1. The Web and Content Distribution Networks
Nick Feamster CS 6250 Fall 2011
Blast through HTTP review slides on the projector.
Swap back to chalkboard for new stuff.
(some notes from David Andersen and Christian Kauffman)

2. Outline HTTP review Persistent HTTP review HTTP caching
Content distribution networks

3. HTTP Basics HTTP layered over bidirectional byte stream Interaction
Almost always TCP
Interaction
Client sends request to server, followed by response from server to client
Requests/responses are encoded in text
Stateless
Server maintains no information about past client requests

4. How to Mark End of Message?
Size of message  Content-Length
Must know size of transfer in advance
Delimiter  MIME-style Content-Type
Server must “escape” delimiter in content
Close connection
Only server can do this

5. HTTP Request Request line Method URL (relative) HTTP version
GET – return URI
HEAD – return headers only of GET response
POST – send data to the server (forms, etc.)
URL (relative)
E.g., /index.html
HTTP version

6. HTTP Request (cont.) Request headers Blank-line Body
Authorization – authentication info
Acceptable document types/encodings
From – user
If-Modified-Since
Referrer – what caused this page to be requested
User-Agent – client software
Blank-line
Body

7. HTTP Request (review)

8. HTTP Request Example
GET / HTTP/1.1 Accept: */* Accept-Language: en-us Accept-Encoding: gzip, deflate User-Agent: Mozilla/5.0 Host: Connection: Keep-Alive

9. HTTP Response Status-line HTTP version 3 digit response code
1XX – informational
2XX – success
200 OK
3XX – redirection
301 Moved Permanently
303 Moved Temporarily
304 Not Modified
4XX – client error
404 Not Found
5XX – server error
505 HTTP Version Not Supported
Reason phrase

10. HTTP Response Headers Blank-line Body Location – for redirection
Server – server software
WWW-Authenticate – request for authentication
Allow – list of methods supported (get, head, etc)
Content-Encoding – E.g x-gzip
Content-Length
Content-Type
Expires
Last-Modified
Blank-line
Body

11. HTTP Response Example
% curl -D - -o /dev/null HTTP/ OK Date: Tue, 25 Oct :50:28 GMT Server: Apache/ (Debian) X-Powered-By: PHP/ squeeze1 Set-Cookie: a1c6441c5610e cceee6bfd0ef=q3a5oq1e47ncpkn97mqbo47qm0; path=/ P3P: CP="NOI ADM DEV PSAi COM NAV OUR OTRo STP IND DEM" Set-Cookie: ja_purity_tpl=ja_purity; expires=Sun, 14-Oct :50:28 GMT; path=/ Expires: Mon, 1 Jan :00:00 GMT Last-Modified: Tue, 25 Oct :50:28 GMT Cache-Control: no-store, no-cache, must-revalidate, post-check=0, pre-check=0 Pragma: no-cache Vary: Accept-Encoding Transfer-Encoding: chunked Content-Type: text/html; charset=utf-8

12. Outline HTTP intro and details Persistent HTTP HTTP caching
Content distribution networks

13. HTTP 0.9/1.0 One request/response per TCP connection Disadvantages
Simple to implement
Disadvantages
Multiple connection setups  three-way handshake each time
Several extra round trips added to transfer
Multiple slow starts
Now that you’ve seen TCP in the previous lectures, the overhead of one TCP connection per object is more clear.

14. Single Transfer Example
Client
Server
0 RTT
SYN
Client opens TCP connection
SYN
1 RTT
ACK
DAT
Client sends HTTP request for HTML
Server reads from disk
ACK
DAT
FIN
2 RTT
ACK
Client parses HTML
Client opens TCP connection
FIN
ACK
SYN
SYN
3 RTT
ACK
Client sends HTTP request for image
DAT
Server reads from disk
ACK
4 RTT
DAT
Image begins to arrive
Lecture 19:

15. -- Things to think about --
More Problems
Short transfers are hard on TCP
Stuck in slow start
Loss recovery is poor when windows are small
Lots of extra connections
Increases server state/processing
Server also forced to keep TIME_WAIT connection state
-- Things to think about --
Why must server keep these?
Tends to be an order of magnitude greater than # of active connections, why?

