MODEL

DRIVEN DEVELOPMENT OF CONTEXT-AWARE MOBILE

APPLICATIONS

An Architecture and a Metamodel

Saber Lajili

ISET, Gafsa and ISIG, Kairouan, Tunisia

Slimane Hammoudi, Olivier Camp

ESEO, 4 rue Merlet de la Boulaye, Angers, France

Mohamed Mohsen Gammoudi

ESSAIT, Universit

e 7 novembre, Tunisia

Keywords:

MDD, Context-awareness, Metamodeling, Transformation.

Abstract:

The development of context-aware application has been the subject of many research works in ubiquitous com-

puting. Nowadays, there is a lack of generic approaches for formalizing the activity of development for this

type of applications, and consequently this activity is very cumbersome and time consuming. This work pro-

poses to use Model Driven Development to promote reuse, adaptability and interoperability in the development

of context-aware applications. Through the separation of concerns in individual models and transformation

techniques, context can be modeled and adapted independently of business logic and platform details. This

paper presents an architecture and a metamodel for model driven development of context-aware applications.

The architecture illustrates the different steps and techniques involved in the process of development. The

metamodel provides a formal representation of contextual information.

1 INTRODUCTION

As envisioned by Weiser in (Weiser, 1991), pervasive

computing, where computers are everywhere and a

person interacts with portable devices that are sen-

sitive and responsive to him, has become a reality

nowadays. In contrast to the more traditional desktop-

based computing paradigm, pervasive computing is

characterized by constant changes in the environment,

often caused by the mobility of the users. In the scope

of pervasive computing, a class of applications that

has raised increasing interest in the research commu-

nity is context-aware mobile applications. These ap-

plications can capture dynamically and take advan-

tage of contextual information (such as user loca-

tion, time, weather, device or user activities). Thus,

context-aware applications can sense their context of

use, and adapt their behaviour accordingly. From an

implementation point of view, the emerging technol-

ogy of web services seems promising for such mobile

applications in pervasive environments.

In this paper, we focus on context-aware services.

This means, services which use the context to carry

out activities and provide relevant information to the

user without any human interaction from his part. To

develop context-aware services, the following three

main issues need to be considered:

• Context identiﬁcation;

• Context provisioning;

• Context-awareness mechanism.

The ﬁrst issue is to identify what kind of context

information will be used. This will allow for the deﬁ-

nition of a model describing the contextual domain in

which the application or service is deﬁned. A number

of context models have been proposed in the litera-

ture, and have been reviewed in (Strang and Linnhoff-

Popien, 2004).

The second issue of provisioning concerns the

derivation of context information. Due to heterogene-

ity of context providers, sensor imperfection, quality

of context information, and dynamic context environ-

Lajili S., Hammoudi S., Camp O. and Gammoudi M. (2009).

MODEL DRIVEN DEVELOPMENT OF CONTEXT-AWARE MOBILE APPLICATIONS - An Architecture and a Metamodel.

In Proceedings of the 4th International Conference on Software and Data Technologies, pages 43-52

DOI: 10.5220/0002254200430052

 SciTePress

ments, context provisioning is not trivial (de Farias

et al., 2007a).

The third issue deals with the mechanisms that can

be used by context-aware services in order to adapt

automatically their behaviors according to context in-

formation.

In this paper, we concentrate on the ﬁrst of these

three issues i.e.; the identiﬁcation of context informa-

tion. A majority of existing context aware service ori-

ented applications model and implement both, busi-

ness and contextual activities together. This design

practice hampers software reuse and context manage-

ment. Motivated by this problem we propose to ap-

ply Model Driven Development (MDD) in context-

aware services development. The Object Manage-

ment Group (OMG) recommends the Model Driven

Architecture (MDA) approach as a standard in Model

Driven Development and considers models as the best

way to represent the structure and the semantic of the

concepts manipulated by a system. Through the sep-

aration of concerns (business and context), the reuse,

adaptability and management of context information

can be improved. Context models can be built as in-

dependent pieces of application models at different

abstraction levels that are then attached by suitable

transformation techniques.

