Content Distribution Networks

1. CPE 401 / 601Computer Network Systems Content Distribution Networks Modified from Ravi Sundaram, Janardhan R. Iyengar, and others

2. Content and Internet Traffic Internet traffic: • Shifts seismically (emailFTPWebP2Pvideo) • Has many small/unpopular and few large/popular flows Zipf popularity distribution, 1/k Shows up as a line on log-log plot

3. Server Farms and Web Proxies (1) Server farms enable large-scale Web servers: • Front-end load-balances requests over servers • Servers access the same backend database

4. Server Farms and Web Proxies (2) Proxy caches help organizations to scale the Web • Caches server content over clients for performance • implements organization policies (e.g., access)

5. HTTP Caching • Clients often cache documents • When should origin be checked for changes? • Every time? Every session? Date? • HTTP includes caching information in headers • HTTP 0.9/1.0 used: “Expires: <date>”; “Pragma: no-cache” • HTTP/1.1 has “Cache-Control” • “No-Cache”, “Private”, “Max-age: <seconds>” • “E-tag: <opaque value>” • If not expired, use cached copy • If expired, use condition GET request to origin • “If-Modified-Since: <date>”, “If-None-Match: <etag>” • 304 (“Not Modified”) or 200 (“OK”) response

6. Web Proxy Caches • User configures browser: Web accesses via cache • Browser sends all HTTP requests to cache • Object in cache: cache returns object • Else: cache requests object from origin, then returns to client origin server Proxy server HTTP request HTTP request client HTTP response HTTP response HTTP request HTTP response client origin server

7. Caching Example (1) Assumptions • Average object size = 100K bits • Avg. request rate from browsers to origin servers = 20/sec • Delay from institutional router to any origin server and back to router = 2 sec Consequences • Utilization on LAN = 20% • Utilization on access link = 100% • Total delay = Internet delay + access delay + LAN delay = 2 sec + minutes + milliseconds origin servers public Internet 1.5 Mbps access link institutional network 10 Mbps LAN

8. Caching Example (2) Possible Solution • Increase bandwidth of access link to, say, 10 Mbps • Often a costly upgrade Consequences • Utilization on LAN = 20% • Utilization on access link = 20% • Total delay = Internet delay + access delay + LAN delay = 2 sec + milliseconds origin servers public Internet 10 Mbps access link institutional network 10 Mbps LAN

9. Caching Example (3) Install Cache • Support hit rate is 60% Consequences • 60% requests satisfied almost immediately (say 10 msec) • 40% requests satisfied by origin • Utilization of access link down to 53%, yielding negligible delays • Weighted average of delays = .6*2 s + .4*10 ms < 1.3 s origin servers public Internet 1.5 Mbps access link institutional network 10 Mbps LAN institutional cache

10. When a single cache isn’t enough • What if the working set is > proxy disk? • Cooperation! • A static hierarchy • Check local • If miss, check siblings • If miss, fetch through parent • Internet Cache Protocol (ICP) • ICPv2 in RFC 2186 (& 2187) • UDP-based, short timeout public Internet Parent web cache

11. Problems with discussed approaches:Server farms and Caching proxies • Server farms do nothing about problems due to network congestion, or to improve latency issues due to the network • Caching proxies serve only their clients, not all users on the Internet • Content providers (say, Web servers) cannot rely on existence and correct implementation of caching proxies • Accounting issues with caching proxies. • For instance, www.cnn.com needs to know the number of hits to the webpage for advertisements displayed on the webpage

12. Problems • Significant fraction (>50% ) of HTTP objects un-cacheable • Sources of dynamism? • Dynamic data: Stock prices, scores, web cams • CGI scripts: results based on passed parameters • Cookies: results may be based on passed data • SSL: encrypted data is not cacheable • Advertising / analytics: owner wants to measure # hits • Random strings in content to ensure unique counting • But…most dynamic content is small, • while static content is large (images, video, .js, .css, etc.)

