Data Communication and Networks

1. Data Communication and Networks Lecture 8 Networks: (Routing) October 23, 2003 Joseph Conron Computer Science Department New York University jconron@cs.nyu.edu

2. Some Perspective on Routing ….. • When we wish to take a long trip by car, we consult a road map. • The road map shows the possible routes to our destination. • It might show us the shortest distance, but, it can’t always tell us what we really want to know: • What is the fastest route! • Why is this not always obvious? • Question: What’s the difference between you and network packet?

3. Packets are Dumb, Students are Smart! • We adapt to traffic conditions as we go. • Packets depend on routers to choose how they get their destination. • Routers have maps just like we do. These are called routing tables. • What we want to know is: • How to these tables get constructed/updated? • How are routes chosen using these tables?

4. Network Information Source and Update Timing • Routing decisions usually based on knowledge of network (not always) • Distributed routing • Nodes use local knowledge • May collect info from adjacent nodes • May collect info from all nodes on a potential route • Central routing • Collect info from all nodes • Update timing • When is network info held by nodes updated • Fixed - never updated • Adaptive - regular updates

5. Routing Strategies • Fixed • Flooding • Random • Adaptive

6. Fixed Routing • Single permanent route for each source to destination pair • Determine routes using a least cost algorithm (chapter 12.3) • Route fixed, at least until a change in network topology

7. Fixed RoutingTables

8. Flooding • No network info required • Packet sent by node to every neighbor • Incoming packets retransmitted on every link except incoming link • Eventually a number of copies will arrive at destination • Each packet is uniquely numbered so duplicates can be discarded • Nodes can remember packets already forwarded to keep network load in bounds • Can include a hop count in packets

9. Flooding Example

10. Properties of Flooding • All possible routes are tried • Very robust • At least one packet will have taken minimum hop count route • Can be used to set up virtual circuit • All nodes are visited • Useful to distribute information (e.g. routing)

11. Random Routing • Node selects one outgoing path for retransmission of incoming packet • Selection can be random or round robin • Can select outgoing path based on probability calculation • No network info needed • Route is typically not least cost nor minimum hop

12. Adaptive Routing • Used by almost all packet switching networks • Routing decisions change as conditions on the network change • Failure • Congestion • Requires info about network • Decisions more complex • Tradeoff between quality of network info and overhead • Reacting too quickly can cause oscillation • Too slowly to be relevant

13. Adaptive Routing - Advantages • Improved performance • Aid congestion control (See chapter 13) • Complex system • May not realize theoretical benefits

14. Classification • Based on information sources • Local (isolated) • Route to outgoing link with shortest queue • Can include bias for each destination • Rarely used - do not make use of easily available info • Adjacent nodes • All nodes

15. Isolated Adaptive Routing

16. ARPANET Routing Strategies(1) • First Generation • 1969 • Distributed adaptive • Estimated delay as performance criterion • Bellman-Ford algorithm (chapter 12.3) • Node exchanges delay vector with neighbors • Update routing table based on incoming info • Doesn't consider line speed, just queue length • Queue length not a good measurement of delay • Responds slowly to congestion

17. ARPANET Routing Strategies(2) • Second Generation • 1979 • Uses delay as performance criterion • Delay measured directly • Uses Dijkstra’s algorithm (Chapter 12.3) • Good under light and medium loads • Under heavy loads, little correlation between reported delays and those experienced

18. ARPANET Routing Strategies(3) • Third Generation • 1987 • Link cost calculations changed • Measure average delay over last 10 seconds • Normalize based on current value and previous results

19. Static Vs. Dynamic Routing • Routes are static if they do not change. • Route table is loaded once at startup and all changes are manual • Computers at the network edge use static routing. • Routes are dynamic if the routing table information can change over time (without human intervention. • Internet routers use dynamic routing.

20. Routing Table Example

21. Dynamic Routing and Routers • To insure that routers know how to reach all possible destinations, routers exchange information using a routing protocol. • But, we cannot expect every router to know about every other router. • Too much Internet traffic would be generated. • Tables would be huge (106 routers) • Algorithms to choose “best” path would never terminate. • How to handle this?

22. Autonomous Systems (AS) • Routers are divided into groups known as an autonomous systems (AS). • ASs communicate using an Exterior Routing Protocol (Intra-AS Routing) • Routers within an AS communicate using an Interior Routing Protocol (Inter-AS Routing)

23. Interior and Exterior Routing

24. Why different Intra and Inter-AS routing ? Policy: • Inter-AS: admin wants control over how its traffic routed, who routes through its net. • Intra-AS: single admin, so no policy decisions needed Scale: • hierarchical routing saves table size, reduced update traffic Performance: • Intra-AS: can focus on performance • Inter-AS: policy may dominate over performance

25. Graph abstraction for routing algorithms: graph nodes are routers graph edges are physical links link cost: delay, $ cost, or congestion level 5 3 5 2 2 1 3 1 2 1 A D E B F C Routing protocol Routing Algorithms Goal: determine “good” path (sequence of routers) thru network from source to dest. • “good” path: • typically means minimum cost path • other def’s possible

