EVALUATION ISSUES FOR UBIQUITOUS COMPUTING
Jung-Hyun Bae, Soon-il Cha, Seok-Kyu Shin
Telecommunications Technology Association, 267-2, Seohyun-dong, Bundang-gu, Seongam-city, Gyeonggi-do, Korea
Keywords: Ubiquitous Computing (UC), Evaluation, Quality Characteristic.
Abstract: One of the main problem with the evaluation of ubiquitous computing (UC) is that we do not have standards
guidelines, or metrics, even though there have been many researches on the individual technical aspects of
ubiquitous systems. UC systems differ from standard applications in many ways. Therefore, it is very hard to
apply the current working standards or metrics to the evaluation of UC system, which leads us to develop a
desirable way to deal with this. This paper suggests the evaluation issues of service and system software to
provide ubiquitous computing. Also, we investigate how equally the evaluation scopes we have suggested and
the quality characteristics could be matched with the current technological feasibility of the ubiquitous
computing systems, so we can see what benefits and the deficiencies of the proposed evaluation scopes would
be. Two case studies are considered and these can be seen as the most-likely applications in the current
ubiquitous computing environment.
1 INTRODUCTION
For decades, the improvement of communications
technologies has brought computing environment
evolved into human from machine. This is called a
ubiquitous computing environment, initially
introduced within the computer systems world by
Weiser in the early 1990s (Weiser, 2002),
comprehends the ability to exist everywhere at the
same time. Ubiquitous environment consists of
innumerable number of computing devices embedded
in almost everything around us, platforms and
networks that interconnect them, and user devices that
make use of and act on the available information. The
system software in this domain, it is a key issue to
provide satisfied UC services to users without
intrusion among heterogeneous devices with different
capabilities and protocols. The ubiquitous computing
has environmental problems such as wireless channel
fading and mobility. As these problems have
possibilities to affect the performance of a network
and application, it is often proposed that quality-of-
service (QoS) be handled at the ubiquitous system
software level (Tokunaga et al, 2004).
This paper proposes evaluation issues of services
and the system software running on the ubiquitous
computing environment. And we investigate the
feasibility for application of the proposed evaluation
scopes through considering two case studies.
2 UBIQUITOUS COMPUTING
ENVIRONMENT
A general ubiquitous computing system environment
has four entities; User, I/O artefact, Service,
Ubiquitous System Software as shown in Figure 1
(Cha et al., 2005).
When the receptive events are triggered by users’
activities, sensors or some physical input artefacts
carry out the operations of reception and integration
of the user’s activities. Examples of some physical
input artefacts are switches mounted to a grip,
trackballs, and mobile phone, gesture and speech
recognition or context awareness facilities. The
receptive function accepts the user’s activities and
act upon it, while the integrated function takes into
account the states of the several sensors as well as the
input artefacts at the same time, delivering the
information to the ubiquitous service. Once the
sensors or the physical input artefacts locate a
detectable event, the ubiquitous services act upon it to
process the integrated event.
Most of the ubiquitous application modules receive
a lot of data from other input artefacts or theirs and
interpret this data to fit into the context of the user’s
activities. The context awareness in the ubiquitous
services is of great importance (Asim, 2004). A very
significant part of the context is to know or be able to
infer the user’s intent. For instance, Global
317
Bae J., Cha S. and Shin S. (2006).
EVALUATION ISSUES FOR UBIQUITOUS COMPUTING.
In Proceedings of the International Conference on Wireless Information Networks and Systems, pages 317-320
Copyright
c
 SciTePress

Positioning Systems (GPSs) give us location context.
Some good sensing networks provide environmental
context, and clever service design can support some
levels of intent inference, i.e., situational context.
Ubiquitous system software controls all the data
processing for these individual entities in the
ubiquitous system and coordinates the contextual-
lization between services so that the services can
make intelligent decisions on how to interpret events.
The output artefacts formulate expressive functions
upon contextual events triggered from the ubiquitous
service. Finally, users evaluate the expressive events
from output artefacts e.g., large-wall-mounted display,
lights, sound or even hap-tic interfaces, in the system.
In a UC environment, service not only provides
configuration of integrated event (or data from the
sensors or physical devices) but also contextualization
with regard to the information that the ubiquitous
computing system has to provide. The system should
provide for the correct translation between data types
and representations of the outputs generated by one
service that are to be used as the inputs to another.
Therefore, service and system software can usually be
chained together to form a complicated task.