16. Persistent Connection Solution
Multiplex multiple transfers onto one TCP connection
How to identify requests/responses
Delimiter  Server must examine response for delimiter string
Content-length and delimiter  Must know size of transfer in advance
Block-based transmission  send in multiple length delimited blocks
Store-and-forward  wait for entire response and then use content-length
Solution  use existing methods and close connection otherwise

17. Persistent Connection Example
Client
Server
0 RTT
DAT
Client sends HTTP request for HTML
Server reads from disk
ACK
DAT
1 RTT
ACK
Client parses HTML
Client sends HTTP request for image
DAT
Server reads from disk
ACK
DAT
2 RTT
Image begins to arrive
Lecture 19:

18. Persistent HTTP Nonpersistent HTTP issues:
Requires 2 RTTs per object
OS must work and allocate host resources for each TCP connection
But browsers often open parallel TCP connections to fetch referenced objects
Persistent HTTP
Server leaves connection open after sending response
Subsequent HTTP messages between same client/server are sent over connection
Persistent without pipelining:
Client issues new request only when previous response has been received
One RTT for each referenced object
Persistent with pipelining:
Default in HTTP/1.1
Client sends requests as soon as it encounters a referenced object
As little as one RTT for all the referenced objects

19. Outline HTTP intro and details Persistent HTTP HTTP caching
Content distribution networks

20. HTTP Caching Clients often cache documents
Challenge: update of documents
If-Modified-Since requests to check
HTTP 0.9/1.0 used just date
HTTP 1.1 has an opaque “entity tag” (could be a file signature, etc.) as well
When/how often should the original be checked for changes?
Check every time?
Check each session? Day? Etc?
Use Expires header
If no Expires, often use Last-Modified as estimate
Ask: What’s the problem with just using date for IMS queries?
- Web servers may generate content per-client Examples: CGI scripts, things like google customized home,
vary with cookies, client IP, referrer, accept-encoding, etc.

21. Example Cache Check Request
GET / HTTP/1.1 Accept: */* Accept-Language: en-us Accept-Encoding: gzip, deflate If-Modified-Since: Mon, Oct :54:18 GMT If-None-Match: "7a11f-10ed-3a75ae4a" User-Agent: Mozilla/5.0 (Windows; U; Windows NT 5.1; de; rv: ) Host: Connection: Keep-Alive

22. Example Cache Check Response
HTTP/ Not Modified Date: Mon, 24 Oct :50:51 GMT Server: Server: Apache/ (Debian) Connection: Keep-Alive Keep-Alive: timeout=15, max=100 ETag: "7a11f-10ed-3a75ae4a”

23. Ways to cache
Client-directed caching: Web Proxies Server-directed caching: Content Delivery Networks (CDNs)

24. 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 server, then returns object to client
origin
server
Proxy
server
HTTP request
HTTP request
client
HTTP response
HTTP response
HTTP request
HTTP response
client
origin
server

25. Caching Example (1) Assumptions Average object size = 100,000 bits
Avg. request rate from institution’s browser to origin servers = 15/sec
Delay from institutional router to any origin server and back to router = 2 sec
Consequences
Utilization on LAN = 15%
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

26. Caching Example (2) Install cache origin Consequence servers
Suppose hit rate is .4
Consequence
40% requests will be satisfied almost immediately (say 10 msec)
60% requests satisfied by origin server
Utilization of access link reduced to 60%, resulting in negligible delays
Weighted average of delays
= .6*2 sec + .4*10msecs < 1.3 secs
origin
servers
public
Internet
1.5 Mbps
access link
institutional
network
10 Mbps LAN
institutional
cache

27. Problems Over 50% of all HTTP objects are uncacheable – why?
Not easily solvable
Dynamic data  stock prices, scores, web cams
CGI scripts  results based on passed parameters
Obvious fixes
SSL  encrypted data is not cacheable
Most web clients don’t handle mixed pages well many generic objects transferred with SSL
Cookies  results may be based on past data
Hit metering  owner wants to measure # of hits for revenue, etc.
What will be the end result?

