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End-to-End Issues. Route Diversity. Load balancing Per packet splitting Per flow splitting Spill over Route change Failure policy Route flapping. Diversity Effects. Packet reorder TCP performance Larger playback buffer Jitter However, jitter can occur due cross traffic. - PowerPoint PPT Presentation
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End-to-End Issues
Route Diversity
Load balancingo Per packet splittingo Per flow splitting
Spill over Route change
o Failureo policy
Route flapping
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Diversity Effects
Packet reordero TCP performanceo Larger playback buffer
Jitter
However, jitter can occur due cross traffic.What contribute more to jitter?
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What contribute more to jitter?
Understand the origins of e2e delay variationso Result from existence of multiple routes• designed load balancing or transient failures
o Result of variations within each route• intra-route issues (congestion)
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S D
S D
Related Work [Wang et al., Pucha et al.] studied the impact that
specific routing events have on the overall delayo Routing changes result in significant RTT delay increaseo However, variability is small
[Augustin et al.] examined the delay between different parallel routes in short time epocho Only 12% have a delay difference which is larger than 1ms
[Pathak et al.] studied the delay asymmetry o There is a strong correlation between one-way delay
changes and route changes
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Key Differences
We study the RTT delay along longer time periods
Examine the difference of the delay distribution between parallel routes
Focus on the origin of delay variabilityoWithin each route (e.g. congestion)o Due to multiple routes (e.g. load-balance)
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How do we measure?
• Use DIMES for conducting two experiments– 2006 and 2009– Over 100 agents measures to each other– Broad set of ASes and geo locations– Active traceroute (ICMP and UDP)– Each agent probes all target IPs every 1-2 hours– 4 days of probing– Collect the route IPs and e2e delay
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Vantage Point Statistics (1)
2006o 102 VPsoMillion tracerouteso 6861 e2e pairso VPs in North
America (70), Western Europe (14), Australia (10), Russia (6), Israel (2)
2009o 105 VPsoMillion tracerouteso 10950 e2e pairso VPs in Western
Europe (41), North America (38), Russia (14), Australia (4), South America (2), Israel (2), Asia (4)
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Vantage Point Statistics (2)
2006 o 18% tier-1o 78% tier-2o 3% small companieso 1% educational
2009o 14% tier-1o 58% tier-2
o 28% educational
Only 7 agents participated in both
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Identifying Routes and Pairs
Using community-based infrastructureo Routes can start and end in non-routable IPso Users can measure from different locations
Only the routable section of each path is consideredo The source (S) is the first routable IPo The destination (D) is the last routable IP
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S D TargetVP
Some Accounting
• The e2e pair Pi=(S,D) contains all the measured paths between S and D
• For a pair Pi , the set Eij contains the measured
paths that follow route j• For a pair Pi , the dominant route Ei
r is the route that was seen the most times– There can be several dominant routes with equal
prevalence– For brevity we assume there is one at index r
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Delay Stability (1)
Each route Eij has a set of RTT delays,
corresponding to each measured path Each delay is a sample, we consider the
segment length resulting from the 95% confidence interval surrounding the mean value – CI(Ei
j) High variance samples result in long CI
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Delay Stability (2)
RTT stability of two routes is the intersection (overlap) between their CI’s
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Key Concept Overlapping CI’s (left)- intra-route delay variance Non-overlapping (right) - inter-route delay variance
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Route Stability (1)
Prevalence is the overall appearance ratio of a route j of pair Pi
As a stability measure, we use the prevalence of the dominant route r
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Route Stability (2)
Use Edit Distance (ED) as a measure for the difference between two routeso Counting insert, delete and substitute operations
Normalize ED by the maximal route length of the two compared routeso Can compare between ED of routes with different
lengthso marks normalized ED for pair i between
routes j and r
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Route Stability (3)
The stability is the weighted average of ED of all non-dominant routes to the dominant route of nearest length:
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Things to Note
We measure RTT valueso Capture forward and reverse path delayo Route stability is measured on the forward path• However, 90% of our routes have very similar forward
and reverse paths• Indicating that stability of one-way is a good estimation
Using UDP and ICMP o Capture all possible routes, not flowso Upper bound for instability
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Results – Route Statistics
• Both have roughly the same route length and median delay• Shorter routes than Paxson’s (15-16hops)• Median delay is around 100msec
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Results – Route Stability
• Overall stable e2e routing (25% of pairs with single route)• Academy pairs have higher stability (55% single route)• USA pairs have slightly higher stability (35% single route)• RouteISM < 0.2 for over 90% of the pairs
Load balancersNot visible in academy pairs
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Results – Origin of Delay Instability
• 70% of the cases, changes in route delay is within routes (high overlap) and not due to multiple path routing
• In 15% of the cases (20% in the 2006 data sets) the change in delay is mainly due to route changes
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Results – Route and Delay Instability
• When the difference between routes is high, higher chances of different delay distribution
• Prevalence does not significantly indicate level of overlap!22
High percentage of zero overlap
Results – Additional Findings
Over 95% of the academic pairs have an overlap of over 0.7o Academic networks have little usage of load-
balancing and “spill-over” backup routes Only 5% of the USA pairs have overlap of 0
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Conclusions
Delay variations are mostly within the routeso 70% of the pairso 95% of the academic pairs
Internet e2e routes are mostly stable The academic Internet is significantly more
stable than commercial networks
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