3 EVALUATION ISSUES FOR
SERVICE AND SYSTEM
SOFTWARE
Under the UC environment, we must consider the one
person-to-many computing interaction. This paper
figures out main function and quality characteristics
for service and system software entities.
Table 1 and Table 2 delineate evaluation scope
with the checklist examples and metrics for each
entity.
3.1 Service
The UC service refers to the applications that perform
computation or action on behalf of users in a
ubiquitous computing environment.
We have found several issues crucially important
for the successful deployment of services in the UC
environment: Functionality, service quality, smartness
and security. These are the key characteristics to make
UC possible.
Functionality
The ubiquitous computing service has the features
necessary to support the requirements. The general
purpose of functionality testing is to verify if the
product performs as expected and documented.
Developers creating a new product start from a
functional specification, which describes the product's
capabilities and limitations. Software functionality
test engineers utilise this specification as a guideline
for expected product response. Tasks are exercised to
test specific features or functions, and the results of
the tasks are verified to be in compliance, suitability
and accuracy with the expected response.
Service Quality
For varying application computation and
communication demands and for a varying quality
offered by the ubiquitous computing environments,
the ubiquitous system has to provide multiple grades
of service quality and maintain a number of agreed-
upon or negotiated service qualities. Technically,
quality of service (QoS) can be guaranteed through
bandwidth, ratio frequency and response time
requirements. In terms of evaluation objectives,
several characteristics of service quality should be
considered as followings: efficiency, resource
availability, reliability, maturity, fault tolerance, fault
recovery, maintainability and adaptability.
Figure 1: Interaction in UC System Environment.
Integration Fabric
Other
Application
Module
Application
Module B
Application
Module D
Application
Module A
Application
Module C
Telephone
Mobile &
Wireless
PervasiveWeb, IM, etc.
e
-
mail, Mail & Fax
…
I/O Artefact
Service
User
Activities Evaluation
Reception
Integration
Expression
Reception
Interpretation
Contextualization
Ubiquitous System Software
…
Configuration Coordination
Receptive
event
Data
Controlled
event
Expressive
event
Coordinated
event
Contextual
event
Integration Fabric
Other
Application
Module
Application
Module B
Application
Module D
Application
Module A
Application
Module C
Telephone
Mobile &
Wireless
PervasiveWeb, IM, etc.
e
-
mail, Mail & Fax
…
I/O Artefact
Service
User
Activities Evaluation
Reception
Integration
Expression
Reception
Interpretation
Contextualization
Ubiquitous System Software
…
Configuration Coordination
Receptive
event
Data
Controlled
event
Expressive
event
Coordinated
event
Contextual
event
WINSYS 2006 - INTERNATIONAL CONFERENCE ON WIRELESS INFORMATION NETWORKS AND SYSTEMS
318

Smartness
Smartness is often referring to Smart house or
smart room where small sensors, such embedded
processors are used to detect their surroundings and
equip human with both information processing and
communication capabilities. A smart house is a truly
interactive house using the latest information and
communication technology to link all the mechanical
and digital devices available today. Humans could
communicate and cooperate with other smart objects
and, theoretically, access all sorts of Internet
resources. Objects and appliances could thus react and
operate in a context-sensitive manner and appear to be
smart. Five aspects of smartness should be considered
for evaluation purpose: location awareness,
environment awareness, situation awareness, user
recognition and personalization.
Table 1: Evaluation Scope of the UC Service.
Data Intrusion Prevention Metrics:
- X = 1- A/ N, where A = No. of times that a major data intrusion event
occurred, and N = No. of test cases tried to cause data intrusion event
- Y = 1- B/N, where B = No. of times that a minor data intrusion even
occurred
- Z = A /T or B / T, where T = period of operation time (during operation
testing)
Is data encrypted to protect the wearer’s privacy?
- To prevent the wearer's identity being discovered
- To prevent the wearer's personal details(sensor data)
from being discovered
- To Provide encryption?
Privacy
Access Auditability X = A /B, where A = No. of “user accesses to the
system and data” recorded in the access history database, and B = No. of
“user accesses to the system and data” done during evaluation
How complete is the audit trail concerning the user
access to the system and data?
Authentication
Security
Personalisation Rate X = A /B, where A = No. of times the ubiquitous
computing system provides correct personalised information to a specific
user, and B = Total No. of times the ubiquitous computing system need to
provide correct customised functions to a specific user
Is the ubiquitous computing system capable of
providing personalised information according to user
preferences?