The remaining of this article is structured as fol-

lows: section 2 presents the concepts of context and

context-aware applications; section 3 introduces the

Model Driven Development approach; section 4 de-

scribes our proposed modeling architecture using the

MDA approach to develop context-aware mobile ap-

plications; in section 5 we lay out the most recent re-

searches on context modelling; we then present and

give a detailed description of our context metamodel;

ﬁnally we conclude our work in section 6.

2 THE CONCEPTS OF CONTEXT

AND CONTEXT-AWARE

APPLICATIONS

New technologies, in particular, wireless communi-

cations, together with the increasing use of portable

devices (smart phones, personal digital assistants -

PDA-, laptop . . . ) have stimulated the emergence

of a new computing paradigm: pervasive computing.

In fact, we have moved from the desktop comput-

ing paradigm to the mobile and ubiquitous computing

paradigm.

Pervasive computing ﬁrstly introduced in 1991 by

Weiser, refers to the seamless integration of devices

into the users’ everyday life. ”Appliances should dis-

appear into the background to make the user and his

tasks the central focus rather than computing devices

and technical issues.”(Weiser, 1991). Computing ap-

plications now operate in a variety of new settings;

for example, embedded in cars or wearable devices.

They use information about their context to respond

and adapt to changes in the computing environment.

They are, in short, increasingly context aware. The

context awareness of such applications is the subject

of a recent ﬁeld of studies in pervasive computing:

context-aware systems.

This terminology was discussed in (Schilit and

Theimer, 1994) and presented as ”software that adapts

according to its location of use, the collection of

nearby people and objects, as well as changes to those

objects over time”. Since then, there have been nu-

merous attempts to deﬁne context-aware computing.

In (Pascoe, 1998) they deﬁne context-awareness

as the ability of a program or device to sense or cap-

ture various states of its environment and itself. Con-

sidering these deﬁnitions, a context-aware applica-

tion must have the ability to capture the necessary

contextual entities from its environment, use them to

adapt its behavior (run time environment) and ﬁnally

present available services to the user. In this sense and

to describe context-awareness independently from ap-

plication, function, or interface, (Pascoe, 1998) pro-

poses four features of context-aware applications :

(1) Contextual sensing which refers to the detection

of environmental states and their presentation to the

user; (2) Contextual adaptation refers to the adapta-

tion of the application’s behavior to the current con-

text; (3) Contextual resource discovery is the use of

context data to discover other resources within the

same context; (4) Contextual augmentation in which

the environment is augmented with digital data asso-

ciated to a particular context.

In (Dey and Abowd, 1999), the authors intro-

duce another deﬁnition in which they insist on the

use of context and the relevance of context informa-

tion. The authors consider that ”a system is context-

aware if it uses context to provide relevant informa-

tion and/or services to the user, where relevance de-

pends on the users task”. They explain how to use

context and propose a classiﬁcation of the features

of context-aware applications that combine the ideas

of (Schilit and Theimer, 1994) and (Pascoe, 1998).

They consequently deﬁne three categories of features

that context-aware applications may support: (1) pre-

sentation of information and services to the user; (2)

automatic execution of a service; and (3) tagging of

context to information for later retrieval.

In order to describe how an application can

be context aware, a lot of works are described in

ICSOFT 2009 - 4th International Conference on Software and Data Technologies

(Matthias et al., 2007) and propose various architec-

tures for context-aware systems. All the works con-

verge to a general architecture composed of ﬁve or-

dered layers presented in ﬁgure 1. The complete de-

scription of every layer is given in (Matthias et al.,

2007).

Application

Storage/Management

Preprocessing

Raw Data Retrieval

Sensors

Figure 1: Architecture of context-aware systems.

