Multi-Layer Analysis of Web Browsing Performance for

Wireless PDAs

Adesola Omotayo & Carey Williamson

April 22, 2023

2

Presentation Outline

Introduction & MotivationRelated WorkData Gathering & ValidationHTTP-level AnalysisTCP-level AnalysisMAC-level & Error AnalysisSummaryFuture Work

3

Introduction & Motivation

Widespread availability of WiFi hot spots

Limited understanding of multi-layer protocol interactions over IEEE 802.11b WLAN

Crucial to understand the performance of the wireless Web

4

Related WorkWorkload of clients at wireline networks

Client-based“Changes in Web Client Access Patterns”,P. Barford, A. Bestavros, A. Bradley, and M. Crovella, 1999

Server-based“Internet Web Servers: Workload Characterization and Performance Implications”,M. Arlitt and C. Williamson, October 1997

Proxy-based“On the Scale and Performance of Cooperative Web Proxy Caching”,A. Wolman, G. Voelker, N. Sharma, N. Cardwell, A. Karlin, and H. Levy, December 1999

Workload of wireless clientsLocal-area

“Analysis of a Local-Area Wireless Network”, D. Tang and M. Baker, August 2000Campus-area

“Analysis of a Campus-Wide Wireless Network”, D. Kotz and K. Essien, September 2002Metropolitan-area

“Analysis of a Metropolitan-Area Wireless Network”, D. Tang and M. Baker, August 1999

5

Data Gathering & Validation

Selected websitesnews, yellow pages, driving directions, stock quotes, educational resources, and downloadable PDA software

Over a period of 35 minutes398 TCP connections

1.8% with expected FIN handshake96.5% used the RST packet 1.7% unsuccessful connections

Wireless Client

Internet

Wired Network

Access Point

Wireless Sniffer

A very simple workload

AP: Netgear WAB 102

PDA: Compaq iPAQ 3600 Pocket PC, Windows CE, IE, MTU size of 1500 bytes

Wireless Sniffer: Sniffer Pro 4.60.01, microsecond resolution timestamps

6

HTTP-level AnalysisServer Response Time

distinct plateaus

consistent server response time

response times < 200 ms

Network RTT dominates the response latency

Cache per-destination state information

Server Response Time versus Connection ID

yahoo

fore

cast

erfo

reca

ster

hmdns

quickdrive

atlantic

tuco

ws

cpsc

i-mec

ca

tucows

airsurfer

CNN

cpsc

tucows

akam

aifa

ntas

yspo

rtsfa

ntas

yspo

rts

cnet

akam

ai

cpsc

weather3

cpsc UofC

chutch

akam

aicn

et

cnet

0

0.05

0.1

0.15

0.2

0.25

0 50 100 150 200 250 300 350Connection ID

Serv

er R

espo

nse

Tim

e in

sec

onds

7

HTTP-level Analysis

Web Object Sizesobject sizes:

90% < 10 KB2.5% > 40 KB

file types:most prevalent: GIF, JPG & HTMLLeast prevalent: PNG

largest objects transferred:executables

Cache contents from wireless portals on Proxy Servers

Increase support for PNG file type across browsers

Compress executable files to be more compact

Distribution of HTTP Transfer sizes

0

5

10

15

20

25

30

0 5000 10000 15000 20000 25000 30000 35000 40000

HTTP Transfer Size in Bytes

Freq

uenc

y in

Per

cent

8

HTTP-level Analysis

HTTP Transfer TimeScatter Plot of HTTP Response Time

0.001

0.01

0.1

1

10

100

1000

1 10 100 1000 10000 100000 1000000

HTTP Response Size in Bytes

Tran

sfer

Tim

e in

Sec

onds

HTTP transfers96% < 1 second2.5% > 2 seconds

larger objects take longer to download

few small objects have excessively long transfer times

HTTP transfer times are generally low

Most responses fit in a single TCP packet

9

TCP-level Analysis

TCP Connection TypeNumber of HTTP Requests Per Connection

akam

ai21

6.23

9.39

.99

216.

239.

