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Enabling the Transition to the Mobile Web with WebSieve
Michael Butkiewicz, Zhe Wu, Shunan Li, Pavithra Murali, Vagelis Hristidis,
Harsha V. Madhyastha (UC Riverside), Vyas Sekar (Stony Brook University)
Source: gomez.com
Why does load time matter?
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Source: gomez.com
Why does load time matter?
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“Google incorporates site speed into search rankings”
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High Load Times are Common
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High Load Times are Common
Median Sitew/o mobile version
19 sec
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High Load Times are Common
Median Mobile Site
13 sec
Median Sitew/o mobile version
19 sec
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Page Complexity Load Time
Well StudiedMobiSys 2010 Huang, et al.
IMC 2011 Butkiewicz, et al.
HotMobile 2011 Wang, et al.
httparchive.org
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Page Complexity Load Time
Well StudiedMobiSys 2010 Huang, et al.
IMC 2011 Butkiewicz, et al.
HotMobile 2011 Wang, et al.
httparchive.org
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Page Complexity Load Time
200850 objects
Well StudiedMobiSys 2010 Huang, et al.
IMC 2011 Butkiewicz, et al.
HotMobile 2011 Wang, et al.
httparchive.org
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Page Complexity Load Time
Well StudiedMobiSys 2010 Huang, et al.
IMC 2011 Butkiewicz, et al.
HotMobile 2011 Wang, et al.
httparchive.org 200850 objects
2012100 objects!
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Page Complexity Load Time
Well StudiedMobiSys 2010 Huang, et al.
IMC 2011 Butkiewicz, et al.
HotMobile 2011 Wang, et al.
httparchive.org 200850 objects
2012100 objects!
Webpage Complexity outpacing Mobile Resources
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WebSieve’s GoalState of the Art: Manual Reduction of Complexity
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WebSieve’s GoalState of the Art: Manual Reduction of Complexity
Our Goal: Automate Mobile-Friendly Optimization
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WebSieve’s GoalState of the Art: Manual Reduction of Complexity
Our Goal: Automate Mobile-Friendly Optimization
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– Block Low Importance Objects
WebSieve’s GoalState of the Art: Manual Reduction of Complexity
Our Goal: Automate Mobile-Friendly Optimization
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– Block Low Importance Objects– Prioritize High Importance Objects
WebSieve’s GoalState of the Art: Manual Reduction of Complexity
Our Goal: Automate Mobile-Friendly Optimization
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– Block Low Importance Objects– Prioritize High Importance Objects
WebSieve’s GoalState of the Art: Manual Reduction of Complexity
Our Goal: Automate Mobile-Friendly Optimization
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Challenge 1. Inferring Object Utility
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Low Utility
Low Utility Challenge 1. Inferring Object UtilityLow
Utility
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High Utility
High Utility
Challenge 1. Inferring Object Utility
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? Utility
Challenge 1. Inferring Object Utility
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HTML
CSS JS
Challenge 2. Discovering Dependencies
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HTML
CSS JS
Challenge 2. Discovering Dependencies
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HTML
CSS JS
Challenge 2. Discovering Dependencies
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Challenge 3. Predicting New Load Times
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Server Variability
Challenge 3. Predicting New Load Times
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Script Processing
Server Variability
Challenge 3. Predicting New Load Times
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ParallelConnection
Limits
Script Processing
Server Variability
Challenge 3. Predicting New Load Times
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foo.com/xO1 O2 O3 O4
Front-end Back-end
Our Vision For WebSieve
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Dependency Extraction
foo.com/xO1 O2 O3 O4
Front-end Back-end
Our Vision For WebSieve
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Dependency Extraction
User Utility Inference
ObjectSelection
foo.com/xO1 O2 O3 O4
Front-end Back-end
Our Vision For WebSieve
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Dependency Extraction
User Utility Inference
ObjectSelection
foo.com/xO1 O2 O3 O4
Our Vision For WebSieve
Fetch Fingerprint
Fetch HTML
Front-end Back-end
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Dependency Extraction
User Utility Inference
ObjectSelection
foo.com/xO1 O2 O3 O4
Front-end Back-end
Our Vision For WebSieve
{O1,O3}
Fetch HTML
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Dependency Extraction
User Utility Inference
ObjectSelection
foo.com/xO1 O2 O3 O4
Front-end Back-end
Our Vision For WebSieve
2. Load {O1,O3}
1. HTML Received
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Challenge 1. Inferring Utility
Approach: User Study + Machine Learning
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Challenge 1. Inferring Utility
Approach: User Study + Machine Learning
Simple Machine Learning Not Enough
Personalization Is Key
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HTML
JPG a JS 1
JS 2 JPG b
JPG c
Original Load
Challenge 2. Discover Dependencies
Approach: Block & Infer
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HTML
JPG a JS 1
JS 2 JPG b
JPG c
HTML
JPG a
Original Load Block JS 1
Challenge 2. Discover Dependencies
Approach: Block & Infer
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HTML
JPG a JS 1
JS 2 JPG b
JPG c
HTML
JPG a
HTML
JPG a JS 1
JPG b
Original Load Block JS 1 Block JS 2
Challenge 2. Discover Dependencies
Approach: Block & Infer
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HTML
JPG a JS 1
JS 2 JPG b
JPG c
HTML
JPG a
HTML
JPG a JS 1
JPG b
Original Load Block JS 1 Block JS 2
Challenge 2. Discover Dependencies
Approach: Block & Infer
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Challenge 3. Object Selection
Approach: Page Tree Cut
Util: 5Time: 4s
Util: 2Time: 0.5s
Util: 1Time: 1s
Util: 0Time: 0.1s
Util: 1Time: 2s
Util: 2Time: 0.5s
Util: 5Time: 0.5s
Util: 7Time: 0.4s
Util: 3Time: 2s
• Cut Dependency DAG• Maximize Utility• Respect Load Time Budget
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Challenge 3. Object Selection
Approach: Page Tree Cut
Util: 5Time: 4s
Util: 2Time: 0.5s
Util: 1Time: 1s
Util: 0Time: 0.1s
Util: 1Time: 2s
Util: 2Time: 0.5s
Util: 5Time: 0.5s
Util: 7Time: 0.4s
Util: 3Time: 2s
• Cut Dependency DAG• Maximize Utility• Respect Load Time Budget
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Wrap UpLoad Time Strongly Impacts User Satisfaction
State of the Art: Manual Complexity Reduction
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Wrap UpLoad Time Strongly Impacts User Satisfaction
State of the Art: Manual Complexity ReductionWebSieve: Automate Mobile-Friendly Optimization
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Wrap UpLoad Time Strongly Impacts User Satisfaction
State of the Art: Manual Complexity ReductionWebSieve: Automate Mobile-Friendly Optimization
– Block Low Importance Objects
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Wrap UpLoad Time Strongly Impacts User Satisfaction
State of the Art: Manual Complexity ReductionWebSieve: Automate Mobile-Friendly Optimization
– Block Low Importance Objects– Prioritize High Importance Objects
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Wrap UpLoad Time Strongly Impacts User Satisfaction
State of the Art: Manual Complexity ReductionWebSieve: Automate Mobile-Friendly Optimization
– Block Low Importance Objects– Prioritize High Importance Objects
Challenges: Object Dependency, Utility, Obj. Selection
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Wrap UpLoad Time Strongly Impacts User Satisfaction
State of the Art: Manual Complexity ReductionWebSieve: Automate Mobile-Friendly Optimization
– Block Low Importance Objects– Prioritize High Importance Objects
Challenges: Object Dependency, Utility, Obj. Selection
Ongoing Prototype Development & Promising Results
