Model Driven Service-Oriented Approach
for Smart Building Energy Management
1
Ding-Yuan Cheng,
2
Nasaraf Shah,
3
Chen-Fang Tsai
2
Kuo-Ming Chao and
1
Chi-Chun Lo
1
Institute of Information Management, National Chiao-Tung University
300, Hsin-Chu, Taiwan
2
DSM Research Group, Department Computing and the Digital Environment
Coventry University Coventry, CV1 5FB, U.K.
3
Department of Industrial Management, Aletheia University, Taiwan, ROC
Abstract. This paper describes a new framework which is featured by integrat-
ing two well-known system modeling methods namely model driven approach
and service-oriented architecture to facilitate web service development and to
effectively satisfy a group of service consumers’ subjective requirements and
dynamic preferences. These models can be combined at different levels and
configured into heterogeneous structures to form various building blocks for
development of service-oriented applications. A case study is used to illustrate
how to systematically use our proposed framework to construct a smart service-
oriented environment system for effective energy management.
1 Introduction
Service-oriented computing has become an important trend in IT development. Espe-
cially, the recent convergence of ubiquitous computing and context-aware computing
in an attempt to integrate numerous types of sensors, heterogeneous communication
protocols, and programming languages to produce an effective and efficient solution
to the design of a distributed smart environment has seen as a considerable challenge.
A number of methods, frameworks and tools to design a smart environment using
service oriented approach have been proposed in the past [1][2][3]. In general, the
aim of these systems is to maximize users’ comfort level, and minimize the cost of
software design, code implementation, application installation, and system mainte-
nance. The communications and interactions among sensors, objects, and human
participants are inherently complex, as they involve different protocols and languages.
It can be viewed as configuration problem that requires various components to work
together in cooperative and coordinated manner in order to produce an optimised
environment to meet the system requirements. Service-Oriented Architecture (SOA),
which offers a way to take sensors, objects, participants as services, can provide an
effective approach to improve their communication and coordination, so the human
Cheng D., Shah N., Tsai C., Chao K. and Lo C.
Model Driven Service-Oriented Approach for Smart Building Energy Management.
DOI: 10.5220/0004465801160130
In Proceedings of the 4th International Workshop on Enterprise Systems and Technology (I-WEST 2010), pages 116-130
ISBN: 978-989-8425-44-7
Copyright
c
 2010 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved

participants can effectively interact with the system and offer their opinions and pref-
erences through a coherent technology.
A web service can be invoked and executed by a number of consumers simulta-
neously. Most service discovery and recommending systems recommend a list of
services according to the functional or non-functional requirements given by service
consumer. Thus, the service consumer can choose the best fit based on a set of criteria.
This kind of cases areis based on an assumption that is the cardinality between an
instance of service and a service consumer is built upon one to one relationship.
However, in some cases such as smart environment, an instance of a service needs to
serve a number of consumers. In other words, an instance of a service needs to meet
various requirements specified by different service consumers. It does not only satisfy
one consumer’s needs, but also of most consumers. It, however, can be very difficult
when conflicting requirements occur. In order to address the above issue, services
should be able to conduct self-adjusting and self-organizing to meet the requirements
or preferences given by most consumers along with changing environments.
Hence it is important that the design of service should consider the user prefer-
ences. The configuration or composition of services should also take the environ-
mental factors into account. So the system needs to adapt to environment changes by
adjusting or configuring its services dynamically in accordance with the data sent by
sensors. For example, the staffs in one office use a collection of the same devices or
functions provided by the system. Each function is intended as a service such as light
service, air condition service, heating service, and ventilation service, etc. Service
consumers could have different preferences or requirements on the services such as
room temperature. Some users may subjectively feel hot for the current room tem-
perature, but some may feel cool or comfortable. How to set the temperature for air
condition/heating service according to these consumers’ preferences can be a chal-
lenging issue. Existing research works in the context-aware system do not sufficiently
address this issue. To increase interoperability among these autonomous services is
required, so these services need to have well-defined interfaces and functions. The
context-aware system would encompass the capacities such as group consensus
reaching mechanism and service self-organizing mechanism to improve system
adaptability.
