understanding website complexity: measurements, metrics, and implications

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Understanding Website Complexity: Measurements, Metrics, and Implications

Michael ButkiewiczHarsha Madhyastha UC Riverside

Vyas Sekar Intel Labs

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doubleclick.net

cnn.comfacebook.com

cdn.turner.comads.cnn.com

Websites today are very complex!Diverse content from many servers and third party services

67% of users encounter “slow” sites once a week (gomez.com)

30% > 3 Seconds

Median = 2 Seconds

Users see slow loading websites!

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Why does load time matter?

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Source: gomez.com

Implications for: Website ownersEnd usersBrowser developersCustomization

Our work

• Comprehensive study of website complexity– Analysis of sites across rank and category– Content and Service level metrics

• Key metrics that impact performance

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Roadmap

• Introduction

• Measurement Setup

• Complexity

• Performance Implications

• Discussion and Summary

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Measurement Setup

• Selecting websites– 1,700 websites from Quantcast top 20k– Primary focus on landing (home) page – Annotated with Alexa Categories

• Tools– Firefox + Firebug– No Local Caching

• Approach – 4 vantage points (3 EC2, 1 UCR)– Every 60 second one page loaded– ~30 measurements per site per vantage point over 9 weeks

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Example Site Download

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CSS

Image

Script

HTML

Time

A B C DObjects

"log":{ "browser":{ "name":"Firefox”, }, "pages":[{ "startedDateTime":"18:12:59.702-04:00", "title":"Wired News”, "pageTimings":{ "onLoad":4630 }] "entries":[{ "startedDateTime":"18:12:59.702-04:00", "time”:75, "request":{ ... "headers":[{ "name":"Host", "value":"www.wired.com" }, } “response":{ "content":{ "mimeType":"text/html", "size":186013, ... ...

Example Firebug Log

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Roadmap

• Introduction

• Measurement Setup

• Complexity – Content-level– Service-level

• Performance Implications

• Discussion and future work

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Median Site = 57 Objects!

Number of Objects: Across Categories

Median125 Objects!

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20% > 100!

Number of Objects: Across Ranks

Not as much difference across rank ranges

Types of Content

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Median site: 33 Images, 10 JavaScript, 3 CSS, 0 Flash Flash

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Normalized types of content

Type % Mostly Homogeneous; Flash Skewed

Roadmap

• Introduction

• Measurement Setup

• Complexity – Content-level– Service-level

• Performance Implications

• Discussion and Summary

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Median site requires contacting 8 servers16

Median News30 Servers!

Number of Servers

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Median News20 Origins!

20% Sites > 13 Origins

Median site requires contacting 6 origins

Number of Origins

Popular non-origin providersName % of sitesgoogle-analytics 58doubleclick 45quantserve 30scorecardresearch 272mdn 24googleadservices 18facebook 17yieldmanager 16

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Most common services: Analytics & AdvertisingMost common objects: Image (small!) and Javascript

bluekai.comimrworldwide.cominvitemedia.com

> 5% of sites each!

Not just usual suspects!

Contribution of non-origin services

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Median SiteObjects / Bytes 30% 35%

20% sites > 80%from 3rd Party

Contribution of non-origin services

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Time only 15%

Median SiteObjects / Bytes 30% 35%

80% from 3rd Party

Roadmap

• Introduction

• Measurement Setup

• Complexity

• Performance Implications

• Discussion and Summary

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Metric Review

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Content-Level Characteristics• Total Objects• Object Type: Number, Size• Absolute & Normalized

Service-Level Characteristics• Number: Server & Origins• Non-Origin Fraction: Servers / Objects / Time

Total combination of 33 metrics

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Load Time vs. Metric Correlation

Load Time Variability vs. Metrics

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Roadmap

• Introduction

• Measurement Setup

• Complexity – Content-level– Service-level

• Performance Implications

• Discussion and Summary

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Discussion: Many other variables

• Client-side plugins– NoScript reduces #objects by half!

• Mobile-specific customizations– Mobile version reduces #objects to a quarter

• Landing vs. non-landing pages– Non-landing seem less complex

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Conclusions• Comprehensive study of Website Complexity

• Median site: 57 objects, contacts 8 servers across 6 origins

• Categories show more differences than popularity ranks

• Non-origin content:– Analytics & advertising popular– large # objects, bytes, servers, not time

• Key performance indicators:– Load Time # objects– Variability # servers

Data: www.cs.ucr.edu/~harsha/web_complexity

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