39.9

9

akam

aiadminUofCgoogle

akamaiquickdrive

CNN

0

10

20

30

40

50

60

70

80

0 51 102 152 204 254 304 355Connection ID

Num

ber o

f HTT

P R

eque

sts

13% were persistent

87% were non-persistent

4% of TCP connections sent > 10 HTTP requests

65% of HTTP transfers occurred on persistent connectionsAs much as 73 HTTP requests were seen per connection

Use persistent connections for all web sites

10

TCP-level Analysis

TCP Connection Duration75% sent < 20 packets6% sent > 100 packets

80% sent < 10 KB8% sent > 50 KB

75% lasted < 1 second10% lasted > 30 seconds

4 connections lasted > 300 sec.

Most TCP connections are non-persistent

Most web object transfers are small

Tightly set the persistent connection timeout

Distribution of TCP Connection Duration

0

5

10

15

20

25

30

35

40

0 5 10 15 20 25 30

Connection Duration in Seconds

Freq

uenc

y in

Per

cent

11

TCP-level Analysis

TCP Connection Throughput

Connection Throughput in bits per second (bps)

14

12

10

8

6

4

2

00 0 200000 400000 600000 800000 1e+06 1.2e+06

Distribution of TCP Connection Throughput

Freq

uenc

y in

Per

cent

95% < 400 Kbps

Non-persistent TCP connections

Small HTTP transfer size

Non-negligible RTTs

TCP slow start effects

12

MAC-level & Error Analysis

MAC-level Retransmissions3% of the packets40% of the connectionsmost retry attempts for a packet: 6

CRC Errors

0.04% of the packets

TCP-level Retransmissions

0.2% of the packets12 TCP connections2 connection have > 3 packet loss

HTTP-level Errors

Unsuccessful: 1%Successful: 96.74%Aborted: 2.26%

Wireless channel quality does not have a major impact on wireless Web browsing performance

13

Summary (1 of 2)

FactsFacts ImplicationsImplications

Network RTT dominates the response latency

Caching per-destination state information (e.g., RTT, cwnd) might be effective

Web objects are typically smallWeb proxy caching of content from wireless portals could reduce network latency

Largest web objects transferred were executables

Software providers should compress executable files into more compact file formats

Even though free, the least prevalent graphics file type on the web is PNG

Increase support for PNG file type across web browsers

14

FactsFacts ImplicationsImplications87% were non-persistent and 65% of HTTP transfers occurred on persistent connections

Wireless Web browsing would be faster if persistent connections were used for all Web sites

Some TCP connections lasted longer than 300 seconds

Persistent connection timeout should be tightly set

52% of the TCP packets were transmitted by the client PDA

Some form of ACK consolidation in Windows CE would economize on wireless network usage and battery power for wireless device

MAC: 3% of the packetsCRC: 0.04% of the packetsTCP: 0.2% of the packetsHTTP: 1% of the connections

Wireless channel quality does not have a major impact on wireless Web browsing performance

Summary (2 of 2)

15

Future Work

Expand the work to a large scale traffic measurement

Study the effect of interference and range overlapping among closely located APs

16

References

M. Arlitt and C. Williamson, “Internet Web Servers: Workload Characterization and Performance Implications”, IEEE/ACM Transactions on Networking, Vol. 5, No. 5, pp. 631-645, October 1997.

P. Barford, A. Bestavros, A. Bradley, and M. Crovella, “Changes in Web Client Access Patterns”, World Wide Web Journal, 1999.

D. Kotz and K. Essien, “Analysis of a Campus-Wide Wireless Network”, Proceedings of ACM MOBICOM, Atlanta, GA, pp. 107-118, September 2002.

D. Tang and M. Baker, “Analysis of a Metropolitan-Area Wireless Network”, Proceedings of ACM MOBICOM, Seattle, WA, pp. 13-23, August 1999.

D. Tang and M. Baker, “Analysis of a Local-Area Wireless Network”, Proceedings of ACM MOBICOM, Boston, MA, pp. 1-10, August 2000.

A. Wolman, G. Voelker, N. Sharma, N. Cardwell, A. Karlin, and H. Levy, “On the Scale and Performance of Cooperative Web Proxy Caching”, Proceedings of ACM SOSP, December 1999.

17

Thank You!

?