CLASSIFICATION AND MODELLING OF WEB TECHNOLOGIES

Mark Wallis, Frans Henskens and Michael Hannaford

Distributed Computing Research Group, School of Electrical Engineering and Computer Science

University of Newcastle, Callaghan, NSW, Australia

Keywords:

Web, Classiﬁcation, Model.

Abstract:

The World Wide Web is a constantly changing environment in which academia, industry and interest groups

participate to innovate and design the next evolution of online user interaction. The ad-hoc nature in which

new web-based systems and technologies have been developed has led to an increasingly diverse environment,

with ill deﬁned interactions and fuzzy classiﬁcation systems. Recently, business pioneers in the industry

have attempted to classify web applications into large groupings based on certain key characteristics. The

high-level taxonomy presented in this paper provides a way to scientiﬁcally classify web applications. By

classifying applications and studying the progression from one classiﬁcation to the next, predictions can be

made as to the direction of future web application development. After presenting a formal classiﬁcation model

this research discusses how this model can be used to compare existing web technologies and design the next

generation of the World Wide Web.

1 INTRODUCTION

The World Wide Web is a constantly changing en-

vironment in which academia, industry and interest

groups participate to design the next evolution of on-

line user interaction. The ad-hoc nature by which new

web-based systems and technologies have evolved

has led to an increasingly diverse environment with

ill deﬁned interactions and fuzzy classiﬁcation sys-

tems. Recently, business pioneers have attempted to

classify web applications into large groupings based

on certain key characteristics (O’Reilly, 2005). Var-

ious attempts have been made to ﬁrm up these clas-

siﬁcations (Hinchcliffe, 2005), but ultimately, they

have been critiqued as too high level and ill deﬁned

(Gilbertson, 2007).

This paper introduces a taxonomy based on the

connections between the various components in-

volved in a World Wide Web interaction. The taxon-

omy is then extended to address the next generation

of web technologies such as Cloud Computing (Boss

et al., 2007). The intent is that this system will be

extendable to cater for future evolution of the World

Wide Web model. The usefulness of such a taxon-

omy is apparent when making comparisons between

web technologies, and designing changes to how web

applications and users interact.

The paper begins with a review of the pre-existing

classiﬁcation systems and key web technologies. The

proposed taxonomy is then presented and critiqued.

Finally, future development concepts are discussed

with comparisons to the presented models.

2 BACKGROUND

Business has, for some time, been a key driver behind

the evolution of the World Wide Web (Cockburn and

Wilson, 1995). The concept of web ”generations” can

be traced back to 2005 where O’Reilly ﬁrst keyed the

phrase ”Web 2.0” (O’Reilly, 2005). At the time, Web

2.0 was identiﬁed as any web notion that matched the

following criteria:

• The application represents a service offering and

is not pre-packaged software.

• The application data evolves as the service is used

by the end users. This is in contrast to applica-

tions where static data is generated solely by the

application owner.

• A framework is provided that supports and en-

courages user submission of software enhance-

ments. These submissions are generally in the

form of plug-ins or extensions to the web appli-

cation.

• Evolution of the application is driven by the end

user as well as the application owner.

151

Wallis M., Henskens F. and Hannaford M..

CLASSIFICATION AND MODELLING OF WEB TECHNOLOGIES.

DOI: 10.5220/0003338801510156

In Proceedings of the 7th International Conference on Web Information Systems and Technologies (WEBIST-2011), pages 151-156

ISBN: 978-989-8425-51-5

 2011 SCITEPRESS (Science and Technology Publications, Lda.)

• The application interface supports interaction

from multiple client devices such as mobile

phones and PDAs.

• The application provides a lightweight, yet dy-

namic, user interface.

A deﬁnition of Web 2.0 is useless without a for-

mal deﬁnition of Web 1.0. Accordingly, Web 1.0 was

retrospectively speciﬁed as providing the same basic

Web Application characteristics, but that the applica-

tions and their data were largely static and not user

driven. The client to server interface was also stricter

in Web 1.0 (O’Reilly, 2005).

