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Consensus Routing:
The Internet as a Distributed System
2009. 2. 26
John P. John, Ethan Katz-Bassett, Arvind Krishnamurthy, and Thomas Anderson
Presented by John P. John
Modified by Moonyoung Chung
Contents
Introduction
Motivation and Goals
Consensus Routing
– Stable Mode
– Transient Mode
Evaluation
Conclusions
NSDI '08 2
Internet Routing
A goal of the Internet is global reachability
But, BGP fails to achieve this goal
– Physical paths exist, but not BGP paths
– 10-15% of BGP updates cause loops and blackholes
– 90% of all packet losses on the Internet due to loops
NSDI '08 3
BGP
Opaque policy routing
– Preferred routes visible to neighbors
– Underlying policies not visible and under local control
Mechanism:
– Autonomous Systems(ASes) send preferred path to
neighbors
– If AS receives new path, start using right away
– Forward path to neighbors, after some delay
– Path eventually propagates to all ASes
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Example
5: 4-5
5: 3-4-5
5: 1-5
1 2 5: 4-5
5: 2-4-5
3
4
Destination 5
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BGP link failure
5: 4-5
5: 3-4-5
5: 1-5
5: 4-5
1 2
5: 2-4-5
5:4-5 3
4
Link 4-5 fails
AS4 withdraws path
Destination 5 from upstream ASes
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BGP link failure
5: 4-5
5: 3-4-5
5: 1-5
5: 4-5
1 2
5: 2-4-5
3
4
2 and 3 pick their
ASRouting loop is formed!
Destination 5 next best paths
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BGP policy change
5: 4-5
5: 3-4-5
5: 6-4-5
5: 1-5 5: 4-5
5: 2-4-5
1 2 5: 6-4-5
5:4-5 3 6 5: 4-5
5: 2-4-5
4
AS4 wants all traffic destined for
AS5 to come through AS6
Destination 5
AS4 withdraws the path
from AS2 and AS3
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BGP policy change
5: 4-5
5: 3-4-5
5: 6-4-5
5: 1-5 5: 4-5
5: 2-4-5
1 2 5: 6-4-5
3 6 5: 4-5
5: 2-4-5
4
2 and 3 loop is formed!
AS Routing pick their
Destination
next best paths
5
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Lack of Consistency
The underlying cause of all these problems is
inconsistent global state
– Link failures
– Traffic engineering
– Scheduled Maintenance
– Link coming up
Protocol behavior complex, unpredictable
No indicator of when system converged to
consistent state
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Motivation and Goal
Goal:
– Networks that have high availability
Insight:
– Consistency is the key
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Consensus Routing
Lesson from distributed system design:
– De-couple safety and liveliness
Safety: Forwarding tables are always consistent
and policy compliant, consistent view of global
state
Liveness: Routing system adapts to failures quickly
and maintains high availability
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Safety: Stable Mode
Problem: Inconsistent state
Solution:
– Apply updates only after they have reached all depend
ent ASes
– Apply updates synchronously across ASes
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Stable Mode
Consistent view of global state
– Stable Forwarding Table (SFT)
at kth epoch
1. Update log
2. Distributed snapshot
3. Frontier computation
4. SFT computation
5. View change
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Update log
ASes compute and
6 5 forward routes as before,
but don’t apply to
forwarding table
4
3
1 2
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Distributed Snapshot
Some node(s) calls for the (k+1)th distributed snapshot
6 5 1. Run BGP, but don’t apply
the updates
Periodically, a distributed
snapshot is taken
4
3 Updates in transit, or
being processed are
marked incomplete
1 2
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Frontier Computation: Aggregation
Consolidators 6 5 1. Run BGP, but don’t apply
the updates
2. Distributed Snapshot
4
3 ASes send snapshot report to the
consolidators
1. the saved sequence of updates
2. the set of incomplete updates
1 2
* frontier: the most recent complete update at each AS
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Frontier Computation: Consensus
Consolidators 6 5 1. Run BGP, but don’t apply
the updates
2. Distributed Snapshot
3. Send info to consolidators
4
Consolidators run a consensus
3
algorithm to agree on the set
of incomplete updates
1 2
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Frontier Computation: Flood
Consolidators 6 5 1. Run BGP, but don’t apply
the updates
2. Distributed Snapshot
3. Send info to consolidators
4. Consensus
4
Consolidators flood the
3
incomplete set to all the ASes
1 2
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SFT Computation & View Change
6 5 1. Run BGP, but don’t apply
the updates
2. Distributed Snapshot
3. Send info to consolidators
4. Consensus
4 5. Flood
3
Apply completed updates
1 2 Versioning, Garbage collection
Details and proof of consistency in the paper
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Mechanism
Other details in the paper:
– Transition between epochs
– Slow/unresponsive ASes
– Failed ASes
– Reintegration of failed ASes
– Provable safety and liveness properties
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Transient Mode: Liveness
Problem: Upon link failure, need to wait till path
reaches everyone
Solution: Dynamically re-route around the failed
link
– use existing techniques
• Pre-computed backup paths
• Deflection
• Detour routing
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Routing Deflection
S
deflect packet to neighbor
1
3 traverse a different route
2
D
Destination
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Backtracking
S
backtracking
1
4
3
2
D
Destination
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Detour Routing
S
tunnel
B Tier 1
4
B is responsible for
forwarding packets
3
5
D
Destination
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Backup routes
Pre-computed failover paths
e.g. RBGP, scheme for pre-computing backup routes
to each destination
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BGP
Global
reachability
Link Failure
(or other BGP event)
Connectivity
BGP converges
to alternate path
Completely
Unreachable
Time
NSDI '08 27
Consensus Routing
Global
Global
reachability
reachability
Link Failure
Switch
(or other BGP event)to
transient routing
Connectivity
Snapshot
Connectivity
Completely
Completely
Unreachable
Unreachable
Time
Time
NSDI '08 28
Evaluation
In the talk, answer the following:
– How does consensus routing affect connectivity?
– What is the traffic overhead?
Methodology
– Extensive simulations on realistic Internet-scale topologies.
– an implemented XORP prototype.
– experiments on PlanetLab.
NSDI '08 29
Methodology
23,390 ASes, 46,095 links
9,100 multi-homed stub AS
Fail each access link of
each multi-homed stub
AS
3 4 5
See what fraction of ASes
are temporarily disconnected
until convergence
1 2
NSDI '08 30
Connectivity
Consensus routing maintains
complete connectivity in
over 99% of the cases
BGP maintains complete
connectivity in < 40%
of the failure cases
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Overhead
overhead
Entire update is not sent, only identifiers of the updates
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Conclusions
BGP’s transient problems are due to inconsistent
global state
Consensus routing enables consistent routing state
with opaque policies
– key technique: separation of safety and liveness
We can have an Internet that has high availability!
NSDI '08 33