In this study, we design an intelligent context-aware service system based on Ser-
vice Component Architecture (SCA) and Model Driven Approach (MDA). It com-
bines these two methods to build a ubiquitous computing environment. The goal of
this framework or system is not only to effectively integrate sensors and services but
it also provides a systematic and adaptive approach to construct services in a dynamic
environment.
The remainder of the paper is organized as follows. In Section 2 the awareness
management process is outlined along with the basic notions required to model the
problem domain. Section 3 discusses a SOA platform. We identify the basic services
and briefly discuss the basic components of the platform. Then we present an exam-
ple to illustrate how smart service in an environment involving human users can be
used to capture and convey information. Finally we conclude the paper.
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2 Related Works
In this section, we review some existing studies and research work in relation to SOA
standards and middleware.
Although smart home and smart office concept have recently attracted a great at-
tentions from research community and industry in Europe and United States, a num-
ber of Smart Home projects within the past few years [4], [5], [6] have been carried
out. Also, AT&T Laboratories at Cambridge [7] built a dense network of location
sensors to maintain a location model shared between users and computing entities.
Microsoft’s EasyLiving [8] focuses on a smart space that is aware of users’ presence
and automatically adjusts environment settings to suit their needs. More recently,
Hewlett Packard’s CoolTown [9] provides physical entities with “Web presence” and
allows the users to navigate from the physical world to the Web virtual environment
by picking up links to Web resources using various sensing technologies. These
projects have provided great insight into smart building and environment, but we are
particularly interested in three different issues of these technologies, namely service
selection, consensus formulation method and service modeling.
2.1 Web Services
Many researchers have focused on approaches or methods on improving service
discovery protocols [10][11][12][13][14] to increase accuracy in service discovery
and selection. One of the most widely used protocols for publishing service is Uni-
versal Description, Discovery and Integration (UDDI) that includes service registry
with explicit specifications to enable service advertisement. In our previous studies on
the UDDI specification [15], we use the tModel to represent the QoS for web services
composition. After that, several researchers have designed the semantic query me-
chanism into UDDI registry, and mapping RDFS upper concepts to UDDI data model
to increase the precision in service selection such as [16] [17] [18].
Services can be classified into atomic or composite [19] services. An atomic ser-
vice is a basic unit which cannot be decomposed further. A composite service is made
of a collection of existing services which can be atomic or composite. Many research
works on service composition have used workflow-based approach, Artificial Intelli-
gence (AI) planning, and other modeling methodologies to compose services. In the
workflow-based composition methods, [20] proposed composite service definition
language (CSDL) to reform the flow. They used a static work flow generation in their
proposed platform. Some researchers presented Semantic Web Service composition
method based on Model-Driven Architecture (MDA) [20] [22], [23] [25], and UML
[21]. These composite services are specified using standard UML model to generate
specifications and to produce applications using MDA concepts.
2.2 Consensus Forming Methods
Decision making is one of the most complicated administrative processes in manage-
ment. In a decision-making process, decision makers may encounter multiple criteria
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for evaluation. Therefore, Multiple Criteria Decision Making (MCDM) is one of the
most well known branches in decision making. MCDM can be divided into two cate-
gories: MODM and MADM. A further discussion about MODM and MADM can be
found in Yoon and Hwang [26][27]. MADM has been widely used by decision mak-
ers in management processes to evaluate and rank possible alternatives.
In a decision making processes, a group of decision makers could be involved and
it is called Group Decision Making (GDM), so the all members’ options or prefe-
rences have to be considered. Most of the GDM problems have strategic dimensions
and can be complicated due to their multi-criteria framework involving many subjec-
tive and quantitative factors. Optimal utilization of the time and resources is a key
element sought by many GDM methods. Various researchers have focused their ef-
forts on increasing the ability of making quality group decisions[28, 29, 30, 31, 32,
33, 34, 35, 36, 37].
