In-class Paper Review #2 “Improving World Wide Web Latency” By Venkata N. Padmanabhan Department of Computer Science Southern Illinois University Edwardsville

In-class Paper Review #2“Improving World Wide Web Latency”

By Venkata N. Padmanabhan

Department of Computer ScienceSouthern Illinois University Edwardsville

Spring, 2006

Dr. Hiroshi FujinokiE-mail: [email protected]

CS 587 High-Speed Networks

Padmanabhan/000


Padmanabhan/001

Problems in HTTP (HTTP 1.0)

= The required time after a web user makes a request for a web page until the page is (completely) displayed at the user’s local monitor

Possible contributing factors in latency

• Transmission bandwidth

• Network congestion (due to high queuing delay at intermediate routers)

• Client/server host resources

(we can never transmit more than link capacity)

The problem addressed by the author Latency

Example Transmitting a 1 Mbyte file across a 1Mbps link

Never be less than 1 second

• Propagation delay The author claims that this is the most serious limiting factor in web latency


Padmanabhan/002

Why is “propagation delay” is the most significant factor?

• Propagation delay is a function of the constant propagation speed of light

• It is the factor money can not improve anything

It is proportional to the physical end-to-end distance

If the distance becomes doubled, the latency will be doubled

You can not improve it by upgrading to a faster hardware

Reducing traffic load will not reduce the latency

Even transmitting 1 bit over a coast-to-coast will take at least 70 ms using the fastest Internet backbone (> 10Tbps)


Padmanabhan/003

The two approaches used by the author to improve web latency

Hide the propagation delay, if it is impossible to eliminate

There are some delay components that are impossible to eliminate,then, try to hide it.

Approach #2

Approach #1

Eliminate the propagation delay as much as possible.

If there is unnecessary delay components and if it isPossible to eliminate, eliminate it!


Padmanabhan/004

The three techniques the author proposed to hide the web latency

HTTP 1.1 Persistent Connection

HTTP 1.1 Pipelining

Pre-fetching web pages in conjunction client-side caching

Already officially adopted in HTTP 1.1

• Pre-fetch prediction algorithm

• Implementation in HTTP

Backward compatibility is important

Implemented by most of the web browsers


Padmanabhan/005

How to eliminate latency?

Eliminate unnecessary message round-trips in HTTP.

Analysis Phase #1 Understand the essences in HTTP (HTTP 1.0)

(The author called this “a brief sketch of the HTTP protocol” (page 3))

• HTTP protocol is layered over a reliable bidirectional byte stream (i.e., socket) normally TCP.

• Each HTTP interaction consists of a request sent from a client to the server, followed by a response sent from the server (i.e., client-server model).

• Client requests are implemented by:

- Methods (GET, POST, etc)- URL (Universal Resource Locator)- HTTP header (Specific data structure to transmit client information)


Padmanabhan/006

Analysis Phase #1 (continued)

• Client requests are parsed by the server

• The server takes the action(s) according to the specified method.

• The server sends a response to the client (meta-information)

• The server sends a status code

HTTP 200 OK

HTTP 404 Page Not Found

HTTP 500 Access Refused

content-length

• The server transmits the content of a web page (just a file)


Padmanabhan/007


Web Browser Web Server

Connection requestfor a stream socket (=TCP)

acceptconnect Socket type: AF_INET SOCK_STREAM


Padmanabhan/008


Web Browser Web Server

A socket (= TCP) connectionas a bi-directional data channel

Web Browser


Padmanabhan/009


Web Server

• URL: www.siue.edu

• Method: GET index.html HTTP/1.0

• HTTP header

• Parse the client request

• Take the requested action

• Transmit a result status code (HTTP 200 OK)

HTTP 200 OK

• Transmit server-side meta-information

Context-length

Contents of a file

• Transmit the contents of the requested web file


Identify unnecessary round tripsAnalysis Phase #2

Eliminate unnecessary message round-trips in HTTP, but we need toidentify which round-trips are unnecessary.