What is understood by ”context information” in

context-aware systems and what could be the deﬁni-

tion of context have been the subjects of many recent

works. The various deﬁnitions of the term are given

and summarized in (Mary and Patrick, 2005). The

ﬁrst deﬁnitions deﬁne speciﬁc contexts for speciﬁc

applications by enumerating concrete contextual en-

tities (Brown et al., 1997; Ryan et al., 1997). For

example the authors in (Brown et al., 1997) deﬁne

context as being information about location, the iden-

tity of people in close proximity, physical conditions.

In (Ryan et al., 1997), the authors add to this deﬁ-

nition the notion of time. Other deﬁnitions are ex-

tremely broad; the most popular one is given by (Dey

and Abowd, 1999): ”Context is any information that

can be used to characterize the situation of an entity.

An entity is a person, place, or object that is consid-

ered relevant to the interaction between a user and an

application, including the user and applications them-

selves”. The authors give a general deﬁnition that can

be used in a wide range of context-aware applications.

To reﬁne their deﬁnition, they identify four categories

of context that they feel are more practically impor-

tant than others. These are location, identity (user),

activity (state) and time (Dey, 2001).

In (Winograd, 2001) the author approves this def-

inition and claims that it covers all proposed works in

context. However he considers it as a general deﬁni-

tion that does not limit a context. Thus he proposes

his own deﬁnition in which he limits a context to ”a

set of information, which is structured and shared. It

evolves and is used for interpretation”. We stress that

the notion of hierarchy (structure) of context intro-

duced by (Winograd, 2001) is important.

The deﬁnition proposed in (Chen and Kotz, 2000)

also presents the context as hierarchically organized.

In this work the authors differentiate between envi-

ronmental information that determines the behavior

of mobile applications and that which is relevant to

the application. They thus deﬁne the context as ”the

set of environmental states and settings that either de-

termines an application’s behavior or in which an ap-

plication event occurs and is interesting to the user”.

As we have said previously, it is difﬁcult to give

a complete deﬁnition for a context. In fact, as stated

in (Mary and Patrick, 2005), the notion of context is

not universal but relative to some situation and appli-

cation domain. We are interested, in our research, in

user centred mobile application. Thus, we consider

that the deﬁning context here is a set of information

structured in three dimensions:

Actor. A person which is a central entity in our sys-

tem.

Environment. In which the person evolves and,

Computational Devices. Which are used by a per-

son to invoke services and that captures the differ-

ent states of the environment.

All the information relative to the three dimensions

can also be shared by other mobile applications.

3 MODEL DRIVEN

ARCHITECTURE (MDA)

At the beginning of this century, software engineering

needed to handle software systems that were becom-

ing larger and increasingly complex. Object-oriented

and component technology were insufﬁcient to pro-

vide satisfactory solutions to support the development

and maintenance of these systems. In order to adapt

to this new context, software engineering has applied

an old paradigm, i.e. models, but with a new ap-

proach, i.e. Model Driven Development. In this

new global trend called Model Driven Development,

Model Driven Architecture MDA is a particular vari-

ant.

3.1 MDA: A Four Layer Architecture

MDA is based on standards from the OMG; it

proposes a four layer architecture (OMG, 2001):

metametamodel, metamodel, model and information

(i.e. an implementation of its model).

Figure 2 presents the basic Metamodeling archi-

tecture of MDA and shows the relationships between

the different levels of the models. In this approach,

everything is a model or a model element.

In level M0, a real system is representedBy a

model in level M1, and a model in level M1 conform-

sTo a metamodel in level M2. These two important re-

lationships of MDA are discussed in (B

ezivin, 2005):

MODEL DRIVEN DEVELOPMENT OF CONTEXT-AWARE MOBILE APPLICATIONS - An Architecture and a

Metamodel

MOF MMM

UML MM CWMJava

Another UML

model m2

A UML

model m1

Another particular

use of m1

A particular

use of m1

Self described

conformsTo

representedBy

Figure 2: The four meta-layers MDA architecture.

