ECE 4450:427/527 - Computer Networks
Spring 2016
Dr. Nghi Tran
Department of Electrical & Computer Engineering
Lecture 6.3: Routing
Dr. Nghi Tran (ECE-University of Akron)
ECE 4450:427/527
Computer Networks
1
Internetworking: Discussions
• For Internetworking, we shall look at few subproblems:
• Interconnect links of the same type: Switches
• We consider an important of class switch: Bridges
to interconnect Ethernet segments.
• We also look a way to interconnect disparate
networks and links: Gateways, or now mostly
known as routers. We shall focus on the IP
• Once we are able to interconnect a whole lot of
links and networks with switches and routers, we
will look at a way to find a suitable path, or route
through a network:
• Paths that are efficient, loop free, etc.: Routing
Dr. Nghi Tran (ECE-University of Akron)
ECE 4450:427/527
Computer Networks
2
Recall: IP Routing Table
Dr. Nghi Tran (ECE-University of Akron)
ECE 4450:427/527
Computer Networks
3
What is Routing?
Construct directions from starting point to destination
Dr. Nghi Tran (ECE-University of Akron)
ECE 4450:427/527
Computer Networks
4
Forwarding vs Routing
• Forwarding: data plane
– Directing a data packet to an outgoing link
– Individual router using a forwarding/routing table
• Routing: control plane
– Computing paths the packets will follow
– Routers talking amongst themselves
– Individual router creating a forwarding table
Routing can be simply understood as a process by which routing
table is built
5
Dr. Nghi Tran (ECE-University of Akron)
ECE 4450:427/527
Computer Networks
5
Why Does Routing Matter?
• End-to-end performance
– Quality of the path affects user performance
– Propagation delay, throughput, and packet loss
• Use of network resources
– Balance of the traffic over the routers and links
– Avoiding congestion by directing traffic to lightly-loaded links
• Transient disruptions during changes
– Failures, maintenance, and load balancing
– Limiting packet loss and delay during changes
Dr. Nghi Tran (ECE-University of Akron)
ECE 4450:427/527
Computer Networks
6
Different Types of Routing
• Routing in a GPS device
• Routing in computer networks
– Shortest path
– Smallest delay
– Highest reliability
– Avoid congested nodes
Dr. Nghi Tran (ECE-University of Akron)
ECE 4450:427/527
Computer Networks
7
Routing
• Network as a Graph
• The basic problem of routing is to find the lowest-cost path
between any two nodes
• The cost of a path equals the sum of the costs of all the
edges that make up the path
• Cost: delay, financial cost, probability of failure, etc.
Dr. Nghi Tran (ECE-University of Akron)
ECE 4450:427/527
Computer Networks
8
Routing
• For a simple network, we can calculate all shortest paths
and load them into some nonvolatile storage on each
node.
• Such a static approach has several shortcomings
• It does not deal with node or link failures
• It does not consider the addition of new nodes or links
• It implies that edge costs cannot change
• What is the solution?
• Need a distributed and dynamic protocol
• Two main classes of protocols
• Distance Vector
• Link State
Dr. Nghi Tran (ECE-University of Akron)
ECE 4450:427/527
Computer Networks
9
Distance Vector: Algorithm
• Construct a one-dimensional array (vector) of distances to all other
nodes, with assumption that each node knows the cost of the link
to each of its directly connected neighbors
• Exchange info with immediate neighbors
• Update distances based on received information
• Stop sending updates as soon as no change occurs
Dr. Nghi Tran (ECE-University of Akron)
ECE 4450:427/527
Computer Networks
10
Distance Vector
Initial distances stored at each node (global view) (assume
unit cost for each link)
Dr. Nghi Tran (ECE-University of Akron)
ECE 4450:427/527
Computer Networks
11
Distance Vector
Dest
Cost
Next
Hop
B
1
B
C
1
C
D

–
E
1
E
F
1
F
G

–
Initial routing table at node A, assume unit cost for each link
Now, how about node B?
Dr. Nghi Tran (ECE-University of Akron)
ECE 4450:427/527
Computer Networks
12
Distance Vector: Local View (initial)
Dest
Cost
Next
Hop
Dest
Cost
Next
Hop
Dest
Cost
Next
Hop
B
1
B
A
1
A
A
1
A
C
1
C
C
1
C
B
1
B
D

