optimizing cost and performance for content multihoming
DESCRIPTION
Optimizing Cost and Performance for Content Multihoming. SIGCOMM’12 -Piggy, 2013.03.18. Outline. What is Content Multihoming Goal Control Framework Global Optimization Local Adaptation Evalution. Content Multihoming. CDN Diversity. CDN DIVERSITY. CDN DIVERSITY. Goal. - PowerPoint PPT PresentationTRANSCRIPT
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OPTIMIZING COST AND PERFORMANCE FOR CONTENT MULTIHOMING
SIGCOMM’12-PIGGY, 2013.03.18
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OUTLINE• What is Content Multihoming• Goal• Control Framework• Global Optimization• Local Adaptation• Evalution
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CONTENT MULTIHOMING
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CDN DIVERSITY
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CDN DIVERSITY
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CDN DIVERSITY
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GOAL• Algorithms and protocols that optimize
• Content publisher cost• Content viewer performance
• A content object can be delivered from multiple CDNs, which CDN(s) should a content viewer use?
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NOTATION
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CONTROL FRAMEWORK
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PASSIVE VS. ACTIVE CLIENT• Passive client
• Use one CDN edge server at a time• Active client
• Adaptation algorithm• Multiple CDN servers for a single content object
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PROBLEM STATEMENT (Q)• QoE guarantee
• CDN k is providing the required features to deliver content object i
• exceeds the performance target• Cost optimization
• Balance load to multiple CDNs to minimize total cost
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ACTIVE CLIENT• Virtual CDN
• Primary CDN• Backup CDN• k’ = (k, j)
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COMPUTING OPTIMIZATION(CMO)• Problem Q has an optimal solution which
assigns a location object into a single CDN
• K|A|N
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BASIC IDEA
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EXTENSION • CDN subscription levels
• Fix fee to different usage levels• Different levels as an individual CDN
• Per-request cost• Extend vector dimension to R+1
• Multiple streaming rates• Independent content objects
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LOCAL ADAPTATION• QoE protection• Prioritized guidance• Low session overhead
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LOCAL ADAPTATION• Similar to TCP AIMD• Total workload control• Priority assignment
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EVALUATION SETTING
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COST SAVING
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COST SAVING
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ACTIVE CLIENT SETTING• Clients
• 500+ Planetlab nodes with Firefox 8.0 + Adobe Flash 10.1
• Two CDNs• Amazon CloudFront• CDN3
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ACTIVE CLIENT TEST CASE
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STRESS TESTS (STEP-DOWN)
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STRESS TESTS (RAMP-DOWN)
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STRESS TESTS (OSCILLATION)
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ACTIVE CLIENT QOE GAIN
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CONCLUSION• We develop and implement a two-level
approach to optimize cost and performance for content multihoming: • CMO: an efficient algorithm to minimize publisher cost
and satisfy statistical performance constraints• Active client: an online QoE protection algorithm to
follow CMO guidance and locally handle network congestions or server overloading
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Q&A