In level M3, a metametamodel is a well-formed spec-

iﬁcation for creating metamodels such as the Meta

Object Facility (MOF), a standard from the OMG. In

level M2, a metamodel is a well-formed speciﬁcation

for creating models.

In level M1, a model is a well-formed speciﬁca-

tion for creating software artefacts. In level M0, an

operational example of a model is the ﬁnal represen-

tation of a software system. Besides the four layer

MDA architecture, the development is based on the

separation of concerns (e.g. business and technical

concerns), which are later recombined. Business con-

cerns are represented using the Platform-Independent

Model (PIM), whereas technical concerns are repre-

sented using the Platform-Speciﬁc Model (PSM).

3.2 Model Transformation in MDA

It is well recognized nowadays that model transfor-

mation is one of the most important operations in

MDA. In the context of the basic four level Meta-

modeling architecture of MDA, various scenarios of

model-to-model transformation have been identiﬁed.

To transform a given model into another model, trans-

formation rules map a source metamodel into the cor-

responding target metamodel. The transformation

rules are based on a transformation language, such as

the standard QVT and are executed by a transforma-

tion engine to produce the target model as output.

4 MDD ARCHITECTURE FOR

CONTEXT-AWARE

APPLICATIONS

Figure 3 illustrates our proposal of an architecture for

model driven development of context-aware applica-

tions. In section 2, our studies on context representa-

tion have conducted us to the conclusion that the most

promising assets for context modeling for ubiquitous

computing environments and context-aware applica-

tions in particular can be found in the ontology for-

malism.

MDA and its four-layer architecture, presented

in section 3, has provided a solid basis for deﬁning

metamodels for any modeling language, so it was a

straight choice to deﬁne an ontology-modeling lan-

guage using MOF. The Ontology Deﬁnition Meta-

model (ODM) was recently adopted as a standard by

the Object Management Group (OMG, 2006). It sup-

ports ontology development and conceptual model-

ing in several standard representation languages. fur-

thermore, it provides a coherent framework for vi-

sual ontology creation based on MOF and UML. The

main goal of ODM is to bridge the gap between tra-

ditional software tools for modeling (like UML) and

artiﬁcial intelligence techniques (Description Logics)

for describing ontologies. The principle of ODM is

to merge Model Driven Architecture and Semantic

Web. Basically, ODM allows creating ontologies us-

ing UML and transforming them to OWL/RDF, Topic

Map or Common Logic. Thus, in our architecture the

speciﬁcation of metamodels (layer M2) involves two

formalisms: UML for the deﬁnition of the business

logic of a given application (PIM Metamodel).

This deﬁnition occurs at the highest level of ab-

straction. The second formalism is ODM from which

we deﬁne a metamodel for context information using

the ontology language RDF. Our metamodel of con-

text information (Ctxt metamodel) groups the main

entities and their relationships, found in Context-

Aware Mobile Applications. Three types of relation-

ships are involved in our architecture. The conform-

sTo relationship represented by ﬁlled arrow and which

link a model from layer M1 to its metamodel at layer

M2, and a metamodel from layer M2 to a general

and unique MOF formalism at layer M3. The de-

scribedBy relationship represented by the dotted ar-

row and which speciﬁes the formalism in which a

given metamodel is described: UML for the PIM

metamodel and ODM for the context metamodel. Fi-

nally, hollow arrows reference models that are either

used (input) or produced (output) by a transformation

process.

The separation of concerns (business and context)

ICSOFT 2009 - 4th International Conference on Software and Data Technologies

is emphasized at layer M1 of our architecture where

PIM and context models are deﬁned independently,

then merged by suitable transformation techniques.

Two types of transformations are involved in our pro-

posal. The ﬁrst type of transformation called ”Pa-

rameterized transformation” represented by ovals, al-

lows merging context information with business logic

at model level. This type of transformation, which

has been investigated recently (Vale and Hammoudi,

2008), is rarely explored and has no standard transfor-

mation language. A CPIM model (Contextual Plat-

form Independent Model) is then obtained and ﬁts

together business requirements with contextual data.