An effective web service discovery mechanism should be able to search and as-
sess services based on their QoS and service contents as well as users’ requirements.
The service assessment or selection often involves multi-criteria decision-making
process [38]. So, the GDM is applicable to service selection when the service con-
sumers have inconsistent or conflicting requirements, as it can be considered as a
reasoning process for reaching group consensus on their requirements for web service
selection.
2.3 Web Service Modeling Methodology
There are several ways to compose services at the design time. Model-driven Archi-
tecture (MDA) [39] is a software architecture framework proposed by the Object
Management Group (OMG). MDA consists of a set of standards that assist the system
in creation, implementation, evolution and deployment. The key technologies of
MDA are Unified Modelling Language (UML), Meta-Object Facility (MOF), XML
Meta-Data Interchange (XMI) and Common Warehouse Metamodel (CWM).
MDA emphasized the importance of modeling for the software architecture design.
MDA suggests a three-layered approach. The Computation Independent Model (CIM)
describes a system from the computation-independent point of view to address struc-
tural aspects of the system. The Platform Independent Model (PIM) defines a system
in terms of a technology-neutral virtual machine or a computational abstraction. The
Platform Specific Model (PSM) consists of a platform model that captures the tech-
nical platform concepts and a model geared towards the implementation technique.
The lifecycle of MDA development is shown as Fig. 1.
In [40], context-awareness is an essential aspect for service utilization, especially
when frequent interactions take place between users and environments. In this paper,
a solution for developing context-aware web services applications is proposed. The
methodology includes a model driven approach to separate the web application func-
tionality development from the context adaptation at the development phases (analy-
sis, design, and implementation). In essence, context adaptation takes place on top of
the web application business functionality to facilitate system evolution.
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Fig. 1. Lifecycle of MDA Developemnt.
3 Design Framework
Model-Driven Architecture (MDA) is a well-developed concept for software design
modeling and implementation. The meta-model plays an important role in MDA.
Also, Meta Object Facility (MOF) is the kernel of transformation between different
MOF layers. The Unify Modeling Language (UML) is the most widely used in soft-
ware engineering. The key task of UML modeling is to identify the class, attribute,
operation, and their relations. A class might inherit from another class. Moreover, a
class can also have many functions which are called operation or method. Therefore,
the design concept is not fully applicable to Service-Oriented applications because
services are loosely coupled operations or functions and there is no inheritance prop-
erty and internal facility to store states in services.
Hence, in this work, we proposed an agile SOA modeling methodology which
combines MDA and Service-Oriented modeling methods. The main goal is not only
to speed up the intelligent system development according to the SOA principles, but
also be able to identify group consensus on service’s QoS requirement and contents in
order to maximize their users’ satisfaction. In SOA, a required function can possibly
be satisfied by multiple services. Therefore, the process of service selection and dis-
covery needs to consider functional as well as non-functional (i.e QoS) requirements.
The characteristic of our proposed methodology allows the services to have ability of
self-adjustment in the process of composition in line with emerging requirements or
environment states.
3.1 Overview
There are four kinds of models in MDA. During initial phase, the business analyst
analyzes the user requirement in CIM. Next, the PIM based on the outcomes derived
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from the previous phase to define the functionalities, the structure, and the behavior
of a system. The PSM focuses more on implementation and execution platform
which could be a specific programming language or database.
In our propose framework, we distinguish two types of requirements which are
functional requirement and comfort requirement in initial phase. After analysis phase,
the users can use any tools or modeling language which they are familiar with to
model the ststem. Here, we adopt the service-oriented modeling framework (SMOF)
as a modeling framework. In PIM to PSM phases, we use Service Component Ar-
chitecture (SCA) as transforming methodology. Also in PSM phase, we use the
Service Data Object (SDO) to manipulate the connection between application and the
database. Our proposed framework is based on MDA that includes SPEF and MOF.
