mar 1, 2004 multi-path routing cse 525 course presentation dhanashri kelkar department of computer...
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Mar 1, 2004
Multi-path Routing
CSE 525 Course Presentation
Dhanashri Kelkar
Department of Computer Science and EngineeringOGI School of Science and Engineering
Mar 1, 2004 Dhanashri Kelkar – OGI School of Science and Engineering
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Multi-path Routing
• A. Akella, B. Maggs, S. Seshan, A. Shaikh, R. Sitaraman, "A Measurement-Based Analysis of Multihoming", ACM SIGCOMM 2003.
• D. Andersen, A. Snoeren, H. Balakrishnan, "Best-Path v. Multi-Path Overlay Routing", IMC 2003.
Mar 1, 2004 Dhanashri Kelkar – OGI School of Science and Engineering
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Multihoming Advantages – The Gist
• A study of multihoming performance and reliability ‣ Data collected from Akamai content
distribution network‣ High-volume content providers‣ Enterprises that mainly receive data
• Analysis:‣ Improve performance and reliability‣ Choosing right set of providers important
Mar 1, 2004 Dhanashri Kelkar – OGI School of Science and Engineering
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Multihoming
• Technique to achieve resilience to service interruptions
• Customer network having more than one external link, either to single ISP or to different providers
• Mainly used for reliability
Mar 1, 2004 Dhanashri Kelkar – OGI School of Science and Engineering
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K-Multihoming
• Customer network multihomed to K (K≥2) service providers
• Expect incremental performance
Mar 1, 2004 Dhanashri Kelkar – OGI School of Science and Engineering
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Multihoming – Two Models
• Enterprise perspective:‣ Route data being downloaded through
appropriate ISP
• Web server perspective:‣ Route data being provided through
appropriate ISP
• Does smart routing improve performance?
• Does choice of ISPs matter?
Mar 1, 2004 Dhanashri Kelkar – OGI School of Science and Engineering
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Data Collection – Enterprise Perspective2-Multihoming
• Data set A1‣ 27 monitoring nodes‣ Two nodes per city
connected to different ISP
‣ Every 6 min. nodes download objects from Akamai customers
‣ Log turnaround time for
request
AkamaiCustomer
ISP1 ISP2
Monitor1
Monitor2
Enterprise Stand-in tPM ix ,
Mar 1, 2004 Dhanashri Kelkar – OGI School of Science and Engineering
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Data Collection – Enterprise PerspectiveK-Multihoming (K>2)
• Data set H1‣ Multiple Akamai
servers per city‣ Each server connected
to different ISP‣ Servers download from
customers periodically‣ Log avg turnaround
time each hour
AkamaiCustomer
ISP 1 ISP K
Server1
ServerK
Enterprise Stand-in tHT
kOP
Mar 1, 2004 Dhanashri Kelkar – OGI School of Science and Engineering
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Performance – 2-multihoming
• Use best provider for each download instead of single provider for all downloads
• Performance metric:
• Measures how much each ISP loses compared to multihoming solution (≥1)
tPNumvalid
tPMtPMN
i
ti ibestix
x ,
,/,,
Mar 1, 2004 Dhanashri Kelkar – OGI School of Science and Engineering
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Performance – K-Multihoming
• Performance metric:
• particular K-multihoming solution• Best multihoming obtained if we choose best of
all ISPs
tNumvalid
tHTtHTN t bestOP
OPk
k
/
kOP
Mar 1, 2004 Dhanashri Kelkar – OGI School of Science and Engineering
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Enterprise 2-Multihoming: Results
• 2-multihoming shows performance benefits but to varying degrees
Mar 1, 2004 Dhanashri Kelkar – OGI School of Science and Engineering
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Enterprise K-Multihoming Performance
• Each line represents different city
• No significant improvement after 4 or 5
• Knowing best ISP in advance is important
Mar 1, 2004 Dhanashri Kelkar – OGI School of Science and Engineering
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Data Collection – Web Server Perspective
ISP 1 ISP K
Server1
ServerK
Web-server Stand-in
Server2
ISP 2
Internet
Mar 1, 2004 Dhanashri Kelkar – OGI School of Science and Engineering
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Web Server Perspective – Cont’d
• Data set A2:‣ In 5 metro areas, pick servers attached to
distinct upstream ISPs‣ Every 6 min. each server downloads 50 KB
object from other Akamai servers‣ Turnaround time for request
Mar 1, 2004 Dhanashri Kelkar – OGI School of Science and Engineering
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Web Server K-Multihoming
• Use Akamai servers to emulate multihomed data centers and their active clients
• Metric for comparison: same as with enterprises
• Not much benefit beyond K=4
Mar 1, 2004 Dhanashri Kelkar – OGI School of Science and Engineering
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Reliability
• Data set containing traceroute measurements from nodes of keynote systems to Akamai servers‣ 50 geographically diverse keynote nodes,
2 per city‣ 20 Akamai servers per city (top 20 ISP)
• Information about IP-level connectivity
• Robustness to IP-level failures
Mar 1, 2004 Dhanashri Kelkar – OGI School of Science and Engineering
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Reliability Metrics
• Fraction of total path diversity captured by solution
‣ Higher value shows better performance
• Degree of overlap in paths
‣ Lower value shows better performance
i
i
kik E
EOPR
20,
,1 50/1)(
i
ki
kikik E
EPOPR
,
,,2 50/1)(
Mar 1, 2004 Dhanashri Kelkar – OGI School of Science and Engineering
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Reliability Analysis
• For both metrics, significant difference in optimal, average, and worse solution‣ Difference about 80%
• Choosing ISPs very crucial
Mar 1, 2004 Dhanashri Kelkar – OGI School of Science and Engineering
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Conclusion
• Multihoming helps, at least 20% improvement on average ‣ But not much beyond 4 providers
• Careful choice necessary‣ Cannot just pick top individual performers‣ Poor choice can affect performance
significantly
Mar 1, 2004 Dhanashri Kelkar – OGI School of Science and Engineering
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Best-path vs. Multi-path Routing
• Analysis of performance of reactive and mesh routing
• Reactive routing: measure path quality using probes and send on best path
• Mesh routing: send redundant duplicates
Mar 1, 2004 Dhanashri Kelkar – OGI School of Science and Engineering
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Design
• Probe-based reactive overlay routing‣ Periodic probes for availability, latency, loss
rate‣ Best path performance
• Redundant multi-path routing‣ Sends redundant data to multiple paths‣ Path independence
Mar 1, 2004 Dhanashri Kelkar – OGI School of Science and Engineering
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Routing Methods
‣ Direct Single packet, direct path‣ Direct direct 2 packets, direct, no spacing‣ DD 10ms 2 packets, direct, 10ms spacing‣ DD 20ms 2 packets, direct, 20ms spacing‣ Lat Reactive routing, min latency‣ Loss Reactive routing, min loss‣ Direct Rand 2 pkts, Redundant routing‣ Lat Loss 2 pkts, Redundant multi-path
Mar 1, 2004 Dhanashri Kelkar – OGI School of Science and Engineering
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Duplication Reduces Loss Rate
• Type Loss %• direct 0.42• direct direct 0.30• dd 10ms 0.27• dd 20ms 0.27• Lat 0.43• Loss 0.33• Direct Rand 0.26• Lat Loss 0.23