–
D

–
D
1
D
E
1
E
E

–
E

–
F
1
F
F

–
F

–
G

–
G

–
G

–
Dest
Cost
Next
Hop
Dest
Cost
Next
Hop
Dest
Cost
Next
Hop
Dest
Cost
Next
Hop
A

–
A
1
A
A
1
A
A

–
B

–
B

–
B

–
B

–
C
1
C
C

–
C

–
C

–
E

–
D

–
D

–
D
1
D
F

–
F

–
E

–
E

–
G
1
G
G

–
G
1
G
F
1
F
Dr. Nghi Tran (ECE-University of Akron)
ECE 4450:427/527
Computer Networks
13
Distance Vector – 1st Update for A
1st Update: Every node sends to its
directly connected neighbors its personal
list of distances
1st Update for A
Dest
Cost
Next
Hop
B
1
B
C
1
C
D

–
E
1
E
F
1
F
G

–
Dr. Nghi Tran (ECE-University of Akron)
ECE 4450:427/527
Dest
Cost
Next
Hop
B
1
B
C
1
C
D
2
C
E
1
E
F
1
F
G
2
F
Computer Networks
14
Distance Vector – 1st Update for B?
1st Update
Dest
Cost
Next
Hop
A
1
A
C
1
C
D

–
E

–
F

–
G

–
Dr. Nghi Tran (ECE-University of Akron)
ECE 4450:427/527
Dest
Cost
Next
Hop
A
1
A
C
1
C
D
2
C
E
2
A
F
2
A
G

–
Computer Networks
15
Distance Vector – 1st Update
Dest
Cost
Next
Hop
Dest
Cost
Next
Hop
Dest
Cost
Next
Hop
B
1
B
A
1
A
A
1
A
C
1
C
C
1
C
B
1
B
D
2
C
D
2
C
D
1
D
E
1
E
E
2
A
E
2
A
F
1
F
F
2
A
F
2
A
G
2
F
G

–
G
2
G
Dest
Cost
Next
Hop
Dest
Cost
Next
Hop
Dest
Cost
Next
Hop
Dest
Cost
Next
Hop
A
2
C
A
1
A
A
1
A
A
2
F
B
2
C
B
2
A
B
2
A
B

