Content Delivery Networks Instructor: Peter Baumann email: - - PowerPoint PPT Presentation

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Content Delivery Networks Instructor: Peter Baumann email: - - PowerPoint PPT Presentation

May 31, 2023 41 likes •182 views

Content Delivery Networks Instructor: Peter Baumann email: p.baumann@jacobs-university.de tel: -3178 Credits: Lucy Cherkasova, office: room 88, Research 1 HP Research Labs Palo Alto 340151 Big Data & Cloud Services (P. Baumann) 1

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1 340151 Big Data & Cloud Services (P. Baumann)

Content Delivery Networks

Instructor: Peter Baumann email: p.baumann@jacobs-university.de tel:

  • 3178
  • ffice:

room 88, Research 1

Credits: Lucy Cherkasova, HP Research Labs Palo Alto

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2 340151 Big Data & Cloud Services (P. Baumann)

Website Requests Unpredictable

CNN, NY Times, ABC News unavailable from 9-10 AM (Eastern Time) Content providers’ dilemma: how many resources to provision?

Need on-demand scalability

Usual 9/11*

50 100 150

Page views / day (in millions) CNN.com

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3 340151 Big Data & Cloud Services (P. Baumann)

Content Delivery Networks (CDN)

Source: http://www.tcsa.org/lisa2001/cnn.txt http://www.akamai.com/en/html/about/press/press479.html

200 400 600 800

Normal

  • 12. Sep 01

Election day (Nov 2), 2004

Used Akamai on Election day Page 1.2k instead of 50k

  • n 12-Sep-2001

Page views / day (in millions) 50k 50k 1.2k CNN.com

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4 340151 Big Data & Cloud Services (P. Baumann)

CDN Architecture

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5 340151 Big Data & Cloud Services (P. Baumann)

CDN, Explained

  • Goal: serve content to end-users with high availability, high performance
  • Synonyms:

content delivery network = content distribution network (CDN)

  • distributed system of servers deployed in multiple data centers
  • CDNs serve large fraction of Internet today
  • web objects (text, graphics and scripts)
  • downloadable objects (media files, software, documents)
  • applications (e-commerce, portals)
  • live streaming / on-demand streaming media
  • social networks, …

Also: minimize hops for minimizing „man in the middle“ sniffing, attacks

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6 340151 Big Data & Cloud Services (P. Baumann)

Mechanisms

  • URL rewriting
  • <img src =http://www.xyz.com/images/foo.jpg>
  • <img src =http://akamai.xyz.com/images/foo.jpg>
  • DNS redirection
  • Transparent, no content modification
  • Typically: two-level DNS lookup - choose most appropriate edge server

name -> list of edge servers selected list item -> IP address

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7 340151 Big Data & Cloud Services (P. Baumann)

Transformations in CDNs

  • Delivered contents are usually modified or transformed by proxies
  • Modify sizes and resolutions of multimedia files
  • Customize dynamic web pages based on client preferences
  • Data transformations may involve multiple proxies
  • Security issue: who allowed to do what?
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8 340151 Big Data & Cloud Services (P. Baumann)

Ex: 2-Step Data Transformations

Transcode High Medium Low Customize banner

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9 340151 Big Data & Cloud Services (P. Baumann)

Edge Devices

  • = entry point (ie: router) into enterprise or service provider core networks
  • Translating between heterogeneous network types
  • Ethernet, Token Ring, ATM, ISDN, ...
  • Normally authenticated
  • CDNs use edges as

Point of Presence (PoP)

  • Often 10s of thousands

[img: wikipedia] [www.lboro.ac.uk/gawc/rb/rb136.html]

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10 340151 Big Data & Cloud Services (P. Baumann)

Strategy Parameters

  • How to determine optimal number of edge servers & placement?
  • Two different approaches:
  • Co-location: placing servers closer to the edge (Akamai)
  • Network core: server clusters in large data centers near main network backbones

(Limelight, AT&T)

  • Content placement
  • Needs large-scale system monitoring & management
  • gather evidence as a basis for design decisions
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11 340151 Big Data & Cloud Services (P. Baumann)

Business Model

  • CDN pays ISP, carriers, network operators
  • Advantage:
  • Less transmission costs: data closer to user
  • Some protection against DoS attacks
  • Examples:
  • Akamai; as of 2009: 56,000 servers in 950 networks in 70 countries; deliver 20% of all

Web traffic - ex: CNN

  • Microsoft Azure CDN; Amazon CloudFront; Amazon S3 – online storage (DropBox!)
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12 340151 Big Data & Cloud Services (P. Baumann)

Challenges

  • Efficient large-scale content distribution
  • large files, video on demand, streaming media
  • low latency, real-time requirement
  • FastReplica for CDNs
  • BitTorrent (general purpose)
  • SplitStream (multicast, video streaming)
  • Update propagation
  • Privacy: delete propagation
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13 340151 Big Data & Cloud Services (P. Baumann)

Fog Computing

  • Fog Computing = Cloud Computing + Edge Computing:
  • dynamic localization of services on user demand
  • across Internet
  • cf CDNs: data + services close to user
  • Manifold applications:
  • user devices & routers; Smart Grid; Smart Traffic Lights / connected vehicles; Wireless

Sensor & Actuator Networks; Decentralized Smart Building Control; …

  • Swarms!
  • cf. ORBiDANSe project: Array Database on board an EO satellite
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Discussion

  • “Flash Crowd” problem
  • L. Niven: Flash crowd. In: The Flight of the Horse. Ballantine Books, 1971
  • Goal: High availability + responsiveness key factors for business Web sites
  • overcome server overload for popular sites
  • minimize network impact in delivery path
  • CDN: large-scale distributed network of servers
  • Surrogate servers (proxy caches)

located closer to edges of Internet

  • edge servers 