The overall architecture is shown in Fig. 2.
Fig. 2. Life-cycle of our proposed MDA service-oriented approach.
Adopting our proposed methodology to design context-aware systems has the follow-
ing advantages:
(1) Services-Oriented Modeling: It can reduce the deficiency of object-oriented mod-
eling in service-oriented applications, as UML meta-model cannot provide the neces-
sary support. In service-oriented environment, software and hardware can be
represented as services. Services are more transparent and loose coupled, which con-
tain a collection of independent functions or operations as compared to objects. Ob-
jects heavily reply on their interdependencies and their internal states to operate.
(2) Autonomous Behavior: A context-aware system based on SOA possesses abilities
such as autonomous adjustment, autonomous management, and autonomous deploy-
ment to satisfy diverse requirements from multi-user. The group consensus approach
collects the preferences from the users and reason over them to provide a basis for
system self-adjustment in order to meet the majority of users’ requirements.
(3) Annotating sensor data with semantics: Sensor data could be value of temperature,
humidity or an expression representing other conditions, but this data could imply a
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condition such as light brightness or weather. The sensor devices and their sensed
data can be grouped together to become services and annotated with semantics for
reasoning.
(4) Information Streams Fusion and resource description: The resource including data,
services, computation resource, and device profile will be described explicitly with
their location and characteristics. This can benefit locating, allocating and re-
deploying resources.
3.2 Top-down Modeling Analysis
Our proposed Model Driven Service-Oriented Approach (MDSOA) provides a top-
down modeling analysis method. As mentioned above, we combine MDA concepts in
the software design and system implementation with web services. The requirements
can be separated into two types: functional requirement, and comfort requirement.
Functional requirement defines scale, quantity, and function of all hardware and
software. For example, the number of lights, air-condition units, dehumidifier or
heater, etc. The comfort requirement is related to users’ preferences which are about
QoS.
The requirements collected from the previous CIM phase lay the foundation for
modeling the required services. An analyst can use any modeling language such as
UML to model the requirements. Because some of the service-oriented features can-
not be satisfied with UML, it requires another modeling language to specify service
flows, service relations, and service capabilities. Hence, we adopt Service-Oriented
Modeling Framework (SOMF) [41] in the PIM phase. SOMF is a discipline of mod-
eling business functions and system behaviors based on services.
Fig. 3. MDA Mapping Architecture of Top-Down Modeling Analysis.
In PSM phase, the main task is to draw SCA diagram and obtain a system meta-
model. After that, the SDO (Service Data Object) and ESB (Enterprise Service Bus)
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can connect to database and bind services together. SDO aims to provide a consistent
means of handling data within applications, regardless of its source and format. It
provides a unified way of handling data of databases and services. ESB is used to
integrate applications, coordinate resources, and manipulate information. The pro-
posed architecture is depicted in Fig. 3.
3.3 Button-up Assembling Analysis
From the top-down modeling analysis, we can analyze the system development life
cycle from abstraction stage to implementation. However, the system should be
adaptable and self-manageable according to changes occurring in the environment, so
it is able to take the users’ feedbacks and environment changes for system adaption.
Hence, we proposed a bottom-up analysis to increase the system’s capability in adap-
tion to the environment.
We adopt the SCA assembly model which deals with the aggregation of compo-
nents and their linkages. The assembly model is independent of implementation lan-
guage. SCA is a set of specifications which is used to build applications and systems
by deploying new service and composing existing components. SCA does not only
extend and complement prior approaches to implementing services, but also provide a
programming model for building applications and systems based on a SOA.
Fig. 4. Bottom-Up Assembling.
The business functions are supported by a series of services which are assembled
together to support a particular operational need. The assembly model deals with the
aggregation of components and the linking of the components. These services run on
the server containers. A service inventory includes a number of server containers.