–
C
1
C
C
2
A
C
2
A
C
2
D
E

–
D

–
D
2
G
D
1
D
F
2
G
F
2
A
E
2
E
E

–
G
1
G
G

–
G
1
G
F
1
F
Dr. Nghi Tran (ECE-University of Akron)
ECE 4450:427/527
Computer Networks
16
Distance Vector – 2nd Update
Dest
Cost
Next
Hop
Dest
Cost
Next
Hop
Dest
Cost
Next
Hop
B
1
B
A
1
A
A
1
A
C
1
C
C
1
C
B
1
B
D
2
C
D
2
C
D
1
D
E
1
E
E
2
A
E
2
A
F
1
F
F
2
A
F
2
A
G
2
F
G
3
C
G
2
G
Dest
Cost
Next
Hop
Dest
Cost
Next
Hop
Dest
Cost
Next
Hop
Dest
Cost
Next
Hop
A
2
C
A
1
A
A
1
A
A
2
F
B
2
C
B
2
A
B
2
A
B
3
D
C
1
C
C
2
A
C
2
A
C
2
D
E
3
C
D
3
A
D
2
G
D
1
D
F
2
G
F
2
A
E
2
E
E
3
F
G
1
G
G
3
A
G
1
G
F
1
F
Dr. Nghi Tran (ECE-University of Akron)
ECE 4450:427/527
Computer Networks
17
Distance Vector: Global View
Final distances stored at each node (global view)
Dr. Nghi Tran (ECE-University of Akron)
ECE 4450:427/527
Computer Networks
18
Distance Vector
• The other common name for this class of algorithm is
Bellman-Ford, after its inventors.
• As we can see, it usually takes a number of
exchanges/updates between neighbors before each node
has complete routing table.
• The process of getting consistent routing information to
all nodes is called convergence: vary
• We have two different circumstances under which a node
decides to send a routing update
• Periodic update
• Triggered update
Dr. Nghi Tran (ECE-University of Akron)
ECE 4450:427/527
Computer Networks
19
Failure of Link F-G
• When a node detects a link failure
•
•
•
•
•
•
F detects that link to G has failed (how?)
F sets distance to G to infinity and sends update to A
A sets distance to G to infinity since it uses F to reach G
A receives periodic update from C with 2-hop path to G
A sets distance to G to 3 and sends update to F
F decides it can reach G in 4 hops via A
Dr. Nghi Tran (ECE-University of Akron)
ECE 4450:427/527
Computer Networks
20
Failure of Link F-G: Updated Tables
A/Dest
Cost
Next
Hop
B/Dest
Cost
Next
Hop
C/Dest
Cost
Next
Hop
B
1
B
A
1
A
A
1
A
C
1
C
C
1
C
B
1
B
D
2
C
D
2
C
D
1
D
E
1
E
E
2
A
E
2
A
F
1
F
F
2
A
F
2
A
G
3
C
G
3
C
G
2
G
D/Dest
Cost
Next
Hop
E/Dest
Cost
Next
Hop
F/Dest
Cost
Next
Hop
G/Dest
Cost
Next
Hop
A
2
C
A
1
A
A
1
A
A
3
D
B
2
C
B
2
A
B
2
A
B
3
D
C
1
C
C
2
A
C
2
A
C
2
D
E
3
C
D
3
A
D
4
C
D
1
D
F
3
C
F
2
A
E
2
E
E
3
F
G
1
G
G
4
A
G
4
A
F
4
D
Dr. Nghi Tran (ECE-University of Akron)
ECE 4450:427/527
Computer Networks
21
Drawback
– Suppose the link from A to E goes down
– In the next round of updates, A advertises a distance of infinity to E,
but C advertise a distance of 2 to E
– Depending on the exact timing of events, the following might happen
• Node B, upon hearing that E can be reached in 2 hops from C,
concludes that it can reach E in 3 hops and advertises this to A
• Node A concludes it can reach E in 4 hops and advertises this to C
• Node C concludes that it can reach E in 5 hops; and so on.
• This cycle stops only when the distances reach some number that
is large enough to be considered infinite
Count-to-infinity problem
Dr. Nghi Tran (ECE-University of Akron)
ECE 4450:427/527
Computer Networks
22
Solutions
• One technique to improve the time to stabilize routing is called split
horizon
– When a node sends a routing update to its neighbors, it does not send those
routes it learned from each neighbor back to that neighbor
– For example, if B has the route (E, 2, A) in its table, then it knows it must have
learned this route from A, and so whenever B sends a routing update to A, it
does not include the route (E, 2) in that update
• In a stronger version of split horizon, called split horizon with poison
reverse
– B actually sends that back route to A, but it puts negative information in the
route to ensure that A will not eventually use B to get to E
– For example, B sends the route (E, ∞) to A
Dr. Nghi Tran (ECE-University of Akron)
ECE 4450:427/527
Computer Networks
23
Routing Information Protocol (RIP)
• Early routing protocol for IP networks
• Distance-vector algorithm where vertices are
networks and not hosts
• Valid hop count (distances) 1-15, with 16
representing infinity
• Limited to fairly small networks
Dr. Nghi Tran (ECE-University of Akron)
ECE 4450:427/527
Computer Networks
24
Metric/Cost in Real World
• Can we just assign a cost of 1 to all links?
• Certainly, there are so many ways to define cost:
• Number of packets queued waiting to be transmitted
• Consider both bandwidth and latency
