TIE Breaking: Tunable
Interdomain Egress Selection
Renata Teixeira
Laboratoire d’Informatique de Paris 6
Universit é Pierre et Marie Curie with Tim Griffin (Cambridge), Mauricio Resende (AT&T), and Jennifer Rexford (Princeton)

Internet as a
Communication Infrastructure performance problems
2

Two-Tier Routing Architecture
Web
Server
Internet
Sprint
User
Interdomain routing (BGP)
Selects AS-level path based on policies
Intradomain routing (IGP)
Most common: OSPF, IS-IS
Selects shortest path from ingress to egress based on link weights
3

User
Selecting Among Multiple
Egresses Today
Web
Server
Sprint
SF
NY
1 1
30
5
1
25
LA
1
B
B’s IGP distance d(B,NY): 2 d(B,SF): 31 d(B,LA): 26
Hot-potato routing
BGP selects closest egress by comparing IGP distances
4

However,
HotPotato Routing is…
 Too disruptive
 Small changes inside can lead to big disruptions dst
9
4
F
3
11
D
8
3
E
8
10
4
G
5
6
C
Consequences
-Transient forwarding instability
-Traffic shift (largest traffic variations)
-BGP updates to other domains
5

However,
HotPotato Routing is…
 Too disruptive
 Small changes inside can lead to big disruptions
 Too restrictive
 Egress selection mechanism dictates a policy
 Too convoluted
 IGP metrics determine BGP egress selection
 IGP paths and egress selection are coupled
6

Maybe a Fixed Ranking?
 Goal: No disruptions because of internal changes
 Solution
 Each router has a fixed ranking of egresses
 Select the highest-ranked egress for each destination
 Use tunnels from ingress to egress dst
9
D
3
4
F 5 8
3
 Disadvantage
C
 Sometimes changing egresses would be useful
E
8
10
4
G
7

Egress Selection Mechanisms hot-potato routing
Explore trade-off fixed ranking robustness to internal changes
8

Metrics for Ranking Egresses
 Egress selection mechanisms are based on a metric (m) that each ingress router (i) uses to rank each egress router (e) for a destination
 Hot-potato routing
• m is the intradomain distance (d(i,e))
 Fixed ranking
• m is a constant
9

Goals of New Metric
 Configurable
 Implement a wide-range of egress selection policies
 Simple computation
 Compute on-line, in real-time
 Based on information already available in routers (distance)
 Easy to optimize
 Expressive for a management system to optimize
 Fine control
 Each ingress can implement its own ranking policy for each destination
10

TIE: Tunable Interdomain
Egress Selection m (e) =
 i
(e) . d(i,e) +
 i
(dst,e)
 constant
 intradomain  and

 Allow a wide variety of egress selection policies
 Hot-potato:

=1,

= 0
 Fixed ranking:

=0,

= constant rank
 Requirements
 Small change in router decision logic
 Use of tunnels (as with fixed ranking)
11

Using TIE
Management
System
Administrator defines policy
Run optimization

,

Configure routers
Routers Upon
 and
 change or routing change
Path computation using m i
(dst,e)
Forwarding table
12

Configuring TIE to
Minimize Sensitivity
Network topology
Set of egress routers per prefix
Set of failures
Management System
Simulation Phase system of inequalities
Optimization Phase configure routers with values
 i
(dst,e) and
 i
(dst,e) that minimize sensitivity
13

Simulation Phase dst
B
A
20
11
10
9
At design time: C
Output of
C
(dst,B)
9.

C
(dst,A) +

C
11.

C
(dst,A) +

C
(dst,A) < 10.

C
(dst,B) +

C
(dst,B)
(dst,A) < 10.

C
(dst,B) +

C
(dst,B)
20.

C
(dst,A) +

C
(dst,A) > 10.

C
(dst,B) +

C
(dst,B)

C
(dst,A)=1,

C
(dst,A)=1,

C
(dst,B) =2,

C
(dst,B) =0
14

Optimization Phase
 One system of inequalities per (node, prefix) pair
 (num egresses – 1) x (num failures +1)
 Practical requirements for setting parameters
 Finite-precision parameter values
Integer programming
 Limiting the number of unique values
Objective function: min

(

+

)
 Robustness to unplanned events
 
1
 Running time
 37 seconds (Abilene network) and 12 minutes (ISP network)
• 196MHz MIPS R10000 processor on an SGI Challenge
15

Evaluation of TIE on
Operational Networks
 Topology and egress sets
 Abilene network (U.S. research network)
 Set link weight with geographic distance
 Configuration of TIE
 Considering single-link failures
 Threshold of delay ratio: 2
  
[1,4] and 93% of
 i
(dst,e)=1
  
{0,1,3251} and 90% of
 i
(dst,e)=0
 Evaluation against hot-potato and fixed ranking
 Simulate single-node failures
 Measure routing sensitivity and delay
16

Sensitivity to Node Failures
15% of egress changes can be avoided without harming delay fraction prefixes affected 17

Delay under Node Failures
It is better than fixed ranking for 60% of tuples
Under threshold, TIE has longer delay than hot-potato ratio of delay after failure to design time delay 18

Conclusion
 TIE mechanism for selecting egresses
 Decouples interdomain and intradomain routing
 Designed for being easy to optimize
 Small change to router implementation
 Operators can optimize TIE for other policies
 Traffic engineering
 Robust traffic engineering
 Planning for maintenance
19

More details http://rp.lip6.fr/~teixeira
20

Multiple Interdomain Egresses
Web
Server
NY
SF
LA
Sprint
User
Multiple egresses for a destination are common!
ISPs usually peer in multiple locations and customers buy multiple connections to one or more
ISPs for reliability and performance
21

Why Hot-Potato Routing?
 Independent and consistent egress decision
 Forward packet to neighbors that have selected same (closest) egress
 Minimize resource consumption
 Limits consumption of bandwidth by sending traffic to next domain as early as possible dst
9
4
F
3
11
D
8
3
E
8
10
4
G
5
6
C
22

Summary of
BGP Decision Process
 BGP decision process
 Ignore if exit point unreachable
 Highest local preference
 Lowest AS path length
 Lowest origin type
 Lowest MED (with same next hop AS)
 Lowest IGP cost to next hop
 Lowest router ID of BGP speaker
23

Other Policies
 Traffic engineering
 Configure TIE parameters to select egresses to obtain optimal link utilization
 Solution: Path-based multi-commodity flow
 Robust traffic engineering
 Combine minimizing sensitivity with traffic engineering problem
 Preparing for maintenance
24

Traffic Engineering with TIE
 Problem definition
 Balance utilization of internal links
 Configure TIE parameters to select egresses to obtain optimal link utilization
 No need to set intradomain link weights
 Solution
 Path-based multicommodity flow
 No need to tweak routing protocols
 Avoid routing convergence
25

Example Policy:
Minimizing Sensitivity
 Problem definition
 Minimize sensitivity to equipment failures
 No delay more than twice design time delay
 Would be a simple change to routers
 If distance is more than twice original distance
• Change to closest egress
 Else
• Keep using old egress point
 But cannot change routers for all possible goals
We can do this with TIE just by setting
 and

26