13. Content Distribution Networks (CDNs) • Content providers are CDN customers Content replication • CDN company installs thousands of servers throughout Internet • In large datacenters • or, close to users • CDN replicates customers’content • When provider updates content, CDN updates servers origin server in North America CDN distribution node CDN server in S. America CDN server in Asia CDN server in Europe

14. The Web:Simple on the Outside… ContentProviders EndUsers Internet

15. …But Problematic on the Inside Peering Points ContentProviders End Users Network Providers UUNet NAP Qwest NAP AOL

16. Why does my click not work • Latency - Browser takes a long time to load the page • Packet Loss - Browser hangs, user needs to hit refresh • Jitter - Streams are jerky • Server load - Browser connects but does not fully load the page • Broken/missing content

17. The Akamai Solution ContentProviders EndUsers Servers at Network Edge NAP NAP

18. Benefits of CDNs • Improved end-user experience • reduce latency • reduce loss • reduce jitter • Reduced network congestion • Increased scalability • Improved fault-tolerance • Reduced vulnerability • Reduced costs

19. CDN vs. Caching Proxies • Caches are used by ISPs to reduce bandwidth consumption, CDNs are used by content providers to improve quality of service to end users • Caches are reactive, CDNs are proactive • Caching proxies cater to their users (web clients) and not to content providers (web servers), • CDNs cater to the content providers (web servers) and clients • CDNs give control over the content to the content providers, caching proxies do not

20. CDNs – Content Delivery Networks (1) CDNs scale Web servers by having clients get content from a nearby CDN node (cache)

21. Content Delivery Networks (2) Directing clients to nearby CDN nodes with DNS: • Client query returns local CDN node as response • Local CDN node caches content for nearby clients and reduces load on the origin server

22. Content Delivery Networks (3) Origin server rewrites pages to serve content via CDN Traditional Web page on server Page that distributes content via CDN

23. CDN Architecture Origin Server CDN Request Routing Infrastructure Distribution and Accounting Infrastructure Surrogate Surrogate Client Client

24. CDN Components • Content Delivery Infrastructure: Delivering content to clients from surrogates • Request Routing Infrastructure: Steering or directing content request from a client to a suitable surrogate • Distribution Infrastructure: Moving or replicating content from content source (origin server, content provider) to surrogates • Accounting Infrastructure: Logging and reporting of distribution and delivery activities

25. Server Interaction with CDN www.cnn.com Origin Server • Origin server pushes new content to CDN • OR • CDN pulls content from origin server CDN 1 Distribution Infrastructure 2 2. Origin server requests logs and other accounting info from CDN OR CDN provides logs and other accounting info to origin server Accounting Infrastructure

26. Client Interaction with CDN CDN california.cnn.akamai.com 1. Hi! I need www.cnn.com/sochi Surrogate (CA) • Go to surrogate • delaware.cnn.akamai.com Request Routing Infrastructure 3. Hi! I need content /sochi delaware.cnn.akamai.com Surrogate (DE) 1 2 3 Client Q: How did the CDN choose the Delaware surrogate over the California surrogate ?

27. Content Distribution Networks & Server Selection • Replicate content on many servers • Challenges • How to replicate content • Where to replicate content • How to find replicated content • How to choose among known replicas • How to direct clients towards replicas

28. Server Selection • Which server? • Lowest load: to balance load on servers • Best performance: to improve client performance • Based on Geography? RTT? Throughput? Load? • Any alive node: to provide fault tolerance • How to direct clients to a particular server? • As part of routing: anycast, cluster load balancing • As part of application: HTTP redirect • As part of naming: DNS

29. Trade-offs between approaches • Routing based (IP anycast) • Pros: Transparent to clients, circumvents many routing issues • Cons: Little control, complex, scalability • Application based (HTTP redirects) • Pros: Application-level, fine-grained control • Cons: Additional load and RTTs, hard to cache • Naming based (DNS selection) • Pros: Well-suitable for caching, reduce RTTs • Cons: Request by resolver not client, request for domain not URL, hidden load factor of resolver’s population • Much of this data can be estimated “over time”

30. DNS based Request-Routing • Common due to the ubiquity of DNS as a directory service • Specialized DNS server inserted in DNS resolution process • DNS server is capable of returning a different set of A, NS or CNAME records based on policies/metrics

31. DNS based Request-Routing www.cnn.com Akamai CDN california.cnn.akamai.com delaware.cnn.akamai.com Surrogate 58.15.100.152 DNS response: A 145.155.10.15 DNS query: www.cnn.com Surrogate 145.155.10.15 Session DNS query: www.cnn.com merlot.cis.udel.edu 128.4.30.15 local DNS server (louie.udel.edu) 128.4.4.12 DNS response: A 145.155.10.15 Q: How does the Akamai DNS know which surrogate is closest ? Akamai DNS