• In the current real world
• Common approach: a constant/link bandwidth
• It means metric changes rarely if at all and only under
the control of network administrator
• Why?
• i) Dynamically changing metrics are too unstable;
• ii) Many networks today lack the great disparity of
speeds and latencies
Dr. Nghi Tran (ECE-University of Akron)
ECE 4450:427/527
Computer Networks
25
Distance Vector vs. Link-State
• Distance vector:
• each node talks only to its directly
connected neighbors …
• but it tell them everything it has learned,
i.e., distance to all nodes
• Link-state:
• each node talks to all other nodes…
• but it tells them only what it knows for sure,
i.e., state of its directly connected links
Dr. Nghi Tran (ECE-University of Akron)
ECE 4450:427/527
Computer Networks
26
Link-State Routing
Strategy: Send to all nodes (not just neighbors)
information about directly connected links (not entire
routing table) and associated cost.
• Rely on two key mechanisms:
– Reliable flooding: Make sure all nodes get the
above information of other nodes
– Route calculation: Once a node has a copy of the
information from every other node, it is able to
compute a complete map of the network, and then
can decide the best route to each destination
Dr. Nghi Tran (ECE-University of Akron)
ECE 4450:427/527
Computer Networks
27
Reliable Flooding
• Objective: Make sure all nodes get the link-state
information of other nodes: Knowledge of directly
connected neighbors and associated cost for each node
• Each node creates an update packet called link-state packet
(LSP) with the following information:
• ID of the node that created LSP
• Cost of link to each directly connected neighbor
• Sequence number (SEQNO)
• Time-to-live for this packet
Reliable flooding: Make sure all nodes get LSP from the
other nodes.
Dr. Nghi Tran (ECE-University of Akron)
ECE 4450:427/527
Computer Networks
28
Reliable Flooding
• Transmission of LSPs between adjacent routers using ACK
and transmission. But how to send an LSP to all nodes?
• We need some more steps to reliably flood an LSP to all
nodes: controlled flooding
• A node x receives a copy of LSP originated from y.
• x then needs to check if it has already had a copy. If
not, store it. If it has, compare sequence number,
keep a newer one.
• If the received LSP is new, x sends a copy of LSP to
all neighbors, except the one from which LSP was
received (why?).
• Neighbors then turn around and do the same
thing: most recent copy of LSP reaches all nodes.
Dr. Nghi Tran (ECE-University of Akron)
ECE 4450:427/527
Computer Networks
29
Reliable Flooding
Reliable Flooding
Flooding of link-state packets.
(a) LSP arrives at node X;
(b) X floods LSP to A and C;
(c) A and C flood LSP to B (but not X);
(d) flooding is complete
Dr. Nghi Tran (ECE-University of Akron)
ECE 4450:427/527
Computer Networks
30
Route Calculation
• Now, assume a given node has copies of LSPs from every
other node:
• it is able to compute a complete map for the topology
of the network
• and from this map it is able to decide the best routes to
each destination
• But how to decide/calculate the best route to each
destination?
• The solution is based on a well-known algorithm from
graph theory – Dijkstra’s shortest-path algorithm
Dr. Nghi Tran (ECE-University of Akron)
ECE 4450:427/527
Computer Networks
31
Shortest-Path Problem: Statement
• Given: network topology with link costs
– c(x,y): link cost from node x to node y
– Infinity if x and y are not direct neighbors
• Compute: least-cost paths to all nodes
– From a given source u to all other nodes
– For each node a: u stores a’s predecessor node along
path from u to a, & cost.
2
3
u
2
1
4
Dr. Nghi Tran (ECE-University of Akron)
ECE 4450:427/527
1
1
4
a
5
3
Computer Networks
32
Dijkstra’s Algorithm: Overview
• Iterative algorithm for a given source node u:
– After k iterations, know least-cost path to k nodes
• S: set of nodes whose least-cost path known
– Initially, S = {u} where u is the source node
– Add one node to S in each iteration
• D(a): current cost of path from source to node a
– Initially, D(a) = c(u, a) for all nodes a adjacent to u
– … and D(a) = ∞ for all other nodes a
– Continuously update D(a) as shorter paths are learned
Dr. Nghi Tran (ECE-University of Akron)
ECE 4450:427/527
Computer Networks
33
Dijkstra’s Algorithm: Implementation