The more recent web application classiﬁcation

has been termed Web 3.0, or the ’semantic web’

(Wainewright, 2005). This model places greater fo-

cus on the following:

• Server to server communication technologies

such as Web Services.

• Applications that provide information as a ser-

vice. For example, an application that provides

currency exchange information via an API.

• Applications that aggregate information from

multiple sources and present it to the user in a

value-added fashion.

• Functionality provided by the web browser using

either local or remote stored components that are

provided and serviced by 3rd parties.

The deﬁnitions of Web 1.0, 2.0 and 3.0 have

grown out of attempts by business to classify ad-

vances in technology. These classiﬁcations have been

retroﬁtted to bracket convenient periods of that evo-

lution, and as a result the classiﬁcation of any indi-

vidual system rarely falls solely into a single group.

This is primarily due to the continuous nature of web

development. The classiﬁcation method presented in

this paper relies on feature selection and interactions

rather than on consideration of how to best provide

solutions to problems found in any current generation

of web application design.

2.1 Web Browsers

Web browser technology has been pivotal in the evo-

lution of the web, acting as the main interface be-

tween the user and published web applications. As the

web evolves, different expectations are placed on the

web browser to provide the functionality required to

support the various generations of web applications.

Web 2.0 saw a push to highly interactive web in-

terfaces. Web browsers have addressed these require-

ments with advances in Javascript (Flanagan, 2002)

and AJAX (Garrett, 2005). These technologies in-

troduced dynamic content to the user, but to date

have been viewed as sluggish and riddled with cross-

browser compatibility problems (King, 2003) (Yank,

2006). In fact, it is not uncommon that web develop-

ers give up attempting to support all the major web

browser platforms. Instead, developers force their

users to use a speciﬁc subset of web browsers for

which they have speciﬁcally catered.

Vision past Web 2.0 reveals a much greater fo-

cus placed on client-side processing. For example,

the concept of a ”Serviced client” is introduced by

Wainewright (Wainewright, 2005). Extensions to this,

introducing the concept that a web browser can take a

much greater responsibility in client to web applica-

tion interaction has also been further discussed in re-

cent publications (Henskens, 2007) (Paul et al., 2008).

2.2 Previous Analysis Work

There have been various attempts in documented re-

search to model the World Wide Web; these basically

fall into two categories.

Initial attempts focused on modelling the interac-

tions between network nodes on the Internet and how

they relate to each other using such tools as Power

Laws (Faloutsos et al., 1999). These laws model in-

teractions on the Internet as a whole, as opposed to

just focusing on web-based trafﬁc. Various projects

(Opte Group, 2008) (Dodge and Kitchin, 2000) have

built quite detailed maps of the Internet based on these

ideas.

Analysis has also been performed from the Soft-

ware Engineering perspective, focusing on how to de-

sign and model the internals of a web application.

These proposals tend to be based around extensions

(Conallen, 1999) to UML (OMG Working Group,

2007) and detail how to model the objects that inter-

nally make up a web application, along with limited

support for modelling service-level interactions.

Recent work in this ﬁeld has seen the creation of

the Web Science Research Initiative. Initial techni-

cal reports (Berners-Lee et al., 2007) suggest that this

group will focus on modelling the world wide web

using concepts deeply founded in the Sciences.

The work presented in this paper focuses on mod-

elling World Wide Web applications themselves by

concentrating on the interactions between the actors

involved in a World Wide Web transaction. By mod-

elling these actions we can determine where the cur-

rent issues in the model lie and design enhancements

to usher in the next generation of web application.

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3 TAXONOMY

The taxonomy proposed in this paper aims to charac-

terise web applications based on key functionality. To

make this possible, a model of actors, and the inter-

actions between these actors in the system has been

established. These interactions are represented by di-

rected graph edges labelled with the type of ﬂow be-

ing described. This model provides a scientiﬁc sys-

tem in contrast to that currently being proposed by

industry and, we believe, provides a powerful tool for

testing and proﬁling next generational enhancements

to the world wide web.

Figure 1: Web 1.0 model.

