Routing Measurements: Three Case Studies

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Routing MeasurementsThree Case Studies

• Jennifer Rexford

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Motivations for Measuring the Routing System

• Characterizing the Internet
• Internet path properties
• Demands on Internet routers
• Routing convergence
• Improving Internet health
• Protocol design problems
• Protocol implementation problems
• Configuration errors or attacks
• Operating a network
• Detecting and diagnosing routing problems
• Traffic shifts, routing attacks, flaky equipment,
  

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Techniques for Measuring Internet Routing

• Active probing
• Inject probes along path through the data plane
• E.g., using traceroute
• Passive route monitoring
• Capture control-plane messages between routers
• E.g., using tcpdump or a software router
• E.g., dumping the routing table on a router
• Injecting network events
• Cause failure/recovery at planned time and place
• E.g., BGP route beacon, or planned maintenance

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Challenges in Measuring Routing

• Data vs. control plane
• Understand relationship between routing protocol
  messages and the impact on data traffic
• Cause vs. effect
• Identify the root cause for a change in the
  forwarding path or control-plane messages
• Visibility and representativeness
• Collect routing data from many vantage points
• Across many Autonomous Systems, or within
• Large volume of data
• Many end-to-end paths
• Many prefixes and update measurements

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Measurement Tools Traceroute

• Traceroute tool exploits TTL-limited probes
• Observation of the forwarding path
• Useful, but introduces many challenges
• Path changes
• Non-participating nodes
• Inaccurate, two-way measurements
• Hard to map interfaces to routers and ASes

destination
source
Send packets with TTL1, 2, 3, and record
source of time exceeded message
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Measurement Intradomain Route Monitoring

• OSPF is a flooding protocol
• Every link-state advertisements sent on every
  link
• Very helpful for simplifying the monitor
• Can participate in the protocol
• Shared media (e.g., Ethernet)
• Join multicast group and listen to LSAs
• Point-to-point links
• Establish an adjacency with a router
• or passively monitor packets on a link
• Tap a link and capture the OSPF packets

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Measurement Interdomain Route Monitoring
Establish a passive BGP session from a
workstation running BGP software
Talk to operational routers using SNMP or telnet
at command line
BGP session over TCP
() BGP table dumps do not burden
operational routers (-) Receives only best
routes from BGP neighbor () Update
dynamics captured () not restricted to
interfaces provided by vendors
(-) BGP table dumps are expensive () Table
dumps show all alternate routes (-) Update
dynamics lost (-) restricted to interfaces
provided by vendors
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Collect BGP Data From Many Routers
Seattle
Cambridge
Chicago
Detroit
New York
Kansas City
Philadelphia
Denver
San Francisco
St. Louis
Washington, D.C.
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Los Angeles
Dallas
Atlanta
San Diego
Phoenix
Austin
Orlando
Houston
Route Monitor
BGP is not a flooding protocol
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Two Kinds of BGP Monitoring Data

• Wide-area, from many ASes
• RouteViews or RIPE-NCC data
• Pro available from many vantage points
• Con often just one or two views per AS
• Single AS, from many routers
• Abilene and GEANT public repositories
• Proprietary data at individual ISPs
• Pro comprehensive view of a single AS
• Con limited public examples, mostly research
  nets

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Measurement Injecting Events

• Equipment failure/recovery
• Unplug/reconnect the equipment ?
• Packet filters that block all packets
• Knowing when planned event will take place
• Shutting down a routing-protocol adjacency
• Injecting route announcements
• Acquire some blocks of IP addresses
• Acquire a routing-protocol adjacency to a router
• Announce/withdraw routes on a schedule
• Beacons http//psg.com/zmao/BGPBeacon.html

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Two Papers for Today

• Both early measurement studies
• Initially appeared at SIGCOMM96 and 97
• Both won the best student paper award ?
• Early glimpses into the health of Internet
  routing
• Early wave of papers on Internet measurement
• Differences in emphasis
• Paxson96 end-to-end active probing to measure
  the characteristics of the data plane
• Labovitz97 passive monitoring of BGP update
  messages from several ISPs to characterize
  (in)stability of the interdomain routing system