4 Examples
In this section, we will demonstrate how MDA and SCA approach can be used to
develop smart building services for building energy management system. Further-
more, we adopted TOPSIS to resolve conflicts in group decisions.
4.1 Architecture
In the proposed smart office system, each device has a unique ID and it provides spe-
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cific service. For example, the motion sensor detects object movement within its
designated range. The temperature sensor measures temperature and humidity. These
sensors can be considered as an atomic service. All the service descriptions in smart
office can be stored in a registry. The overall architecture is shown as Fig 5.
Fig. 5. System architecture.
(1) Services Repository. The aim of semantic web service is to locate services auto-
matically based on the functionalities provided by the web services. These services
are registered in a service repository which is UDDI. Therefore, we use the JUDDI to
build UDDI environment which provides Business Entities, Service Entities, Binding
Templates, and tModels to represent the business details and its services. Services
registered with in JUDDI can be searched by name, location, business, bindings or
tModels.
(2) Consensus Service. We design a consensus service which is based on the TOPSIS
method to reason over a group of users’ preferences to identify their potential agree-
ments. These preferences can be very subjective and inconsistent and they could be
represented in different ways. The preferences can be associated with uncertainty,
fuzziness, and incompleteness. The consensus service is able to identify common
requests from the majority of users and made recommendations to the device service
to adjust the devices such as the light or air-condition services.
(3) Service Execution Engine. Service Execution Engine (SEE) provides a run time
environment for service binding and execution. We use an open source system, Tus-
cany, which is an Enterprise Service Bus (ESB) for our SEE. SEE is not only a web
server container but also can forward the message to other web services accordingly
which are deployed on the other server. For achieving goal of service execution, we
use the Synapse, which is an open source project as a routing server on Apache web
server. Synapse provides a simple, lightweight and fully open source SOA infrastruc-
ture to assemble and manage composite applications as well as route messages. Syn-
apse supports HTTP, SOAP, SMTP, JMS, FTP and file system transport for message
exchange using XSLS, XPath and XQuery to bind the web services. Fig 6 shows the
service execution engine architecture.
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Fig. 6. Service Execution Engine architecture.
(4) Rule Database. The rule database is used to store the expert rules and user prefe-
rences. Moreover, we used a tool kit, FuzzyJ, as the fuzzy inference engine in our
prototype system. The inference engine contains essential pre-defined knowledge for
interpreting and classifying the information e.g., Very Cold, Normal, Warm, Hot,
Very Hot. It consists of primitive and composite fuzzy terms, modifier and quantifica-
tion of fuzzy terms, and fuzzy rules. Primitive terms are a set of atomic terms that
represent a collection of raw data collecting by service broker.
(5) Sensor Services. The sensor device is associated with a sensor service which col-
lects and senses the environmental parameters. Sensor service transmits the sensor
data to service execution engine. The description of service is represented in RDF.
The sensor data in stored in XML format can be parsed consistently by other services.
4.2 Module Design
The prototype system is a smart office system and it is designed by following SCA
principles. We designed several composite services which are called SensorCompo-
site, InferenceComposite, UserOpionComposite, ConsensusComposite and Device-
Composite. The SensorComposite is composed of several components which include
FireSensorComponent, SmogSensorComponent, VoiceSensorComponent, Move-
mentSensorComponent, TemperatureSensorComponentand BrightnessSensorCom-
ponent. The SensorComposite is responsible for all kinds of sensor services. All sen-
sor data is transmit to InferenceComposite to evaluate whether the change of the
device parameters such as brightness of light is necessary or not. Another important
mechanism is related to handling the group preferences. The UserOpinionComposite
is used to collect users’ preferences. The feedbacks and preferences from users are
sent to ConsesusComposite to calculate and obtain their consensus if there is any. The
result of group consensus is then sent to the DeviceComposite.