1 Initialization:
2 S = {u}
3 for all nodes {a}
4 If a adjacent to u {
5
D(a) = c(u,a)
6 else D(v) = ∞
7
8 Loop
9 Find b not in S with the smallest D(b)
10 Add b to S, store D(b) and P(b) (predecessor node)
11 update D(a) for all {a} adjacent to b and not in S:
12
D(a) = min{D(a), D(b) + c(b,a)}
13 until all nodes in S
Dr. Nghi Tran (ECE-University of Akron)
ECE 4450:427/527
Computer Networks
34
Example
2
3
2
2
1
1
3
4
2
1
5
4
2
5
4
3
3
2
1
1
1
4
1
2
3
1
1
3
4
2
5
4
Dr. Nghi Tran (ECE-University of Akron)
1
4
3
ECE 4450:427/527
1
1
4
5
3
Computer Networks
35
Example (Cont.)
2
3
2
2
1
1
3
1
4
2
1
5
4
2
5
4
3
3
2
1
1
1
4
1
2
3
1
3
4
2
1
5
4
Dr. Nghi Tran (ECE-University of Akron)
4
3
ECE 4450:427/527
1
1
4
5
3
Computer Networks
36
Dijkstra’s Table
Step
S
v
w
x
y
z
s
t
D(v)
P(v)
D(w)
P(w)
D(x)
P(x)
D(y)
P(y)
D(z)
P(z)
D(s)
P(s)
D(t)
P(t)
3
u
2
u
3
w
5
v
6
y
6
w
8
x
.
.
.
.
.
.
7
u,w,v,x,y
,z,s,t
Dr. Nghi Tran (ECE-University of Akron)
ECE 4450:427/527
Computer Networks
37
Shortest-Path Tree
• Shortest-path tree from • Routing table at u
u
v
3
u
1
2
1
x
1
w
link
y
2
4
5
4
s
Dr. Nghi Tran (ECE-University of Akron)
z
t
3
ECE 4450:427/527
v
w
x
y
z
s
t
(u,v)
(u,w)
(u,w)
(u,v)
(u,v)
(u,w)
(u,w)
Computer Networks
38
Open Shortest First Path (OSPF)
• It is the most widely used link-state routing protocols in
practice
• Open: Publicly available
• SPF: Alternative name for link-state
• OSPF adds a number of features to the basic link-state
• Authentication: Make sure all nodes can be trusted
• Additional hierarchy: Network domain divided further
in to areas: a router might just need to get to a right
area
• Load balancing: Allow multiple routes to the same
place to be assigned the same cost: traffic distributed
evenly to those routers
Dr. Nghi Tran (ECE-University of Akron)
ECE 4450:427/527
Computer Networks
39
Distance Vector vs. Link-State
• Distance vector: each node talks only to its directly
connected neighbors, but it tell them everything it
has learned, i.e., distance to all nodes
• Link-state: each node talks to all other nodes, but
it tells them only what it knows for sure, i.e., state
of its directly connected links
Dr. Nghi Tran (ECE-University of Akron)
ECE 4450:427/527
Computer Networks
40
Distance Vector vs. Link-State
• Who is the winner?
Message complexity
• LS: with n nodes, E links, O(nE)
msgs sent . A lot of information
needs to be stored.
• DV: exchange between neighbors
only
Speed of Convergence
• LS: O(n2) algorithm requires O(nE)
msgs
• DV: convergence time varies
– may be routing loops
– count-to-infinity problem
Dr. Nghi Tran (ECE-University of Akron)
Robustness: what happens if
router malfunctions,
misbehaves?
LS:
– node can advertise incorrect
link cost
– each node computes only its
own table, providing a degree
of robustness
DV:
ECE 4450:427/527
– DV node can advertise
incorrect path cost
– each node’s table used by
others , error propagate thru
network
Computer Networks
41
Routing in the Internet
• Routing protocols we have learned so far: idealization, all
routers identical, flat network
• Internet: Network of hundreds of thousands of networks:
Not possible to directly using those protocols: they do not
scale to those kinds of numbers!!!
• We need something else!!!
Dr. Nghi Tran (ECE-University of Akron)
ECE 4450:427/527
Computer Networks
42
Routing in the Internet
• Internet is organized as autonomous systems (AS) each of
which is under the control of a single administrative entity
• Autonomous System (AS)
– corresponds to an administrative domain
– examples: University, company, backbone network, as may
the network of a single ISP
– AS chooses its own routing protocol, e.g., distance-vector
or link-state
• Divide routing problem in two parts:
• Intra-domain: We have already learned
• Inter-domain: Border Gateway Protocol (BGP) (BGP-v4)
Dr. Nghi Tran (ECE-University of Akron)
ECE 4450:427/527
Computer Networks
43
BGP
• Few books dedicated to BGP
• Key points:
• Assumes the Internet is an arbitrarily interconnected
set of AS‘s
• Impossible to define optimal path
• Advertise only reachability: complete paths as an
enumerated lists of ASs to reach a particular network
• Does not belong to either distance-vector or link-state
• For further discussions (high points), see Chapter 4.1.2
Dr. Nghi Tran (ECE-University of Akron)
ECE 4450:427/527
Computer Networks
44