26. Static or dynamic? Static: routes change slowly over time Dynamic: routes change more quickly periodic update in response to link cost changes Routing Algorithm classification

27. Routing Algorithm classification • Global or decentralized? • Global: • all routers have complete topology, link cost info • “link state” algorithms • Decentralized: • router knows physically-connected neighbors, link costs to neighbors • iterative process of computation, exchange of info with neighbors • “distance vector” algorithms

28. 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 A Link-State Routing Algorithm

29. A Link-State Routing Algorithm • 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

30. Dijsktra’s Algorithm 1 Initialization: 2 N = {A} 3 for all nodes v 4 if v adjacent to A 5 then D(v) = c(A,v) 6 else D(v) = infty 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

31. 5 3 5 2 2 1 3 1 2 1 A D E B F C Dijkstra’s algorithm: example D(B),p(B) 2,A 2,A 2,A D(D),p(D) 1,A D(C),p(C) 5,A 4,D 3,E 3,E D(E),p(E) infinity 2,D Step 0 1 2 3 4 5 start N A AD ADE ADEB ADEBC ADEBCF D(F),p(F) infinity infinity 4,E 4,E 4,E

32. Algorithm 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 A A A D D D D B B B B C C C C 2+e 2+e 0 0 1 1 1+e 1+e 0 e 0 0 Dijkstra’s algorithm, discussion 1 1+e 0 2+e 0 0 0 0 e 0 1 1+e 1 1 e … recompute … recompute routing … recompute initially

33. iterative: continues until no nodes exchange info. self-terminating: no “signal” to stop asynchronous: nodes need not exchange info/iterate in lock step! distributed: each node communicates only with directly-attached neighbors Distance Table data structure each node has its own row for each possible destination column for each directly-attached neighbor to node example: in node X, for dest. Y via neighbor Z: distance from X to Y, via Z as next hop X = D (Y,Z) Z c(X,Z) + min {D (Y,w)} = w Distance Vector Routing Algorithm

34. cost to destination via E D () A B C D A 1 7 6 4 B 14 8 9 11 D 5 5 4 2 1 7 2 8 1 destination 2 A D E B C E E E D (C,D) D (A,D) D (A,B) B D D c(E,D) + min {D (A,w)} c(E,D) + min {D (C,w)} c(E,B) + min {D (A,w)} = = = w w w = = = 2+3 = 5 8+6 = 14 2+2 = 4 Distance Table: example loop! loop!

35. cost to destination via E D () A B C D A 1 7 6 4 B 14 8 9 11 D 5 5 4 2 destination Distance table gives routing table Outgoing link to use, cost A B C D A,1 D,5 D,4 D,2 destination Routing table Distance table

36. Iterative, asynchronous: each local iteration caused by: local link cost change message from neighbor: its least cost path change from neighbor Distributed: each node notifies neighbors only when its least cost path to any destination changes neighbors then notify their neighbors if necessary wait for (change in local link cost of msg from neighbor) recompute distance table if least cost path to any dest has changed, notify neighbors Distance Vector Routing: overview Each node:

37. Distance Vector Algorithm: At all nodes, X: 1 Initialization: 2 for all adjacent nodes v: 3 D (*,v) = infty /* 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 */ X X X w

38. 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 X X w X X w X w

39. 2 1 7 X Z Y Distance Vector Algorithm: example

40. 2 1 7 Y Z X X c(X,Y) + min {D (Z,w)} c(X,Z) + min {D (Y,w)} D (Y,Z) D (Z,Y) = = w w = = 7+1 = 8 2+1 = 3 X Z Y Distance Vector Algorithm: example

41. 1 4 1 50 X Z Y 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) algorithm terminates “good news travels fast”

42. 60 4 1 50 X Z Y Distance Vector: link cost changes Link cost changes: • good news travels fast • bad news travels slow - “count to infinity” problem! algorithm continues on!

43. 60 4 1 50 X Z Y 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? algorithm terminates

44. 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(n**2) algorithm requires O(nE) msgs may have oscillations DV: convergence time varies may be routing loops count-to-infinity problem Comparison of LS and DV algorithms

45. Comparison of LS and DV algorithms • 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 propagates thru network

46. RIP ( Routing Information Protocol) • Distance vector algorithm • Included in BSD-UNIX Distribution in 1982 • Distance metric: # of hops (max = 15 hops) • Can you guess why? • Distance vectors: exchanged every 30 sec via Response Message (also called advertisement) • Each advertisement: route to up to 25 destination nets

47. OSPF (Open Shortest Path First) • “open”: publicly available • Uses Link State algorithm • LS packet dissemination • Topology map at each node • Route computation using Dijkstra’s algorithm • OSPF advertisement carries one entry per neighbor router • Advertisements disseminated to entire AS (via flooding)