The second type of transformation is the traditional

transformation technique using a language such as

QVT, which maps a CPIM model into a CPSM model

(contextual platform speciﬁc model). As our main ap-

plication domain concerns mobile applications, Web

service platforms seem the most adapted.

Parameterized transformations have been intro-

duced by Frankel (Frankel, 2003), who mentions the

importance of parameterization in model operations

using the association of tagged values with PIM and

PSM models. Tagging model elements allows the

model language to easily ﬁlter out some speciﬁc el-

ements. Transformation by parameter could be used

to improve new functionalities or to change the appli-

cation’s behavior (activities).

In our proposal, the designer has to mark, in the

Metametamodel(MOF)

UML (MM)

ODM (MM)

PIM (MM)

Ctxt(MM)

PIM Model

Context Model

CPIM Model

CPSM

Web Service

Transfo

Model

QVT

in out

M3 Layer

M2 Layer

M1 Layer

CW service mngt

repository

runtime

repository

XML

M0 Layer

out

Figure 3: The model driven development architecture.

application model (PIM), the elements that will re-

ceive the context information (a mark, identiﬁed by

the symbol #, is given for these elements to be rec-

ognized by the transformation engine). The marked

elements represent context-aware elements, in others

words, the model elements that can be contextualized.

The transformation language must thus support such

parameterization. In our case the parameters can be a

Context Property and/or a Context Data Type. We use

templates to specify which elements in the applica-

tion model are potentially context-aware ; This is pre-

sented and discussed in (Vale and Hammoudi, 2008).

The transformation engine has to navigate through the

PIM verifying the parameters and the elements that

are marked and then carry out the transformation.

Template parameters (Frankel, 2003) are used to

specify how classiﬁers, packages and operations can

be parameterized. UML 2.0 states that any model el-

ement can be templateable. For independent context-

aware models we need to identify context elements

that could be used as parameters. Such elements

would then be exposed as formal parameters for tem-

plate transformations and speciﬁed as actual parame-

ters when binding the template (Vale and Hammoudi,

2008).

5 CONTEXT MODELING

To deﬁne and store context data in machine process-

able forms, it is necessary to deﬁne and build a con-

text model. The number of new mobile applications

that take care of context is growing every year. Thus

the task of modeling and designing context seems rel-

evant and constitutes a challenge for researchers. This

section investigates a number of context models de-

scribed in the literature for context-aware mobile ap-

plications, and proposes a context metamodel based

on the main concepts found on these models.

5.1 Related Work

In the earlier stage of the research, many works fo-

cused on building a very speciﬁc context aware ap-

plication such as the Active Badge Location System

(Want et al., 1992). Some of them proposed location

centered models (Schilit, 1995). These metamodels

are very limited and the applications are very spe-

ciﬁc. In (Henricksen et al., 2002), the authors pro-

posed models that take care of some contextual en-

tities like place, person, temperature, devices, etc..

These models have been proposed in their own graph-

ical language ORM. As a consequence, it is impossi-

ble to exchange model and context information due to

MODEL DRIVEN DEVELOPMENT OF CONTEXT-AWARE MOBILE APPLICATIONS - An Architecture and a

Metamodel

the lack of uniform metamodel.

Recent researches beneﬁt from the standard tools

in particular UML/MOF and ontology tools in or-

der to build a uniform infrastructure and to facili-

tate the use and the exchange of models. As a re-

sult, some works focus on deﬁning metamodels to

design speciﬁc kinds of applications. These works

limit the scope of the context information that is con-

sidered. However, they take care of the natural di-

versity of context information. Most of them use an

ontology based approach. The relevant works based

on such an ontology based approach are summarized

in (Strang and Linnhoff-Popien, 2004) and presented

in more details in (Matthias et al., 2007). Other re-

cent researches (de Farias et al., 2007b; Sheng and

Benatallah, 2005) propose a high abstract level meta-

model based on UML/MOF standards. These works,

aim at deﬁning and building a uniform infrastructure.