28. Outline HTTP intro and details Persistent HTTP HTTP caching
Content distribution networks

29. Content Distribution Networks (CDNs)
origin server
in North America
The content providers are the CDN customers.
Content replication
CDN company installs hundreds of CDN servers throughout Internet
Close to users
CDN replicates its customers’ content in CDN servers. When provider updates content, CDN updates servers
CDN distribution node
CDN server
in S. America
CDN server
in Asia
CDN server
in Europe

30. 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 know replicas
How to direct clients towards replica

31. 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
Not covered
As part of application  HTTP redirect
As part of naming  DNS
Ask: What things might you want to pick the server using?
How do you direct clients to a server? Anyone know how Akamai works?

32. Application-Based Content Routing
HTTP supports simple way to indicate that Web page has moved (30X responses)
Server receives GET request from client
Decides which server is best suited for particular client and object
Returns HTTP redirect to that server
Can make informed application specific decision
May introduce additional overhead  multiple connection setup, name lookups, etc.
OK solution in general, but…
HTTP Redirect has some flaws – especially with current browsers
Incurs many delays, which operators may really care about
Draw diagram: Client ---> Server
<---redir----
> Server 2
<----answer----

33. Naming-Based Content Routing
Client does DNS name lookup for service
Name server chooses appropriate server address
A-record returned is “best” one for the client
What information can name server base decision on?
Server load/location  must be collected
Information in the name lookup request
Name service client  typically the local name server for client

34. Other Findings Each CDN performed best for at least one (NIMI) client
Why? Because of proximity?
The best origin sites were better than the worst CDNs
CDNs with more servers don’t necessarily perform better
Note that they don’t know load on servers…
HTTP 1.1 improvements (parallel download, pipelined download) help a lot
Even more so for origin (non-CDN) cases
Note not all origin sites implement pipelining

35. What is a Content Distribution Network?
The RFCs and Internet Drafts define a Content Distribution Network, “CDN”, as:
Content Delivery Network or Content Distribution Network. A type of CONTENT NETWORK in which the CONTENT NETWORK ELEMENTS are arranged for more effective delivery of CONTENT to CLIENTS.

36. What is a Content Distribution Network?
A CDN is an overlay network, designed to deliver content from the optimal location
In many cases, optimal does not mean geographically closest
CDNs are made of distinct, geographically disparate groups of servers, with each group able to serve all content on the CDN
Servers may be separated by type
E.g. One group may serve Windows Streaming Media, another group may serve HTTP
Servers are not typically shared between media types

37. What is a Content Distribution Network
Some CDNs are network-owned (Level 3, Limelight, AT&T), some are not (Akamai, Mirror Image, CacheFly, Panther Express)
Network-owned CDNs have all / most of their servers in their own ASN
Non-network CDNs can place servers directly in other ASNs
This means things like NetFlow will not be useful for determining traffic to/from non-network CDNs

38. The Akamai System 85,000+ Servers 1700+ POPs 72+ Countries
The Akamai EdgePlatform:
85,000+
Servers
1700+
POPs
72+
Countries
950+ Networks
660+ Cities
Resulting in traffic of:
5.4 petabytes / day
790+ billion hits / day
436+ million unique clients IPs / day
(circa April 2011)

39. How CDNs Work
When content is requested from a CDN, the user is directed to the optimal server
This is usually done through the DNS, especially for non-network CDNs
It can be done though anycasting for network owned CDNs
Users who query DNS-based CDNs be returned different A records for the same hostname
This is called “mapping”
The better the mapping, the better the CDN

40. How CDNs Work Example of CDN mapping
Notice the different A records for different locations:
[NYC]% host
CNAME a568.d.akamai.net
a568.d.akamai.net A
a568.d.akamai.net A
[Boston]% host
a568.d.akamai.net A
a568.d.akamai.net A

41. CDN Mapping: Another Example
From Atlanta
% ping youtube.com PING youtube.com ( ) 56(84) bytes of data.
64 bytes from yx-in-f93.1e100.net ( ): icmp_req=1 ttl=54 time=1.81 ms
From Boston
% ping youtube.com PING youtube.com ( ) 56(84) bytes of data. 64 bytes from ord08s07-in-f9.1e100.net ( ): icmp_seq=1 ttl=52 time=22.8 ms

