X,V) changes by d) 13 /* change cost to all dest's via neighbor v by d */ 14 /* note: d could be positive or negative */ 15 for all destinations y: D (y,V) = D (y,V) + d 16 17 else if (update received from V wrt destination Y) 18 /* shortest path from V to some Y has changed */ 19 /* V has sent a new value for its min DV(Y,w) */ 20 /* call this received new value is "newval" */ 21 for the single destination y: D (Y,V) = c(X,V) + newval 22 23 if we have a new min D (Y,w)for any destination Y 24 send new value of min D (Y,w) to all neighbors 25 26 forever

w

XX

XX

X

w

w