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Paxson Study Forwarding Loops

• Forwarding loop
• Packet returns to same router multiple times
• May cause traceroute to show a loop
• If loop lasted long enough
• So many packets traverse the loopy path
• Traceroute may reveal false loops
• Path change that leads to a longer path
• Causing later probe packets to hit same nodes
• Heuristic solution
• Require traceroute to return same path 3 times

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Paxson Study Causes of Loops

• Transient vs. persistent
• Transient routing-protocol convergence
• Persistent likely configuration problem
• Challenges
• Appropriate time boundary between the two?
• What about flaky equipment going up and down?
• Determining the cause of persistent loops?
• Anecdote on recent study of persistent loops
• Provider has static route for customer prefix
• Customer has default route to the provider

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Paxson Study Path Fluttering

• Rapid changes between paths
• Multiple paths between a pair of hosts
• Load balancing policies inside the network
• Packet-based load balancing
• Round-robin or random
• Multiple paths for packets in a single flow
• Flow-based load balancing
• Hash of some fields in the packet header
• E.g., IP addresses, port numbers, etc.
• To keep packets in a flow on one path

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Paxson Study Routing Stability

• Route prevalence
• Likelihood of observing a particular route
• Relatively easy to measure with sound sampling
• Poisson arrivals see time averages (PASTA)
• Most host pairs have a dominant route
• Route persistence
• How long a route endures before a change
• Much harder to measure through active probes
• Look for cases of multiple observations
• Typical host pair has path persistence of a week

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Paxson Study Route Asymmetry

• Hot-potato routing

• Other causes
• Asymmetric link weights in intradomain routing
• Cold-potato routing, where AS requests traffic
  enter at particular place
• Consequences
• Lots of asymmetry
• One-way delay is not necessarily half of the
  round-trip time

Customer B
Provider B
multiple peering points
Early-exit routing
Provider A
Customer A
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Labovitz Study Interdomain Routing

• AS-level topology
• Destinations are IP prefixes (e.g., 12.0.0.0/8)
• Nodes are Autonomous Systems (ASes)
• Links are connections business relationships

4
3
5
2
6
7
1
Client
Web server
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Labovitz Study BGP Background

• Extension of distance-vector routing
• Support flexible routing policies
• Avoid count-to-infinity problem
• Key idea advertise the entire path
• Distance vector send distance metric per dest d
• Path vector send the entire path for each dest d

d path (2,1)
d path (1)
3
1
data traffic
data traffic
d
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Labovitz Study BGP Background

• BGP is an incremental protocol
• In theory, no update messages in steady state
• Two kinds of update messages
• Announcement advertising a new route
• Withdrawal withdrawing an old route
• Study saw an alarming number of updates
• At the time, Internet had around 45,000 prefixes
• Routers were exchanging 3-6 million updates/day
• Sometimes as high as 30 million in a day
• Placing a very high load on the routers

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Labovitz Study Classifying Update Messages

• Analyze update messages
• For each (prefix, peer) tuple
• Classify the kinds of routing changes
• Forwarding instability
• WADiff explicit withdraw, replaced by alternate
• AADiff implict withdraw, replaced by alternate
• Pathological
• WADup explicit withdraw, and then reanounced
• AADup duplicate announcement
• WWDup duplicate withdrawal

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Labovitz Study Duplicate Withdrawals

• Time-space trade-off in router implementation
• Common system building technique
• Trade one resource for another
• Can have surprising side effects
• The gory details
• Ideally, you should not send a withdrawal if you
  never sent a neighbor a corresponding
  announcement
• Requires remembering what update message you sent
  to each neighbor
• Easier to just send everyone a withdrawal when
  your route goes away

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Labovitz Study Practical Impact

• Stateless BGP is compliant with the standard
• But, it forces other routers to handle more load
• So that you dont have to maintain state
• Arguably very unfair, and bad for global Internet
• One router vendor was largely at fault
• Router vendor modified its implementation
• ISPs then deployed the updated software

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Labovitz Study Still Hard to Diagnose Problems