client server

SYN

SYN-ACK

ACKDAT

ACKDAT

ACKDAT

FINACK

FIN

ACKSYN

SYN-ACK

ACKDAT

DAT

0 RTT

1 RTT

2 RTT

3 RTT

4 RTT

• Establish stream socket• TCP 3-way handshake

• Transmit GET request for index.html top page

• ACK can be piggy-backed to the GET payload packet

• Receive the top page• Parse other required files

• Establish stream socket• TCP 3-way handshake

• Transmit GET request for another file

• Receive the requested page

• TCP prepares data structure for a connection

• Server establishes a connection• Server accesses its local HDD

• Server drops the connection

• TCP prepares data structure for a connection

Padmanabhan/010


Padmanabhan/012

• Which round-trips are unnecessary?

• How can we eliminate those unnecessary round trips??

Padmanabhan said, “almost all of the unnecessary round trips may be eliminated by surprisingly simple changes in HTTP protocol.



Padmanabhan/013


Significant expected benefits in eliminating unnecessary round-trips (page 5)

• Reducing number of round-trips Shorter web latency

• Reducing processing overhead at both client and server

• Reducing connections - Allocating new ports

- Creating/deleting TCP data structures

- Creating/deleting processes/threads

• Reducing application-level workload- Overhead for authentication

- Overhead for message encryption

• Less probability of request refusal due to the max. # of TCP connections

Significant for busy/popular web servers

The author described these to convince The significance of his proposed solutions


Padmanabhan/014


TCP TIME_WAIT and CLOSE_WAIT

TCP TIME_WAIT: A host waits for up to a few minutes (4 min. in default) after FIN message has been released.

For a busy/popular web server, the number of TCP connections opened (and those still not dropped) will quickly hit the max. number ofconnections allowed at a server host.


Padmanabhan/015


At a busy/popular web server host, the TCP connections (entries in the TCP connection management table) tend to increase in a short time.


Padmanabhan/016

Another thought to convince the importance in reducing the number of round-trips

• The average file size in web application is very small

Use of a subjective word

- Mean document size is 13 Kbytes (12,925 bytes)

- The median is 1.77 Kbytes (1,770 bytes)

- 12,727 messages are zero-contents message (TCP+IP header only)

The statistics from 200,000 HTTP retrievals say:

Most of the files are less than 1.7KB. Occasional large files

Only 40 bytes in a message


Padmanabhan/017

Another thought to convince the importance in reducing the number of round-trips

• The average file size in web application is very small

Use of a subjective word

client server

Small messages

S1 R1

U1 = R1/S1

Large messages

client server

S2 R2

U2 = R2/S2

U1 < U2


Solution #1: Persistent Connection

client server

SYN

SYN-ACK

ACKDAT

ACKDAT

ACKDAT

FINACK

FIN

ACKSYN

SYN-ACK

ACKDAT

DAT

Padmanabhan/018

Keep a stream socket connection (= TCPconnection) until you download all the files


Solution #1: Persistent Connection

client server

SYN

SYN-ACK

ACKDAT

ACKDAT

ACKDAT

ACK

DAT

DAT

Padmanabhan/019

Keep a stream socket connection (= TCPconnection) until you download all the files

DAT

DAT

• Round trips reduced

• Reduced TIME_WAIT

• Reduced CLOSE_WAIT


Padmanabhan/020

Implementation details in Persistent Connection

1. Detection of the end of transmissions (page 8)

2. Backward-compatible extension of HTTP 1.0 (page 9)

How can the client know the end of transmissions?

