Multi-Layer Analysis of Web Browsing Performance for

Wireless PDAs

Multi-Layer Analysis of Web Browsing Performance for

Wireless PDAs

Adesola Omotayo & Carey WilliamsonAdesola Omotayo & Carey Williamson

April 18, 2023April 18, 2023

2

Presentation OutlinePresentation Outline

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

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

3

Introduction & MotivationIntroduction & 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

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 WorkRelated Work

Workload of clients at wireline networksClient-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 2000

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

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

Workload of clients at wireline networksClient-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 2000

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

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

5

Data Gathering & ValidationData Gathering & Validation

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

Over a period of 35 minutes

398 TCP connections1.8% with expected FIN handshake96.5% used the RST packet 1.7% unsuccessful connections

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

Over a period of 35 minutes

398 TCP connections1.8% 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 workloadA 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 AnalysisHTTP-level AnalysisServer Response TimeServer Response Time

distinct plateaus

consistent server response time

response times < 200 ms

distinct plateaus

consistent server response time

response times < 200 ms

Network RTT dominates the response latency

Cache per-destination state information

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-m

ecc

a

tucows

airsurfer

CNN

cpsc

tucows

akam

aifa

ntas

yspo

rts

fant

asys

port

s

cnet

akam

ai

cpsc

weather3

cpsc UofC

chutch

akam

aicn

et

cnet

0

0.05

0.1

0.15

0.2

0.25

0 50 100 150 200 250 300 350

Connection ID

Se

rve

r R

es

po

ns

e T

ime

in

se

co

nd

s

Server Response Time versus Connection ID

yahoo

fore

cast

erfo

reca

ster

hmdns

quickdrive

atlantic

tuco

ws

cpsc

i-m

ecc

a

tucows

airsurfer

CNN

cpsc

tucows

akam

aifa

ntas

yspo

rts

fant

asys

port

s

cnet

akam

ai

cpsc

weather3

cpsc UofC

chutch

akam

aicn

et

cnet

0

0.05

0.1

0.15

0.2

0.25

0 50 100 150 200 250 300 350

Connection ID

Se

rve

r R

es

po

ns

e T

ime

in

se

co

nd

s

7

HTTP-level AnalysisHTTP-level Analysis

Web Object SizesWeb Object Sizesobject sizes:

90% < 10 KB2.5% > 40 KB

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

largest objects transferred:executables

object 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

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

Fre

qu

ency

in

Per

cen

t

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

Fre

qu

ency

in

Per

cen

t

8

HTTP-level AnalysisHTTP-level Analysis

HTTP Transfer TimeHTTP 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

Tra

nsfe

r T

ime i

n S

eco

nd

s

Scatter 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

Tra

nsfe

r T

ime i

n S

eco

nd

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

larger objects take longer to download

few small objects have excessively long transfer times

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

HTTP transfer times are generally low

Most responses fit in a single TCP packet

9

TCP-level AnalysisTCP-level Analysis

TCP Connection TypeTCP Connection TypeNumber of HTTP Requests Per Connection

akam

ai

216.2

39.3

9.9

9216.2

39.3

9.9

9

akam

ai

adminUofCgoogle

akamaiquickdrive

CNN

0

10

20

30

40

50

60

70

80

0 51 102 152 204 254 304 355

Connection ID

Nu

mb

er

of

HT

TP

Req

uests

Number of HTTP Requests Per Connection

akam

ai

216.2

39.3

9.9

9216.2

39.3

9.9

9

akam

ai

adminUofCgoogle

akamaiquickdrive

CNN

0

10

20

30

40

50

60

70

80

0 51 102 152 204 254 304 355

Connection ID

Nu

mb

er

of

HT

TP

Req

uests

13% were persistent

87% were non-persistent

4% of TCP connections sent > 10 HTTP requests

65% of HTTP transfers occurred on persistent connections

As much as 73 HTTP requests were seen per connection

13% were persistent

87% were non-persistent

4% of TCP connections sent > 10 HTTP requests

65% of HTTP transfers occurred on persistent connections

As much as 73 HTTP requests were seen per connection

Use persistent connections for all web sitesUse persistent connections for all web sites

10

TCP-level AnalysisTCP-level Analysis

TCP Connection DurationTCP Connection Duration75% sent < 20 packets

6% sent > 100 packets

80% sent < 10 KB

8% sent > 50 KB

75% lasted < 1 second

10% lasted > 30 seconds

4 connections lasted > 300 sec.

75% sent < 20 packets

6% sent > 100 packets

80% sent < 10 KB

8% sent > 50 KB

75% lasted < 1 second

10% 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

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

Fre

qu

en

cy in

Perc

en

t

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

Fre

qu

en

cy in

Perc

en

t

11

TCP-level AnalysisTCP-level Analysis

TCP Connection ThroughputTCP 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

Fre

qu

ency

in

Per

cen

t

95% < 400 Kbps95% < 400 Kbps

Non-persistent TCP connections

Small HTTP transfer size

Non-negligible RTTs

TCP slow start effects

Non-persistent TCP connections

Small HTTP transfer size

Non-negligible RTTs

TCP slow start effects

12

MAC-level & Error AnalysisMAC-level & Error Analysis

MAC-level RetransmissionsMAC-level Retransmissions

3% of the packets

40% of the connections

most retry attempts for a packet: 6

3% of the packets

40% of the connections

most retry attempts for a packet: 6

CRC ErrorsCRC Errors

0.04% of the packets0.04% of the packets

TCP-level RetransmissionsTCP-level Retransmissions

0.2% of the packets

12 TCP connections

2 connection have > 3 packet loss

0.2% of the packets

12 TCP connections

2 connection have > 3 packet loss

HTTP-level ErrorsHTTP-level Errors

Unsuccessful: 1%

Successful: 96.74%

Aborted: 2.26%

Unsuccessful: 1%

Successful: 96.74%

Aborted: 2.26%

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

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

13

Summary (1 of 2)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)Summary (2 of 2)

15

Future WorkFuture Work

Expand the work to a large scale traffic measurement

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

Expand the work to a large scale traffic measurement

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

16

ReferencesReferences

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.

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!Thank You!

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