Personalization
Automatic Identification Rate = A /B, where A = No. of cases the ubiquitous
computing system identifies a user correctly, and B = Total No. of cases the
ubiquitous computing system needs to identify a user
Can the ubiquitous computing system automatically
identify the user?
User
recognition
Situation Sensitivity = confidence intervals (α± β%) in terms of the real
situation of the user
Is the system capable of providing environment-aware,
such as location-aware and orientation-aware sensor
data?
Situation
awareness
Environment Sensitivity = confidence intervals (α± β%) in terms of the real
environment of the user
Is the system capable of providing environment-aware,
such as location-aware and orientation-aware sensor
data?
Environment
awareness
Location Sensitivity = confidence intervals (
α± β
%) in terms of the real
location of the user
How accurate can the ubiquitous computing system
sense the user location?
Location
awareness
Smartness
Adaptability of data structure X = A /B, where A = No. of data which are
operable but are not observed due to incomplete operations caused by
adaptation limitations, and B = No. of data which are expected to be
operable in the environment to which the software is adapted
Can user or maintainer easily adapt software to data sets
in new environment?
Adaptability
Failure Analysis Capability X = 1- A /B, where A =No. of failures of which
causes are still not found, and B = Total No. of registered failures
Can user identify specific operation which caused
failure?
Maintainability
Recovery Rate =A /B, where A = No. of implemented recovery
requirements confirmed, and B = No. of recovery requirements in the
specification
How capable is the product in restoring itself after
abnormal event or at request?
Fault recovery
Fault avoidance rate = A /B, where A = Number of fault patterns having
avoidance, and B = Number of fault patterns to be considered
How many fault patterns were brought under control to
avoid critical and serious failures?
Fault Tolerance
Fault Detection Rate = A/B, where A = absolute number of faults detected in
this product, and B = number of estimated faults to be detected (using past
history or modelling techniques)
How many faults were detected in this product?Maturity
Reliability R(u) = exp(-u
λ
(x)) = exp(-u/MTTF). Here u is the projected
execution time in the future, x is a variable of integration, and
λ
(x) is the
failure rate.
How to measure system reliability?Reliability
Availability A = MTTF/(MTTF +MTTR), where MTTF is the mean time to
failure. MTTR is the mean time to repair.
What is the availability of the system?
Resource
availability
Maximum memory Utilisation X = Amax /Rmax, where Amax = MAX(Ai),
(for i=1 to N), Rmax = required maximum No. of memory related error
messages from 1st to i-th evaluation, and N = No. of evaluations
What is the absolute limit on memory required in
fulfilling a function?
Efficiency
Service
Quality
Accuracy to expectation Ratio = A / T, where A = No. of cases encountered
by the users with a difference against the reasonably expected results
beyond allowable, and T = Operation time
Are the differences between the actual and reasonably
expected results acceptable?
Accuracy
Function Adequacy X = A / B, where A = No. of functions in which
problems are detected, and B = Total No. of functions
How adequate are the evaluated functions?Suitability
Functional compliance ratio X = 1 –A/B, where A = No. of functionality
compliance items specified that have not been implemented, and B = Total
No. of functionality compliance items specified
How compliant is the functionality of the product to
applicable regulations, standards and conventions?
Compliance
Functionality
Metric(s)Checklist ExampleCharacteristicCriteria
Data Intrusion Prevention Metrics:
- X = 1- A/ N, where A = No. of times that a major data intrusion event
occurred, and N = No. of test cases tried to cause data intrusion event
- Y = 1- B/N, where B = No. of times that a minor data intrusion even
occurred
- Z = A /T or B / T, where T = period of operation time (during operation
testing)
Is data encrypted to protect the wearer’s privacy?
- To prevent the wearer's identity being discovered
- To prevent the wearer's personal details(sensor data)
from being discovered
- To Provide encryption?
Privacy
Access Auditability X = A /B, where A = No. of “user accesses to the
system and data” recorded in the access history database, and B = No. of
“user accesses to the system and data” done during evaluation
How complete is the audit trail concerning the user
access to the system and data?
Authentication
Security
Personalisation Rate X = A /B, where A = No. of times the ubiquitous
computing system provides correct personalised information to a specific
user, and B = Total No. of times the ubiquitous computing system need to
provide correct customised functions to a specific user
Is the ubiquitous computing system capable of
providing personalised information according to user
preferences?