However, literature often considers UML as a limited

language regarding its capacity to adequately capture

contextual information (de Farias et al., 2007b). In-

deed, UML is a general purpose modeling language,

whose semantics was never intended to accommodate

the speciﬁc features of ubiquitous applications. Con-

text modeling demands a more speciﬁc metamodel.

In what follows, we present and discuss the two main

approaches for context modeling: UML/MOF and on-

tology, and we ﬁnally give our point of view.

5.2 UML/MOF Approach

Some recent works based on the UML/MOF approach

have been proposed to model a mobile context-aware

application and mobile services. These applications

must react to the constant changes in context within

a dynamic environment. Following this approach, the

authors in (Sheng and Benatallah, 2005), propose a

high abstract level metamodel in which a metamodel

named ContextUML is dedicated to context-aware

web services. On the one hand, they present a lan-

guage to model the context for mobile applications;

on the other hand, they propose a mechanism to adapt

the selected services to the necessary context infor-

mation available. The proposed context metamodel

consists of two main classes the Context and the Con-

textSource classes. The ﬁrst models the context infor-

mation, and is further specialized by two sub classes

AtomicContext and CompositeContext, whereas the

second class, ContextSource, models the resource

from which the contexts are retrieved. It is also spe-

cialized in two sub classes ContextService and Con-

textServiceCommunity. This metamodel does not re-

ﬁne contextual information. So, it is hard to identify

contextual entities. Another recent work is presented

in (de Farias et al., 2007b); It proposes a MOF-based

contextual information metamodel, more expressive

than ContextUML. In addition the MOF metamodel

takes the dynamics of the context into account by

adding the notion of time. To best match contextual

information with the selected service, they deﬁne an

environment composed of ﬁve views; amongst them

the metamodel service view and a context metamodel

core view (de Farias et al., 2007b).

5.3 Ontology-based Approach

Modeling context using an ontology-based approach

allows describing contexts semantically and provides

a vocabulary for representing knowledge about a do-

main. In addition ontologies are very suitable and ap-

plicable to model a speciﬁc-domain. Thus a lot of ef-

forts on modeling context based ontologies have been

proposed. The majority of them are oriented to de-

scribe the context of speciﬁc context-aware applica-

tions like smart homes, virtual guide tours, smart as-

sistants, etc.

In 2003, a promising emerging context modeling

approach, based on ontologies, was proposed for the

CoBrA system (Chen et al., 2003). This system pro-

vides a set of ontological concepts to characterize en-

tities such as persons, places, intentions or several

other kinds of objects within their contexts.

In 2005, in (Gu et al., 2005), the authors propose

a metamodel to describe a smart home environment.

They deﬁne a hierarchical context ontology in which

two layers are distinguished: 1) Common upper on-

tology in which the basic concepts are deﬁned such

(e.g.; A person, location, computational entities, ac-

tivity, etc). 2) The domain-speciﬁc ontology in which

the details of basic concepts are deﬁned and their

properties (eg: person have properties name, role, sta-

tus, etc.).

Other works, proposing a high level context meta-

model, are presented in (Capiello et al., 2005). The

authors focus on modeling a general domain which

covers a large type of user centered applications. For

example applications related to the tourism domain

such as virtual traveler’s guide, hotel guides, etc..

They deﬁne a top ontology that speciﬁes the generic

contextual entities and a speciﬁc ontology which de-

ﬁnes subclasses of the basic element that are deﬁned

previously in the top ontology. The deﬁne a context

top ontology that is composed of many contextual en-

tities such as the user proﬁle, the environment and the

channel. The user proﬁle describes the properties as-

sociated with the user. The environment consists of

location, the ambient condition, the time, etc. Finally

the channel describes the element that characterizes

ICSOFT 2009 - 4th International Conference on Software and Data Technologies

the interaction of the users with the platform used to

access services. It includes a device, a network etc..