42. How CDNs Work CDNs use multiple criteria to choose the optimal server
These include standard network metrics:
Latency
Throughput
Packet loss
These also include things like CPU load on the server, HD space, network utilization, etc.
Geography still counts
That whole speed-of-light thing
Should be able to solve that with the next version of ethernet…

43. Why CDNs Peer with ISPs
The first and foremost reason to peer is improved performance
Since a CDN tries to serve content as “close” to the end user as possible, peering directly with networks (over non-congested links) obviously helps
Peering gives better throughput
Removing intermediate AS hops seems to give higher peak traffic for same demand profile
Might be due to lower latency opening TCP windows faster
Might be due to lower packet loss

44. Why CDNs Peer with ISPs Redundancy Burstability
Having more possible vectors to deliver content increases reliability
Burstability
During large events, having direct connectivity to multiple networks allows for higher burstability than a single connection to a transit provider
Burstability is important to CDNs
One of the reasons customers use CDNs is for burstability

45. Why CDNs Peer with ISPs Peering reduces costs Network Intelligence
Reduces transit bill (duh)
Network Intelligence
Receiving BGP directly from multiple ASes helps CDNs map the Internet
Backup for on-net servers
If there are servers on-net, the IX can act as a backup during downtime and overflow
Allows serving different content types

46. Why ISPs peer with CDNs Performance Cost Reduction
CDNs and ISPs are in the same business, just on different sides - we both want to serve end users as quickly and reliably as possible
You know more about your network than any CDN ever will, so working with the CDN directly can help them deliver the content more quickly and reliably
Cost Reduction
Transit savings
Possible backbone savings

47. How Non-Network CDNs use IXes
Peer Network
Non-network CDNs do not have a backbone, so each IX instance is independent
The CDN uses transit to pull content into the servers
Content is then served to peers over the IX IX
Content
CDN Servers
Transit
Origin Server

48. How CDNs use IXes
Non-network CDNs usually do not announce large blocks of address space because no one location has a large number of servers
It is not uncommon to see a single /24 from a CDN at an IX
This does not mean you will not see a lot of traffic
How many web servers does it take to fill a gigabit these days?

49. How well do CDNs work? Hosting Center Hosting Center OS Backbone ISPCS CS CS IX IX
Recall that the bottleneck links are at the edges.
Even if CSs are pushed towards the edge, they are still behind the bottleneck link!
Site
ISP CS
ISP
ISP CS S S S
Sites S S S S S C C C

50. Reduced latency can improve TCP performance
DNS round trip
TCP handshake (2 round trips)
Slow-start
~8 round trips to fill DSL pipe
total 128K bytes
Compare to 56 Kbytes for cnn.com home page
Download finished before slow-start completes
Total 11 round trips
Coast-to-coast propagation delay is about 15 ms
Measured RTT last night was 50ms
No difference between west coast and Cornell!
30 ms improvement in RTT means 330 ms total improvement
Certainly noticeable

51. Lets look at a study Zhang, Krishnamurthy and Wills
AT&T Labs
Traces taken in Sept and Jan. 2001
Compared CDNs with each other
Compared CDNs against non-CDN

52. Methodology Selected a bunch of CDNs
Akamai, Speedera, Digital Island
Note, most of these gone now!
Selected a number of non-CDN sites for which good performance could be expected
U.S. and international origin
U.S.: Amazon, Bloomberg, CNN, ESPN, MTV, NASA, Playboy, Sony, Yahoo
Selected a set of images of comparable size for each CDN and non-CDN site
Compare apples to apples
Downloaded images from 24 NIMI machines

53. Response Time Results (II) Including DNS Lookup Time
About one second
Cumulative Probability
Author conclusion: CDNs generally provide much shorter download time.

54. HTTP (Summary) Simple text-based file exchange protocol Workloads
Support for status/error responses, authentication, client-side state maintenance, cache maintenance
Workloads
Typical documents structure, popularity
Server workload
Interactions with TCP
Connection setup, reliability, state maintenance
Persistent connections
How to improve performance
Caching
Replication