Figure 2: Web 2.0 model.

To build this model, the following key actors have

been identiﬁed;

• User - the end user who interacts with the web

browser to gain access to the information and ser-

vices provided by the World Wide Web.

• Web Browser - the software interface between the

user and the web application.

• Web Application - the software package, de-

ployed as a service offering and hosted on one or

more servers.

• Web Application owner - the entity that owns and

manages the web application.

• Web Service - a software package that provides

server-to-server APIs and services, generally as a

source of information which the web application

would transform and aggregate.

These actors can be used to represent any world

wide web transaction directly involving users and web

applications. In some cases, the way each actor is im-

plemented may change from deployment to deploy-

ment. For example, not every Web Application may

make use of Web services. Flows between these com-

ponents can be generalised as either requests for data,

or requests to create/alter data. The following will

now demonstrate the use of these actors and interac-

tions to formally deﬁne the Web 1.0, 2.0 and 3.0 con-

cepts.

Figure 3: Web 3.0 model.

The Web 1.0 model depicted in Figure 1 represents

a basic page/object request ﬂow with the data being

generated by the application owner. All of the data

processing is performed by the web application with

only basic web browser support required. The page

request ﬂow represents the user requesting a speciﬁc

URL from the web browser. The web browser in

turns discovers and connects to the web application,

making the request for the speciﬁed URL. The web

browser then continues to service the requests for the

various objects that form the original page requested

by the user. Data in the Web 1.0 model comes from

the application owner. Generally, this data is in the

form of static images and HTML content.

CLASSIFICATION AND MODELLING OF WEB TECHNOLOGIES

153

The Web 2.0 model in Figure 2 takes multiple

steps forward from the Web 1.0 model. On the client

side, multiple cross-browser platforms are supported,

with varying degrees of protocol support. There is

a much greater reliance on client-side processing to

create dynamic interfaces and reduce overall applica-

tion latency. Data can be created either by the ap-

plication owner, or by the users. For example, user

provided data is common-place in the popular social

networking sites that ﬁt this paradigm. Web browsers

can also be instructed to make additional data re-

quests independently of the user, allowing for real-

time data refreshes. This is commonly implemented

using AJAX technology and is a forerunner for web

browsers themselves being able to directly take part

in web services (Paul et al., 2008).

The Web 3.0 model depicted in Figure 3 takes the

next step forward by introducing Web Services and

API functionality to the back-end of the Web Applica-

tion. The front-end of the model, which represents the

user, the web browser, and its interaction with the web

application, stays unchanged from Web 2.0. There are

two sides to the web services enhancements to this

model.

• In Web 3.0 the web application can expose ser-

vices via an API or web service. This is repre-

sented in the model as the API request/response

ﬂows. An example is a 3rd party application mak-

ing requests to the modelled web application for

information on services.

• The web application itself is able to make out-

going requests to other 3rd party APIs and web

services. Depicted as the data request/response

ﬂows, this information is pushed through an ag-

gregator in the web application which can com-

bine the data from multiple 3rd party sources. The

combined data is often then represented, through

the web application to the user, to provide value-

added functionality. A classic example of such a

service is a news aggregation website which takes

multiple RSS (RSS Advisory Board, 2007) feeds

from different sources and aggregates them into a

single user interface.

To demonstrate further uses for this taxonomy we

can use this design to model how advances in Cloud

Computing affect the interactions between our actors.

Figure 4 shows the model applied to a cloud com-

puting design. Using a selection procedure and high-

lighting the external User and Web Browser actors we

can show that cloud computing poses no change in the

way that users themselves interact with the web. Ex-

periments show that latency though will be affected

due to the additional infrastructure elements of a stan-

dard infrastructure-as-a-service cloud computing de-

sign.

Figure 4: Cloud Computing model.

4 USING THE TAXONOMY

The usefulness of a taxonomy is based on the met-

rics that can be gathered through implementation of

the model in a data modelling package. Examples of

metrics that can be analysed using the presented de-

sign include, but are not limited to:

• Total number of messages passed between actors.

• Total bandwidth required between pairs of actors.