32. DNS based Request-Routing www.cnn.com Akamai DNS Akamai CDN Measurement results Measure to Client DNS Measurement results Measure to Client DNS Surrogate Surrogate DNS response DNS query Measurements Measurements Session DNS query local DNS server (louie.udel.edu) 128.4.4.12 merlot.cis.udel.edu 128.4.30.15 DNS response

33. What is the Mapping Problem • Problem of directing requests to servers so as to optimize end-user experience • reduce latency • reduce loss • reduce jitter • Assumption - servers are fine • Applicable to 2 mirrors or 1000s of Akamai locations

34. Server Selection Metrics • Network Proximity (Surrogate to Client): • Network hops (traceroute) • Internet mapping services (NetGeo, IDMaps) • … • Surrogate Load: • Number of active TCP connections • HTTP request arrival rate • Other OS metrics • … • Bandwidth Availability • …

35. Attempt • Measure which is closer • Closeness changes over time • Measure frequently • Bothers people • Too many to do ~500,000 unique nameservers on any given day 10 sec per measurement cycle

36. Idea • Topology • relatively static • changes in BGP time • order of hours if not days • Congestion • dynamic • changes in round-trip time • order of milliseconds

37. Set cover • Let sets represent proxy points • Let elements represent nameservers • Find minimum collection of proxy points covering nameservers X covers 1, 2, 3 and 4 X 1 2 3 4

38. Topology Discovery • At each mirror maintain list of partial paths to nameservers • At each epoch extend paths by 1, in randomized fashion, and exchange with other mirror • If the two (partial) paths to a namerver have intersected then declare that nameserver done. • If path has reached forbidden IP then wait • Use pair of proxies in case of failure

39. Topology Discovery 500,000 nameservers reduced to 90,000 proxy points (clusters) Problem - Still too many measurements to do. 90,000 measurements every 10s with 32B packets requires a few Mbps per mirror. Solution - Importance based sampling • 7,000 account for 95% end-user load! Maps built every 10s

40. CDN Types (Skeletal) CDNs Hosting CDN Relaying CDN Full Site Content Delivery Partial Site Content Delivery Request Routing Techniques DNS based URL Rewriting

41. Value of a CDN • Scale: Aggregate infrastructure size • Reach: Diversity of content locations (diverse placement of surrogates) • Request routing efficiency, delivery techniques

42. How Akamai Works • Clients fetch html document from primary server • E.g. fetch index.html from cnn.com • URLs for replicated content are replaced in HTML • E.g. <imgsrc=“http://cnn.com/af/x.gif”> replaced with <imgsrc=http://a73.g.akamai.net/7/23/cnn.com/af/x.gif> • Or, cache.cnn.com, and CNN adds CNAME (alias) for cache.cnn.com a73.g.akamai.net • Client resolves aXYZ.g.akamaitech.net hostname • Maps to a server in one of Akamai’s clusters

43. How Akamai Works • Akamai only replicates static content • At least, simple version. Akamai also lets sites write code that run on their servers, but that’s a pretty different beast • Modified name contains original file name • Akamai server is asked for content • Checks local cache • Check other servers in local cluster • Otherwise, requests from primary server and cache file • CDN is a large-scale, distributed network • Akamai has ~25K servers spread over ~1K clusters world-wide • Why do you want servers in many different locations? • Why might video distribution architectures be different?

44. How Akamai Works • Root server gives NS record for akamai.net • This nameserver returns NS record for g.akamai.net • Nameserver chosen to be in region of client’s name server • TTL is large • g.akamai.netnameserver chooses server in region • Should try to chose server that has file in cache • Uses aXYZ name and hash • TTL is small • Small modification to before: • CNAME cache.cnn.com cache.cnn.com.akamaidns.net • CNAME cache.cnn.com.akamaidns.net  a73.g.akamai.net

45. How Akamai Works – Already Cached cnn.com (content provider) DNS root server Akamai server End-user GET index.html Akamai high-level DNS server 1 2 Akamai low-level DNS server 7 8 Nearby hash-chosenAkamai server 9 10 GET /cnn.com/foo.jpg

46. How Akamai Works cnn.com (content provider) DNS root server Akamai server End-user GET foo.jpg 12 GET index.html 11 Akamai high-level DNS server 5 1 2 3 6 4 Akamai low-level DNS server 7 8 Nearby hash-chosenAkamai server 9 10 GET /cnn.com/foo.jpg