Personalization
Automatic Identification Rate = A /B, where A = No. of cases the ubiquitous
computing system identifies a user correctly, and B = Total No. of cases the
ubiquitous computing system needs to identify a user
Can the ubiquitous computing system automatically
identify the user?
User
recognition
Situation Sensitivity = confidence intervals (α± β%) in terms of the real
situation of the user
Is the system capable of providing environment-aware,
such as location-aware and orientation-aware sensor
data?
Situation
awareness
Environment Sensitivity = confidence intervals (α± β%) in terms of the real
environment of the user
Is the system capable of providing environment-aware,
such as location-aware and orientation-aware sensor
data?
Environment
awareness
Location Sensitivity = confidence intervals (
α± β
%) in terms of the real
location of the user
How accurate can the ubiquitous computing system
sense the user location?
Location
awareness
Smartness
Adaptability of data structure X = A /B, where A = No. of data which are
operable but are not observed due to incomplete operations caused by
adaptation limitations, and B = No. of data which are expected to be
operable in the environment to which the software is adapted
Can user or maintainer easily adapt software to data sets
in new environment?
Adaptability
Failure Analysis Capability X = 1- A /B, where A =No. of failures of which
causes are still not found, and B = Total No. of registered failures
Can user identify specific operation which caused
failure?
Maintainability
Recovery Rate =A /B, where A = No. of implemented recovery
requirements confirmed, and B = No. of recovery requirements in the
specification
How capable is the product in restoring itself after
abnormal event or at request?
Fault recovery
Fault avoidance rate = A /B, where A = Number of fault patterns having
avoidance, and B = Number of fault patterns to be considered
How many fault patterns were brought under control to
avoid critical and serious failures?
Fault Tolerance
Fault Detection Rate = A/B, where A = absolute number of faults detected in
this product, and B = number of estimated faults to be detected (using past
history or modelling techniques)
How many faults were detected in this product?Maturity
Reliability R(u) = exp(-u
λ
(x)) = exp(-u/MTTF). Here u is the projected
execution time in the future, x is a variable of integration, and
λ
(x) is the
failure rate.
How to measure system reliability?Reliability
Availability A = MTTF/(MTTF +MTTR), where MTTF is the mean time to
failure. MTTR is the mean time to repair.
What is the availability of the system?
Resource
availability
Maximum memory Utilisation X = Amax /Rmax, where Amax = MAX(Ai),
(for i=1 to N), Rmax = required maximum No. of memory related error
messages from 1st to i-th evaluation, and N = No. of evaluations
What is the absolute limit on memory required in
fulfilling a function?
Efficiency
Service
Quality
Accuracy to expectation Ratio = A / T, where A = No. of cases encountered
by the users with a difference against the reasonably expected results
beyond allowable, and T = Operation time
Are the differences between the actual and reasonably
expected results acceptable?
Accuracy
Function Adequacy X = A / B, where A = No. of functions in which
problems are detected, and B = Total No. of functions
How adequate are the evaluated functions?Suitability
Functional compliance ratio X = 1 –A/B, where A = No. of functionality
compliance items specified that have not been implemented, and B = Total
No. of functionality compliance items specified
How compliant is the functionality of the product to
applicable regulations, standards and conventions?
Compliance
Functionality
Metric(s)Checklist ExampleCharacteristicCriteria
Security
The security of UC service refers to establish
mutual trust between infrastructure and device in a
manner that is minimally intrusive. Security can be
implemented in heterogeneous components such as
firewalls, different computer operating systems and
multiple databases. Authentication is one of the most
important characteristics of ubiquitous computing
security. Authentication provides confirmation of user
access rights and privileges to the information to be
retrieved.
3.2 System Software
UC device hardware is not simply limited to handheld
devices. There is also a large amount of fixed-
infrastructure hardware that may be incorporated into
a system. The software that runs the hardware devices,
and coordinates the usage of the physical resources is
of paramount importance. The UC systems software
and networks have two orthogonal aspects:
configuration and coordination.
Configuration
The systems software and networks used by a UC
system need to be able to be adequately configured so
that the ubiquitous computing system can effectively
use the hardware. From a purely configurational point
of view, the most important aspects of configuration
management are: scalability and extensibility.
Coordination
Coordination describes the system software’s
ability to coordinate a user request operating across
the ubiquitous computing system. We sub-divide this
category into resource coordination, mobility,
reliability and distributed systems support.
Table 2: Evaluation Scope of the UC System Software.
1-A/B where A is the number of machines still operating (in the
presence of other machines being unavailable) and users are still able
to submit new jobs (and have them complete) and B is the total
number of machines in the environment
To what level are the distributed physical resources inter-
dependent?