The DeviceComposite would also receive the sensor data and preferences from
sensors and users. All the data and signals are stored in XML-format file. We model
these composite services by using SCA diagram which is shown in Fig. 7.
The system gathers environment related data to generate appropriate information
for use. For example, a user may leave his seat, and move to conference room. The
motion detection sensor would sense the situation, and the light will be turn off. The
patterns of interactions among these appliances and their controls can be driven by
analyzing sensor data. Thus, the detailed workflow design or relationship between user
and appliance are not necessary to be prescribed at design time. Hence, the proposed
framework includes a SCA approach which consists of service-oriented modeling and
assembling mechanism. Sensor and intelligent mechanisms can be considered as ser-
126

vices. It can not only activate component automatically, but also improve the service
capability on semantic interpretation and to reuse the existing service to build new
composite services to meet new requests.
Fig. 7. Service Composite based on SCA.
4.3 Implementation Details
We use a sequence diagram to help readers understand how services are activated and
adjusted to meet users’ requirements. The system has sensors to detect brightness,
voice and temperature and the corresponding devices to control them. The sensor ser-
vice transmits the sensor data to ESB. The ESB binds the inference service with rules
to reason over data and pass the outcomes to the device services. The device services
control and adjust the devices by giving appropriate commands and parameters (such
as dimmable light and air-condition).
Fig. 8. Sequence Diagram of service support the self-adjust between ESB and users.
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If the users feel too hot or gloomy, they can make requests to adjust the light or air-
condition. These requests are collected and submitted to the consensus service. Since
not every user wants to change the lighting or temperature and they may have conflict-
ing requests or preferences, the consensus service will reason over these data to pro-
duce the recommendations which satisfy most users’ preferences or requirements. If
there is any change required in the environment, the device services will set new para-
meters and send commands to the device such as light and air-condition according to
the recommendations.
5 Discussion
A number of research projects have been established in an attempt to solve the issues
associated with context-aware systems. Although sensing and perceptual technologies
have been increasingly recognized as key methods to develop smart environment, the
main problem is that a group of users might have different requirements in the same
space. Achieving context-awareness needs to take into account the variations present
in the environment and users’ opinions. The system does not only analyze the system
functional requirements, but also need to consider the users’ preferences.
Combining SCA and MDA could provide an adaptive platform to develop an auto-
nomous adaptation system. The main characteristic of SCA is that it supports declara-
tive foundation which enables it to access and compose services of diverse appliances.
Thus a context-aware system can use semantic annotations to locate and bind services
dynamically.
6 Conclusions
In this paper, we have demonstrated MDA approach along with SCA concept to de-
velop Service-Oriented applications. The appliances in the framework modeled as
services are annotated with semantics to alleviate the difficulty in development. The
composition mechanisms, message routing and data driven functions support the
intelligent control between appliances and sensors.
Our main contribution is a system modeling methodology which is based on
MDA and SCA to facilitate the development of smart building energy management
system which often involves complex activities and interactions among sensors, de-
vices and human users. Although sensors can control the devices, it needs to work
cooperatively with other devices and human users. In a context-aware system with
multiple users involved, it is important to develop a synchronous information stream
and fusion. Our proposed Model Driven Service-Oriented approach provides a solu-
tion for developers to extend service features to accommodate existing devices or
applications without rewriting them.
This study presents an overview of MDA with emphasis on the application of smart
office based on SCA framework which provides a mechanism to support necessary
steps required for service composition. The developers can take advantage of these
existing services and supporting functions to produce composite service for intelligent
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control. A prototype of the proposed framework based on a number of existing hard-
ware such as Arduino and software such as Synapse, and Tuscany has been developed
to test the feasibility of the proposed approach. Further development of the system by
introducing more intelligent rules and repositories is needed.
Acknowledgements. The research is supported by the National Science Council of
Taiwan under the grant No. NSC 96-2416-H-009-008-MY3. This research is also
partially supported by EU FP7 program under grant agreement no 224609.
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