• Latency between request/response pairs.

• Load placed on each actor in the system.

While this data in a lone model might not provide

much value, it is when comparing the information be-

tween models that the usefulness of the presented tax-

onomy becomes apparent. As new logical require-

ments emerge in web development these models can

be used to compare various implementation styles and

technologies to see which produces the best set of re-

sults. The taxonomy can then be seen as a key tool

in the methodology of any future world wide web re-

search.

Take, for example, the evolution from Web 1.0 and

Web 2.0. One of the primary ﬂaws identiﬁed in Web

1.0 was that it relied on the web site owner to generate

content. Web 2.0 moved to a model where users them-

selves generated a signiﬁcant proportion of the con-

tent. Of course, generating the content means that the

upload bandwidth requirements between the User ac-

tor and the web application are greatly increased and

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154

Figure 5: Page refresh vs AJAX - bytes.

Figure 6: Page refresh vs AJAX - response time

the content itself is at risk during transit, especially if

the content is sensitive. Taking the Web 1.0 model

(Figure 1) and increasing the ﬂow requirements on

the graph edge between the Web Browser and Web

Application has ﬂow on effects to the other metrics

presented by the model. Correct use of this taxon-

omy at the cusp of the Web 1.0 to Web 2.0 evolution

would have highlighted the fact that the Web Browser

would be spending a signiﬁcantly larger portion of

time stalled, waiting for data uploads to complete.

Such problems would have been identiﬁed early and

rectiﬁed before the user-generated content concept

caught on. In fact, the solution to the large upload

issue most likely would have been taken from con-

cepts we are now seeing in Web 3.0, where the content

would have been uploaded, perhaps in a compressed

format, using a web service-based architecture. This

effectively would have freed up the web browser to

allow the user to continue using the application with-

out having to wait for their upload to complete. In the

end, proper use of such a taxonomy may have seen

the Internet skip Web 2.0 all together and move from

Web 1.0 to a hybrid 2.0/3.0 design.

Another example of the comparative nature of this

taxonomy can be seen when using it to compare tra-

ditional Web 1.0 page-refresh approaches with Web

2.0 AJAX techniques. In Web 1.0, if the web appli-

cation developer wanted to constantly update a page

with data automatically, then the only option was to

refresh the entire page. AJAX alternativly provides

the developer with a means of providing the updated

information via an XML stream that is processed be-

hind the scenes by a Javascript AJAX library. Figure

5 shows an experiment that compares the bytes trans-

ferred between a web browser and web application

over a period of 10 minutes with a 30 second refresh

rate. The ﬁrst series shows a traditional whole-page

refresh approach where each request/response pair is

the same size. The second series shows an AJAX ap-

proach where the initial response is much larger as

it incorporates the AJAX library itself, but all suse-

quent request/responses are much smaller due to the

CLASSIFICATION AND MODELLING OF WEB TECHNOLOGIES

155

XML stream. The results are shown as culmative

bytes transferred.

The same page refresh vs AJAX situation can be

measured from a latency point of view. By compar-

ing the message round-trip processing time at the ap-

plication server side of the model we can draw con-

clusions around how changes in the model can affect

CPU utilisation on the web server. Figure 6 shows

the difference in processing times for each HTTP re-

quest/response pair in the page-refresh and AJAX ex-

amples described above.

5 CONCLUSIONS

This research analysed the current state-of-play with

regard to the World Wide Web and the technolo-

gies it promotes. A review was presented of the

business-oriented classiﬁcation of web generations,

and how web browsers currently interact. A taxon-

omy was presented that supports further study of Web

1.0 through Web 3.0. This taxonomy provides a way

to compare and contrast web generations, supporting

technical modelling and analysis of past, current and

future generations. The taxonomy allows us to model

the interactions and analyse issues that need address-

ing in the current model, providing a way for future

web development projects to compare and contrast

different designs and technologies. Enhancements

presented in other concurrent research (Wallis et al.,

2010) will rely on this model to prove that changes

in interactions between actors will not adversly affect

the performance of the World Wide Web as a whole.

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