Network Sensitivity to Hot-Potato Disruptions Renata Teixeira (UC San Diego) teixeira with Aman...
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Transcript of Network Sensitivity to Hot-Potato Disruptions Renata Teixeira (UC San Diego) teixeira with Aman...
Network Sensitivity to Hot-Potato Disruptions
Renata Teixeira
(UC San Diego)http://www-cse.ucsd.edu/~teixeira
with
Aman Shaikh (AT&T), Tim Griffin(Intel), and Geoff Voelker (UCSD)
SIGCOMM’04 – Portland, OR
2SIGCOMM’04
Internet Routing Architecture
UCSDSprint
AT&T Verio
AOL
interdomain routing (BGP)
intradomain routing (OSPF,IS-IS) User
Web Server
End-to-end performance depends on all ASes
along the path
Changes in one AS may impact traffic
and routing in other ASes
3SIGCOMM’04
Hot-Potato Routing
San Francisco
Dallas
New York
Hot-potato routing = route to closest egress point when there is more than one route to destination
ISP network
9 10
dstmultiple connections to the same peer
-All traffic from customer to peers-All traffic to customer prefixes with multiple connections
4SIGCOMM’04
Hot-Potato Disruption
San Francisco
Dallas
New York
ISP network
dst
9 10- failure- planned maintenance- traffic engineering
11
Routes to thousands of destinations switch
exit point!!!
11
5SIGCOMM’04
Consequences of Hot-Potato Disruptions
Transient forwarding instability Up to three minutes convergence delay Normal internal changes take a couple of seconds
Traffic shift Responsible for largest traffic matrix variations
Interdomain routing changes Around 2 – 5% of a router’s external BGP updates
6SIGCOMM’04
What to do about it?
Engineer network to minimize disruptions Network operator: operational practices to avoid
changes Network designer: designs that minimize sensitivity
Need a vocabulary and metrics to evaluate impact of internal changes Compare possible network designs Identify critical events Take special care during maintenance or traffic
engineering
7SIGCOMM’04
Modeling Hot-Potato Routing
Model of egress selection in backbone networks Internal topology and link weights Set of egress routers for each destination prefix
Apply topology changes Link or router failures Link weight changes
Evaluate impact of topology changes For a router what fraction of prefixes shifts Most critical link failure …
8SIGCOMM’04
Modeling Egress Selection
AB
C
DG
EF
4
5
11
39
34
108
68
dst
Egress set for a destination prefix (dst) = set of border nodes that learn routes to dst ({A,B})
AB
Region of egress node A = nodes that are closer to A than B
Region of A Region of B
9SIGCOMM’04
Modeling Topology Changes
C
DG
EF
4
5
11
39
34
108
68
Region of A Region of B
AB
Topology change = edge or node deletion, link weight change
dst
C
DG
EF
4
5
11
39
34
108
68
Region of A Region of B
AB
C shifts from region of A to B
dst
10SIGCOMM’04
Generalizing to All Prefixes
Fraction of prefixes at a router that change egresses after a single topology change Routing-shift function (HRM)
AB
C
DG
EF4
5
11
39
34
106
68
A B
X (10,000 prefixes)
Z (4,000 prefixes)Y (1,000 prefixes)
Routing-shift at C when CF is deleted= 10,000/15,000(i.e. 2/3)
11SIGCOMM’04
All Prefixes, Routers, and Topology Changesro
uter
s
topology changes
C
failure of CF
fraction of prefixes at C that changes egress after the failure of link CF: 2/3
routing-shift function
12SIGCOMM’04
Node Routing Sensitivity Metrics (RM)
rout
ers
topology changes
C
Node routing sensitivity Expected fraction of route shifts
experienced by a node
Worst case Maximum route shift experienced
by a node
13SIGCOMM’04
Routing Impact of a Graph Transformation (RM)
Impact of graph transformations Average fraction of route shifts
across all nodes
Worst case Maximum route shift caused by each
graph transformation
rout
ers
topology changesfailure of CF
14SIGCOMM’04
Case Study: A Large ISP Backbone Network
Obtaining input for the model Topology – intradomain routing messages Egress sets – collection of BGP tables Set of graph transformations
• Single link failures• Single router failures
Probability distribution for graph transformations• Uniform
15SIGCOMM’04
Order failuresaccording to average impact
Which failures are most disruptive?ro
uter
s
single router failures
fraction of failures
Ro
utin
g Im
pa
ct o
f Fai
lure
s router failureslink failures
Most failures cause no hot-potato disruptionsOperators can focus on
most disruptive failures
16SIGCOMM’04
Which routers are most sensitive?
rout
ers
single router failures
Order routersaccording to average sensitivity
router failureslink failures
fraction of routers
No
de
Ro
utin
g S
en
sitiv
ity
Very few hot-potato changes on average,but there are many failures that causeno shift
High variance among routers
17SIGCOMM’04
What is the largest routing shift for each router?
rout
ers
single router failuresor
single link failures
Order routersaccording to worst case sensitivity
Wo
rst C
ase
N
od
e R
ou
ting
Se
nsi
tivity
fraction of routers
Very disruptive failuresfor some routers
18SIGCOMM’04
Conclusion
Contributions Model of hot-potato disruptions Basis for a sensitivity analysis tool
Robustness should be a first-order metric As important as traditional performance metrics Network should have small reactions to small changes
Two approaches Engineer the system: our model Redesign routing interaction: on-going work