1-A/B where A is the number of machines that have been booted in
the environment and users are still able to submit new jobs (and have
them complete) and B is the total number of machines in the
environment
Is the systems software a ‘distributed/network operating
system’ or a ‘middleware layer’?
Distributed
systems support
What is the availability (‘up-time’) of the systems software? 1-(A/B)
where A is the time that the systems software has been unavailable
due to fault(s) and B is the sum of the time the systems software has
been operating and to has been unavailable.
What technical support is available for the system
software or hardware?
What is the availability (‘up-time’) of the hardware? 1-(A/B) where A
is the time that the hardware has been unavailable due to fault(s) and
B is the sum of the time the hardware has been operating and to has
been unavailable
Does the system continue working in the presence of a
variety of faults?
Reliability
1-(A/B) where A is the time for the system to access a re-located piece
of hardware (after the system is quiescent) and B is the time to access
the hardware before moving
Is there enough information available on remote
resources to make a good judgement on where to locate
code/data
1-(A/B) where A is the time for the system to locate a re-located piece
of hardware and B is the time to locate the hardware before moving
Is the resource monitoring aspect of the systems software
sophisticated enough to judge whether a program or code
would be more efficient if located elsewhere?
Mobility
1-(A/B) where A is the response time of the system after a new
service is invoked and B is the response time of the system before the
service was invoked.
How well does the systems software control resource
sharing on the local hardware
Resource
coordination
Coordination
A/B where A is the number of software systems that have technical
support available from the Vendor and B is the total number of
softwar e systems in the environment
Can programmers interrogate the services or other
hardware used by the system?
A/B where A is the number of software and hardware systems that can
be upgraded in the field and B is the total number of hardware and
software systems in the environment that could need upgrading
Is there a programmer API that can be used to extend the
system?
Extensibility
A/B where A is the number of jobs (queries, service invocations) that
are waiting to be executed and B is the number of jobs that are
concurrently being executed on average (lower is better).
Is there a list of drivers or APIs that can be used by
developers or technical people to use a new piece of
hardware with the ubiquitous computing system?
1-(A/B) where A is the response time of the system after new
hardware is added and B is the response time of the system before the
new hardware was added
Does the ubiquitous computing system support the ability
to add new hardware?
Scalability
Configuration
Metric(s)Checklist ExampleCharacteristicCriteria
1-A/B where A is the number of machines still operating (in the
presence of other machines being unavailable) and users are still able
to submit new jobs (and have them complete) and B is the total
number of machines in the environment
To what level are the distributed physical resources inter-
dependent?
1-A/B where A is the number of machines that have been booted in
the environment and users are still able to submit new jobs (and have
them complete) and B is the total number of machines in the
environment
Is the systems software a ‘distributed/network operating
system’ or a ‘middleware layer’?
Distributed
systems support
What is the availability (‘up-time’) of the systems software? 1-(A/B)
where A is the time that the systems software has been unavailable
due to fault(s) and B is the sum of the time the systems software has
been operating and to has been unavailable.
What technical support is available for the system
software or hardware?
What is the availability (‘up-time’) of the hardware? 1-(A/B) where A
is the time that the hardware has been unavailable due to fault(s) and
B is the sum of the time the hardware has been operating and to has
been unavailable
Does the system continue working in the presence of a
variety of faults?
Reliability
1-(A/B) where A is the time for the system to access a re-located piece
of hardware (after the system is quiescent) and B is the time to access
the hardware before moving
Is there enough information available on remote
resources to make a good judgement on where to locate
code/data
1-(A/B) where A is the time for the system to locate a re-located piece
of hardware and B is the time to locate the hardware before moving
Is the resource monitoring aspect of the systems software
sophisticated enough to judge whether a program or code
would be more efficient if located elsewhere?
Mobility
1-(A/B) where A is the response time of the system after a new
service is invoked and B is the response time of the system before the
service was invoked.
How well does the systems software control resource
sharing on the local hardware
Resource
coordination
Coordination
A/B where A is the number of software systems that have technical
support available from the Vendor and B is the total number of
softwar e systems in the environment
Can programmers interrogate the services or other
hardware used by the system?
A/B where A is the number of software and hardware systems that can
be upgraded in the field and B is the total number of hardware and
software systems in the environment that could need upgrading
Is there a programmer API that can be used to extend the
system?