As an example of speciﬁc ontology, a basic concept

location specialized in three subclasses: political ge-

ography, physical geography and architectural posi-

tion. The political geography is a street, city, country,

state or country. This metamodel uses only two types

of relation: aggregation (part of ) and inheritance (is

a).

The ontology based approaches are characterized

by: (1) Simplicity of use; (2)Flexibility and extensi-

bility by appending a new context elements; (3) Pos-

sibility to have a hierarchical context ontology; (4)

Expressiveness to describe as many context states as

possible. (5) Genericity so as not to be limited to spe-

cial kinds of context atoms but to allow the deﬁnition

of generic context classes that can then be specialized

by subclasses.

5.4 ODM: A Good Compromise

Although some approaches, e.g. (Sheng and Be-

natallah, 2005) or (de Farias et al., 2007b) advo-

cate a rather generic knowledge of context-awareness,

nowadays no single approach for modeling context

provides for all relevant contexts in the necessary de-

tail. The main objective of the ODM is to bridge the

gap between traditional software tools for modeling

(like UML) and artiﬁcial intelligence techniques (De-

scription Logics) for describing ontologies. The prin-

ciple of ODM is to merge two main domains of re-

search: namely, Model Driven Development and Se-

mantic Web. Basically, ODM allows the description

of ontologies using UML (by using a UML proﬁle

with existing tools like Rational Rose or Poseidon)

and transforming it to OWL/RDF.

5.5 Our Metamodel

As we said above, we are interested in modeling a

broad spectrum of user centered context aware mobile

applications and thus, have designed a high level con-

text metamodel from which various models can easily

be instantiated to describe their own speciﬁc context

information.

Figure 4 presents our context metamodel which

illustrates the most important and generic contextual

entities. By contrast to the other works discussed in

section 4, our work does not focus on proposing nei-

ther, a low level context metamodel for very speciﬁc

context aware applications for example smart home

(Gu et al., 2005). Indeed such a choice does not pro-

vide a reusable metamodel. Nor does it attempt to

deﬁne a high level and very abstract metamodel for

the design of mobile applications (de Farias et al.,

2007b). In (Sheng and Benatallah, 2005), the au-

thors propose an original approach for modeling con-

text aware mobile applications. Their metamodel for

context information is centered on the Context entity

that represents generic contextual information. This

model does not represent the main contextual entities

that should be considered in a given mobile context-

aware application. In (Broll et al., 2007), the authors

present a similar context metamodel and illustrate its

use in the development of a mobile application that

helps a user ﬁnding a restaurant. Also, they introduce

the notions of atomic and composite context. How-

ever, the entities in the metamodel are in our opinion

not described with a sufﬁcient level of detail, and are

thus poor semantically.

In this study, we propose a solution to these short-

comings and adopt a UML/ODM/MOF approach to

express our vision. Using such an approach it is possi-

ble to create a high level metamodel and beneﬁt from

all the advantages of the object, model and ontology

based approaches. Our context metamodel appears

both generic and rich semantically; It identiﬁes and

adds the most relevant and generic contextual entities

that can be encountered when modeling any mobile

and context aware application.

This context metamodel consists of six generic

classes and three generic contextual entities. It en-

riches semantically the Context and Contextual Entity

classes by adding speciﬁc attributes and associations.

The Context class models context information, it is

identiﬁed by a name and has two types of relation: the

aggregation includes and the association uses. The

ﬁrst relation expresses that a Context is composed

of many Context Entity. It illustrates the low level

composite context (e.g: a composite context informa-

tion ”proﬁle” is composed of three atomic contexts:

”name”, ”sex”, ”date of birth”). The second relation

uses expresses the possibility of using other contex-

tual information to specify a context; this could for

instance be past context information encountered by

the application. This allows to derive new context in-

formation from other contexts (e.g: the user favourite

food deduced from the user previous preferences).