• Despite having very detailed view into BGP
• Some pathologies were very hard to diagnose
• Possible causes
• Flaky equipment
• Synchronization of BGP timers
• Interaction between BGP and intradomain routing
• Policy oscillation
• These topics were studied in follow-up studies
• Example study of BGP data within a large ISP
• http//www.cs.princeton.edu/jrex/papers/nsdi05-ji
  an.pdf

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ISP Study Detecting Important Routing Changes

• Large volume of BGP updates messages
• Around 2 million/day, and very bursty
• Too much for an operator to manage
• Identify important anomalies
• Lost reachability
• Persistent flapping
• Large traffic shifts
• Not the same as root-cause analysis
• Identify changes and their effects
• Focus on mitigation, rather than diagnosis
• Diagnose causes if they occur in/near the AS

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Challenge 1 Excess Update Messages

• A single routing change
• Leads to multiple update messages
• Affects routing decision at multiple routers

Persistent Flapping Prefixes
Group updates for a prefix with inter-arrival lt
70 seconds, and flag prefixes with changes
lasting gt 10 minutes.
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Determine Event Timeout
Cumulative distribution of BGP update
inter-arrival time
BGP beacon
(70, 98)
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Event Duration Persistent Flapping
Complementary cumulative distribution of event
duration
(600, 0.1)
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Detecting Persistent Flapping

• Significant persistent flapping
• 15.2 of all BGP update messages
• though a small number of destination prefixes
• Surprising, especially since flap dampening is
  used
• Types of persistent flapping
• Conservative flap-damping parameters (78.6)
• Policy oscillations, e.g., MED oscillation
  (18.3)
• Unstable interface or BGP session (3.0)

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Example Unstable eBGP Session
Peer
ATT
p
Customer
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Challenge 2 Identify Important Events

• Major concerns of network operators
• Changes in reachability
• Heavy load of routing messages on the routers
• Flow of the traffic through the network

Classify events by type of impact it has on the
network
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Event Category No Disruption
p
AS2
AS1
No Traffic Shift
ATT
No Disruption each of the border routers has
no traffic shift
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Event Category Internal Disruption
p
AS2
AS1
Internal Disruption all of the traffic shifts
are internal traffic shift
ATT
Internal Traffic Shift
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Event Type Single External Disruption
p
AS2
AS1
external Traffic Shift
ATT
Single External Disruption traffic at one exit
point shifts to other exit points
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Statistics on Event Classification
Events Updates
No Disruption 50.3 48.6
Internal Disruption 15.6 3.4
Single External Disruption 20.7 7.9
Multiple External Disruption 7.4 18.2
Loss/Gain of Reachability 6.0 21.9
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Challenge 3 Multiple Destinations

• A single routing change
• Affects multiple destination prefixes

Group events of same type that occur close in time
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Main Causes of Large Clusters BGP Resets

• External BGP session resets
• Failure/recovery of external BGP session
• E.g., session to another large tier-1 ISP
• Caused single external disruption events
• Validated by looking at syslog reports on routers

p
AS2
AS1
ATT
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Main Causes of Large Clusters Hot Potatoes

• Hot-potato routing changes
• Failure/recovery of an intradomain link
• E.g., leads to changes in IGP path costs
• Caused internal disruption events
• Validated by looking at OSPF measurements

P
Hot-potato routing route to closest egress
point
10
11
9
ISP
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Challenge 4 Popularity of Destinations

• Impact of event on traffic
• Depends on the popularity of the destinations

Netflow Data
Weight the group of destinations by the traffic
volume
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ISP Study Traffic Impact Prediction

• Traffic weight
• Per-prefix measurements from Netflow
• 10 prefixes accounts for 90 of traffic
• Traffic weight of a cluster
• The sum of traffic weight of the prefixes
• Flag clusters with heavy traffic
• A few large clusters have large traffic weight
• Mostly session resets and hot-potato changes

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ISP Study Summary
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Three Studies, Three Approaches

• End-to-end active probes
• Measure and characterize the forwarding path
• Identify the effects on data traffic
• Wide-area passive route monitoring
• Measure and classify BGP routing churn
• Identify pathologies and improve Internet health
• Intra-AS passive route monitoring
• Detailed measurements of BGP within an AS
• Aggregate data into small set of major events