• Boundary delimiter

• Blocked data transmission protocol

• Store-and-forward

• HTTP PC-enabled server should be able to handle PC-non-enabled HTTP clients

• HTTP PC-enabled client should be able to handle PC-non-enabled HTTP servers

• OS-kernel and TCP should not be changed


client server

SYN

SYN-ACK

ACKDAT

ACKDAT

ACKDAT

ACK

DAT

DAT

Padmanabhan/021

DAT

DAT

Solution #2: HTTP Pipelining An improvement over Persistent Connection

client server

SYN

SYN-ACK

ACKDAT

ACKDAT

ACKDAT

ACK

DAT

DAT

DAT

DATDAT

DATDAT

DAT

This parallel HTTP requests areimpossible in PC (since this requires multiple connections)


Padmanabhan/022

Solution #2: HTTP Pipelining

client server

SYN

SYN-ACK

ACKDAT

ACKDAT

ACKDAT

ACK

DAT

GET-ALL

DAT

DAT

DAT

DAT

• Parse the index.html

• Identify all the files needed for this page

• Request all files

Web Browser


Padmanabhan/023

Web Server


• Method: GETALL ***** HTTP/1.0

• HTTP header



HTTP 200 OK


A requested file A requested file A requested file

HTTP Header

FTTP Header contains “context-length” field

US Home

CNN Top


Padmanabhan/024


• HTTP Pipelining working with the client-side cache

Web Browser


Padmanabhan/025

Web Server


• Method: GETLIST ***** HTTP/1.0

• HTTP header

HTTP 200 OK


A requested file A requested fileA requested file

Only the files missing in the client’s cache will be requestedUsing HTTP Pipelining

CNN_icon.gif

US_Home.gifNetScape.gif

ToolBar.gif

Client-Side cache




Padmanabhan/026

Solution #3: HTTP Pre-Fetching

CNN TOP

US Home

Weather page

Travel page



client server

SYN

SYN-ACK

ACKGETALL

ALLFILES

GETALL

ALLFILES

ALLFILES

GETALL

Initial TCP hand- shaking delay

• Requesting TOP page

• Browsing time

• Requesting US home page

• Browsing time

• Requesting weather page

Padmanabhan/027



client server

SYN

SYN-ACK

ACKGETALL

ALLFILES

GETALL

ALLFILES

ALLFILES

GETALL



• Browsing time


• Browsing time


Padmanabhan/028

Latency as observed by a web user



Utilize the time foruser’s browsing totransmit next data



client server

SYN

SYN-ACK

ACKGETALL

ALLFILES

GETALL

ALLFILES

ALLFILES

GETALL



• Browsing time

Padmanabhan/029



• Browsing time






client server

SYN

SYN-ACK

ACKGETALL

ALLFILES

GETALL

ALLFILES

ALLFILES

GETALL



• Browsing time

Padmanabhan/030


• Browsing time



client server

SYN

SYN-ACK

ACKGETALL

ALLFILES

GETALL

ALLFILES

ALLFILES

GETALL



• Browsing time

Padmanabhan/031

• Browsing time

Need to predict which files will be requested

Need to predict which files will be requested



Padmanabhan/032

How can we predict next files to be requested by a web user?

New web customer

Files in USHome

Files in Weather Page

Files in Europe Home

0.5

0.2

0.2

0.3

0.2Files in

Another Page

Files in Another Page

0.25

0.25

index.html(Top page)

This figurealmost stolen from

Padmanabhan’s paper

This figurealmost stolen from

Padmanabhan’s paper



Padmanabhan/033

How to calculate the probability of a group of files to be requested next?

Web Server

Requests from clients

Httpd

Prefecthd

OS/file-system

Log web requests

Prediction Window



Padmanabhan/034


• Concept of “Prediction Window”

index.html(Top page)

- “Prediction Window” = An array of “slots”

- Each slot remembers a file requested

- Remember as many files as in the prediction window



Padmanabhan/035


• The dependency (prediction) graph has an arch from a file A (or a group of files) to another file B, if and only if:

- B was accessed within w accesses after A

(w is the window size)

• The probability (weight) of an arc is the ratio of (the number of accesses to B) to (the number of accesses to A).

INOUT

Prediction Window as FIFO Queue

When a page entry is kicked put or re-inserted, all the files after the one is recorded

Documents

In-class Paper Review #2 “Improving World Wide Web Latency” By Venkata N. Padmanabhan Department of Computer Science Southern Illinois University Edwardsville