Furthermore, atomic context information is elemen-

tary context information that is acquired from one

source (e.g: sensor, database . . . ). On the opposite, a

composite context is an interpretation of various other

context informations. It comprises and relates to var-

ious pieces of context information whose combina-

tion has a meaning of its own. Composite context in-

formation consists of multiple atomic and/or compos-

ite context information (Sheng and Benatallah, 2005).

The second generic entity of the metamodel is the

MODEL DRIVEN DEVELOPMENT OF CONTEXT-AWARE MOBILE APPLICATIONS - An Architecture and a

Metamodel

Context

+name: string

Context_Entity

+id: string

+type: string

+source: string

+timestamp: time

Computational_Device

Actor

+state: string

Environment

Profile

+id: int

includes

1..*

0..*

has

0..*

0..1

uses

0..1

1..*

uses

0..*

1..*

captures

0..*

Figure 4: Our context metamodel.

Context Entity. It is enriched semantically by three

attributes:

• The Source. From which the context informa-

tion is captured. We characterize four main

sources: Sensors, actors (users), user applications

and derivation from other context information.

According to these sources, we classify context

informations into three types: (Henricksen et al.,

2002):

– Sensed. Information obtained from hardware

sensors (e.g: user location coordinates cap-

tured from GPS sensor) or software sensors (eg:

the weather information obtained from Internet

servers)

– Deduced. Information obtained from one or

more other context information using inference

functions or rules. (e.g accordingly to user lo-

cation coordinates, the user can be located near

or far the selected restaurant)

– Proﬁled. Information supplied directly by the

users (eg: user proﬁles sush as preferences,

constraints) or indirectly through users applica-

tions (e.g: software that maintains a history of

user preferences)

• Timestamp. To indicate the dynamics of context

information

Further, Context Entity is specialized by three

main classes: Actor, Environment and Computa-

tional Device.

Actor. It can be a person or another object that has a

state and proﬁle. It evolves in an environment and

uses computational devices to invoke services.

The state of an Actor can be ”moving” or ”ﬁxed”.

Computational Device. It is the mobile computing

system used by the actor to access the services and

capture contextual information from the environ-

ment. The computational device can obtain infor-

mation concerning the type of device it is (PDA,

laptop, cellular phone . . . ), the application, the

network, etc.

Environment. It is constituted of all information sur-

rounding the actor and its computational device

and, that can be relevant for the application. It

includes different categories of information:

ICSOFT 2009 - 4th International Conference on Software and Data Technologies

• Spatial context information can be location,

city, building . . .

• Temporal context information comprises time,

date, season . . .

• Climate can be temperature, type of weather . . .

The last entity is a proﬁle: it is important to mention

it here because this entity is capital in any user cen-

tered context aware application. In addition proﬁle

is strongly attached to the actor and contains the in-

formation that describes it. An actor can have both

a dynamic and/or a static proﬁle. In fact, the static

proﬁle gathers information relevant for any mobile

context-aware application. It can be the ”date of

birth”, ”name” or ”sex”. On the opposite, dynamic

proﬁle includes customized information depending on

the speciﬁc type of application and/or the actor. It can

be goals, preferences, intentions, desires, constraints,

etc. For example the goal of a tourist searching for

a restaurant is to have dinner. He has a pain in his

stomach as a constraint.

6 CONCLUSIONS

In this work we have investigated the issue of context

information modeling and have proposed an archi-

tecture for the development of context-aware mobile

applications according to a model driven approach.

Context-aware development has been an emergent

subject of many research works in ubiquitous com-

puting. However, few of them propose Model Driven

Development as an approach for context-aware ap-

plications. By the separation of concerns in individ-

ual models and by suitable transformation techniques,

context can be provided, modelled and adapted inde-

pendently of business logic and platform details. We

have proposed an architecture with three main objec-

tive:

• A separation between context information and

business logic in individual models;

• The integration of the context model into the

business logic using parameterized transforma-

tion techniques;

• The mapping of the contextualized business logic

model into a web service platform.

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