A UCWW CLOUD-BASED SYSTEM FOR INCREASED SERVICE

CONTEXTUALIZATION IN FUTURE WIRELESS NETWORKS

Ivan Ganchev

1,2

, Máirtín O’Droma

, Nikola S. Nikolov

3,1

, Zhanlin Ji

4,1

Telecommunications Research Centre, University of Limerick, Limerick, Ireland

Department of Computer Systems, Plovdiv University, Plovdiv, Bulgaria (on leave)

Department of Computer Science and Information Systems, University of Limerick, Limerick, Ireland

Research Centre for Bioengineering and Sensing Technology, University of Science and Technology Beijing, China

Ivan.Ganchev@ul.ie, Mairtin.ODroma@ul.ie, Nikola.Nikolov@ul.ie, Zhanlin.Ji@ustb.edu.cn

Keywords: Ubiquitous Consumer Wireless World (UCWW); Future Networks (FN); Cloud-based System; Software

Architecture, Middleware, Service Contextualization, Context Awareness.

Abstract: This paper describes the design and development of a novel cloud-based system for increased service

contextualization in future wireless networks. The principal objective is the support of mobile users

(consumers) in a Ubiquitous Consumer Wireless World (UCWW) seeking to choose and select the ‘best’

service instance in a UCWW environment matched to their dynamic contextualized and personalized

service delivery requirements and expectations, thereby increasing user freedom in where, when and how

they access desired services, and increasing user-driven networking. The design challenges to create such a

cloud-based system with an ever-enhanced capacity to be attuned to a user-client’s dynamic contexts, and

do this for all its users, are addressed, and software infrastructural design solutions suggested. The cloud

idea proposed here is one which should yield efficiencies and saving for consumers, operate as an

additional ‘behind-the-scenes’ decision support subsystem to make smart decisions based on mining of the

most up-to-date data stored in the cloud repositories related to service contexts and personalized profiles.

Rather than the use of known efficient heuristic methods employed with large and complex data structures,

together with associated algorithms solving the combinatorial optimization problems, an alternative method,

proposed here for making predictions, is to discover patterns in the behaviour of the individual client-

consumer, to bring into play, in the decision process, patterns and trends of other client-consumers seeking

the same or similar services, and also the constant update of the user’s wireless environment context through

information garnered from other sources, such as wireless access service provider updates, teleservice

provider updates, and data sensed by the sensors in the environment. Indentifying and addressing the need

as directly as this is a novel approach towards providing context-aware personalized services. It is

particularly novel, and desirable, in the UCWW context. Hence, this consumer supportive smart repository

solution may appropriately be called a UCWW cloud. The paper sets out an infrastructural design of this

cloud, ordered within a conceptual UCWW software architecture, together with its various elements, e.g.,

decision support subsystem and mobile network environment elements of personalized information retrieval

(PIR).

1 INTRODUCTION

The research described in this paper is motivated by

the context-awareness and service contextualization

problems within the Ubiquitous Consumer Wireless

World (UCWW) environment. The UCWW,

proposed in (O’Droma, 2007) & (O’Droma, 2010),

sets out a generic consumer-centric techno-business

model foundation for future generations of wireless

communications. The evolution of the UCWW

environment represents a shift from the currently

dominating subscriber-based access to wireless

communication services, towards more consumer-

centric one. By utilizing a person-centric IPv6

address scheme, enabling full number portability as

well as an access-network-independent third-party

Ganchev I., Ganchev I., O’Droma M., Nikolov N., Nikolov N., Ji Z. and Ji Z.

A UCWW CLOUD-BASED SYSTEM FOR INCREASED SERVICE CONTEXTUALIZATION IN FUTURE WIRELESS NETWORKS.

DOI: 10.5220/0004785500690078

In Proceedings of the Second International Conference on Telecommunications and Remote Sensing (ICTRS 2013), pages 69-78

ISBN: 978-989-8565-57-0

authentication, authorization, and accounting (3P-

AAA) service provision, consumers can dynamically

select a provider for a service from a list of

alternatives. This in turn opens up the opportunity

for stronger competition between providers and as

such, to an improved level of service for the

consumer. Effective exploitation of the attractive

benefits of this freedom will need the support of

‘smart’ software tools. These will dynamically

collect and sort through the vast numbers of service

options on offer to a consumer at any time and place,

which might otherwise be overwhelming, and

extract service-type-dependent ranked choice

suggestions matched to the consumer’s relevant

profile.