Extensibility
A/B where A is the number of jobs (queries, service invocations) that
are waiting to be executed and B is the number of jobs that are
concurrently being executed on average (lower is better).
Is there a list of drivers or APIs that can be used by
developers or technical people to use a new piece of
hardware with the ubiquitous computing system?
1-(A/B) where A is the response time of the system after new
hardware is added and B is the response time of the system before the
new hardware was added
Does the ubiquitous computing system support the ability
to add new hardware?
Scalability
Configuration
Metric(s)Checklist ExampleCharacteristicCriteria
4 CASE STUDY
We consider two case studies and investigate the
propriety of the proposed evaluation scopes for UC
service and ubiquitous system software.
4.1 Mobile Banking Service
The main applications of the ubiquitous service would
be via mobile phones. SK telecom and Telecom NZ
EVALUATION ISSUES FOR UBIQUITOUS COMPUTING
319

introduced the mobile banking service in 2004. The
customer can use the service anywhere without
distorting or blocking the signal. Service provider’s
global network allows the mobile banking to be sued
around the world using their roaming service
(Maintainability – Service Quality). One of the major
banks in New Zealand, ASB bank has introduced
mobile banking service, taking security seriously and
offering the security of a secure 128 bit encrypted
connection. Furthermore, the customers are required
to enter their personal access code and passwords to
sign on the system (Security – Service). They also
provide some emergency situation control such as
battery discharges while doing banking service. All of
the banking transactions the customers made before
their phone battery discharged should have done
through. Once battery is recharged, customers can
check the balances and the record of the last
transactions the customers made. Alternatively,
because all the online service are real time, the
customers can also check the balanced and last
transactions through internet banking or telephone
banking service (Reliability – Service Quality and
Coordination). In addition, as the customers’ accounts
will be displayed on the screen of the mobile phone,
so the customer can access their accounts quickly
without fuss when they are on the move
(Functionality – Service). This service is also
designed to cope with a large number of users and has
a back-up system (Scalability – Configuration).
4.2 Location-Awareness Service
As another application of the ubiquitous service via
mobile phones, Vodafone Germany (2000) introduced
the first location awareness services based on the
WAP portal in the world. All location-based services
offered so far to mobile phone users are always pull-
services, say; the user has to explicitly request
information relevant to her current location. This is
particularly annoying if the user always has to
establish a WAP connection before he can use such
services. It takes a lot of time, which limits the values
of the service to the user, and it is also very costly as
the user usually has to pay for the online time. Thus,
this service should be very easy to use, therefore must
offer a simple, yet powerful interface, be robust, and
error-tolerant, covering the reasonable service region
(Reliability – Service Quality and Coordination, Re-
source availability – Service Quality). The location-
awareness service must also be secure and private to
the users. The user should be able to turn on/off the
service to actively confirm her wish for localization
for privacy reasons (Privacy – Service). The most
important technical concern of this service is the high
accuracy location enabler across all environments
(Location awareness – Smartness). However, in order
to realize the proper location awareness service,
information has to be automatically delivered to the
user (Functionality, Adaptability – Service). The
system architecture for tracking location should also
not be restricted to or depend on specific kinds of
trackers. It must allow adding new trackers (perhaps
even newly developed trackers) and including them
easily in the overall architecture (Extensibility,
Scalability – Configuration).
5 CONCLUSION
This paper outlines the issues to be considered in
terms of UC service and system software evaluation.
We also apply the proposed evaluation scopes to two
case studies. However, these are not a full evaluation
scope but some important things. We expect that
these issues can be the beginning point to make the
systematic UC system evaluation model along with
the present software evaluation model such as
ISO/IEC 9126 or 12119. Our work raises the need of
framework development and opens a new discussion
for the UC evaluation.
REFERENCES
M. Weiser, 2002. The Computer for the 21st Century. IEEE
Pervasive Computing, 1 (1), pp.18-25.
Tokunaga. E, et al, Aug. 2004. A middleware infrastructure
for building mixed reality applications in ubiquitous
computing environments, MOBIQUITOUS 2004,
pp.382-391.
S. I Cha, J. H Bae, et al, Jan.2005. Evaluation issues of
ubiquitous computing systems, APIS 2005, pp.637-640.
Asim. S, Daniel. S, Aug. 2004. Application design for
wearable and context aware computers, IEEE Pervasive
Computing, pp.20-29.
WINSYS 2006 - INTERNATIONAL CONFERENCE ON WIRELESS INFORMATION NETWORKS AND SYSTEMS
320