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Changing Traffic Patterns
High bandwidth cost of inter-user traffic
High delay of local communications
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Diverse Traffic RequirementsInter-user communications Real-time traffic Autonomous device traffic
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Challenges to Sustained Net. Scalability
• Are existing network architectures well-suited to meet evolving traffic requirements?
• Throwing capacity at the problem is not cost efficient or effective– Cannot reduce end-to-end
delay– Existing capacity not used
effectively
?
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Dissertation Research Overview
• Network engineering process
• Clean slate ideas
• Dirty slate solutions
Network Measurement
Topology Design
Resource Allocation
MIST [Broadnets ’07]
AirLab [CCR ’11]
Cloud Routing [Comcom ‘09]SISR [SECON ’09]Distr. OSNs [CoNEXT ‘10]
AggrBP [in preparation]
ParaNets [HotMobile ‘07]
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Online Social Networks (OSNs)
• OSNs are fun, socially significant, and here to stay
• OSN traffic is the next evolution in Internet usage
• How is OSN traffic different?
• Can we deliver OSN traffic more effectively?Mike P. Wittie, Veljko Pejovic, Lara Deek, Kevin C. Almeroth, Ben Y. Zhao "Exploiting Locality of Interest in Online Social Networks," in ACM CoNEXT, 2010.
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Project Overview
• Infrastructure discovery– DNS redirection
• Interaction analysis– Crawls of public profiles
• Protocol discovery– Packet traces
• Path measurement– PlanetLab + ping
U.S.-centralized infrastructure
Local communication patterns
Inefficient routing
High latency and loss paths
High network costs
Unresponsive service
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Facebook’s Infrastructure
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Social Graph and Interactions
• Locality of interest:– Percentage of user
communications within a region
• Web crawls of public user profiles
• Social graph
• Interaction history– Local-to-Local– Remote-to-Local– Local-to-Remote
Russia0.26mil
Egypt 3.86mil
Sweden 8.59mil
NYC 2.95mil
LA 2.25mil
Local Remote
Users and Social Links
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Locality of Interest: Posts
Many posts between local users
Local to Local Local to Remote Remote to Local
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Delivery Ratio of Wall Posts
Needlessly routed through the U.S.
Local to Local Local to Remote Remote to Local
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Internet Path Measurement
• High latency and loss but separable by a regional proxy
Region
Latency (ms) Loss (%) Capacity (Mbps)
Direct
To Region
LastMile
Direct
To Region
LastMile
Direct
To Region
LastMile
Russia 148 115 31 6.1 0 1.8 29.6 367 29.6
Egypt 164 176 67 5.8 0 5.8 0.92 736 0.92
Sweden 104 95 14 0.32 0 2.9 9.47 188 9.47
NYC 74 43 33 0.75 0 0.6 9.51 99 9.51
LA 27 9.1 18 0.5 0 0.4 2.02 228 2.02Facebook Akamai UserFacebook Akamai User Regional Server
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Discussion
Challenges
• Infrastructure centralization results in inefficient routes
• Many round trips and poor paths inflate request delay
Solutions
• Locality of interest allows OSN state partitioning:
REGIONAL OSN CACHES
• Split the high latency and loss path segments:
REGIONAL TCP PROXIES
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Current Facebook Architecture
1. New content
2. Display markup
3. Static contentPost
Facebook Akamai User
1. New content
2. Display markup
3. Static contentPost
1, 2, 3
Facebook Akamai User Regional Server
With TCP Proxies
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Current Facebook Architecture
1. Any new content?
2. Concatenated display markup
3. Static contentPoll
Facebook Akamai User
With Regional Caches
3. Static contentPoll
Facebook Akamai User Regional Server
1, 2, 3
1. Any new content?
2. Concatenated display markup
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Replay Posts
Add Push
Process Poll
Simulate TCP
Simulating Facebook Traffic
Interaction History
Transaction Traces
Social Graph
Inputs Simulation Core Metrics
Path Measurement
Network Load
Transaction Delay
Cache Usage
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Delay of Post Transactions
TCP proxies significantlyreduce transaction delay
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Network Load
Regional caches significantlyreduce load on Internet paths
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Discussion
• Lack of sophisticated topology design has significant impact on Facebook performance:– Inefficient centralized processing of regional communications– Unresponsive service due to high latency and loss on Internet paths and
many round trips
• Regional TCP proxies and caches can improve OSN responsiveness
• Distributed infrastructure is a more effective scaling strategy– Infrastructure design that can conform to communication patterns– Multi-cloud service deployments and optimization
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Summary and Conclusions
• Sustained network scalability challenged by changing traffic patterns
• More sophisticated network design and resource management methods can address fundamental limitations of existing deployments
• Networks scalability an important problem:– Allow the Internet to continue to play important role in our lives– Support new types of applications– Maintain democratic access to digital communications
• Clean slate ideas and dirty slate solutions for a new set of problems
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Vision for Future Work
• Clean slate ideas and dirty slate solutions a fruitful and valid research approach
• Networks scalability an important problem:– Allow the Internet to play important role in our lives– Support new types of applications– Maintain democratic access to digital communications
• Apply my research philosophy to a new set of problems:– Large distributed applications in a diverse cloud services ecosystem– Autonomous device coordination and services