In support of these tools and of the whole

consumer-choice optimization process, we propose

here the development of a UCWW cloud-based

system to facilitate the delivery of increasingly

contextualized services in future wireless networks.

Through this user-centric UCWW cloud, mobile

users can have access to a more contextualized level

of service provision, with a much greater level of

choice in terms of service delivery. Moreover,

service providers can deliver a much more

specialized level of service, to a much larger set of

mobile users.

The main goal in our work is to provide the user

with a context-aware software tool that can assist the

user to choose and select the ‘best’ service instance

in a UCWW environment. Through an appropriate

graphical user interface (GUI) the tool may make the

service choice easier or may make the choice on

behalf of the user when authorized to do so. In both

cases, the software tool would benefit greatly from

the ability to make accurate predictions of user

preferences in particular situations, i.e., making the

choice of one particular mobile service instance

(provider) when the user desires to use a specific

service. This prediction may be the result of solving

a combinatorial optimization problem, where the

user has specified criteria for making a particular

choice. For example, the GUI may allow the user to

specify a few parameters such as an upper bound on

the price, lower bound on the quality of service

(QoS), etc. The difficulty is both computational –

often such problems are NP-complete (Garey, 1979)

– and related to the limited hardware resources on

mobile devices, which may not allow the use of

large and complex data structures and algorithms.

Therefore, efficient heuristic methods must be used,

particularly for the context of solving the

combinatorial optimization problems (Wolsey,

1999) & (Cook, 1997) on mobile devices. An

alternative method for making predictions is to allow

the software to discover patterns in the behaviour of

the consumer. In order to achieve this, the user

behaviour should be recorded, stored and uploaded

as appropriate to a distributed repository. On behalf

of individual users, but for many users, this will

allow always best connected and best served

(ABC&S) applications, within the distributed

repository, to carry out effective mining of data

(Usama, 1996) & (Mikut, 2011) that may result in

more accurate and more beneficial user behaviour

predictions (Witten, 2011). Such a repository can be

viewed as a UCWW cloud that facilitates data

storage and offers service predictions based on the

patterns discovered within the user data.

For this, foremost cloud computing principles

and techniques need to be employed along with

effective data collection and data mining techniques

to facilitate predictions as to the applicability of

services to particular users. The impact of this work

will be to provide a more consumer-centric wireless

services environment, which can also be

commercially attractive to service providers.

The rest of the paper is organized as follows.

Section 2 provides an overview of the UCWW.

Section 3 presents the UCWW cloud as a context-

aware middleware. Section 4 describes the decision

support subsystem of the UCWW cloud. Section 5

considers the implementation issues. Finally, section

6 concludes the paper and suggests future research

directions.

2 UBIQUITOUS CONSUMER

WIRELESS WORLD (UCWW)

Being a wireless communication environment rather

than a wireless technology, and while requiring

some distinct technological infrastructural

modifications and innovations (O’Droma, 2007) &

(O’Droma, 2010), UCWW is completely in harmony

with, and will benefit fully from, almost all the

existing global technological developments and

ongoing standardization efforts in wireless

communications, e.g., Next Generation Mobile

Networks (NGMN) Alliance proposals (Kibria,

2007), 3rd Generation Partnership Project's (3GPP)

Long-Term Evolution and System Architecture

Evolution (LTESAE) (Ekstrom, 2006), and ITU-T's

ongoing work on Next Generation Networks (NGN)

(Carugi, 2005). The primary change UCWW brings

is that, through it, users become consumers instead

of subscribers. The ‘in harmony’ element of this

evolution is emphasized by the fact that UCWW

Second International Conference on Telecommunications and Remote Sensing

consumers may opt out (or in) of having such

subscriber-like contracts, or may have several

simultaneously through a single Consumer Identity

Module (CIM) card and without conflict with

different access network providers (ANPs). While it

is evolutionary, it enables significant and new user-

driven wireless communication capabilities and

benefits, and converting the wireless environment

into a consumer-centric one. True user-driven

ABC&S paradigm (Passas, 2004) may be considered

to encompass many of these benefits, and more.

Most are obviously inherent and distinctively

characteristic of UCWW; others are not, e.g., the

user-driven integrated heterogeneous networking

(IHN) and interworking – a published amendment to

an existing ITU-T recommendation standard for the

latter is shown in (O’Droma, 2010). In this, UCWW

marks a seismic shift from the network-centric,

subscriber-based techno-business model (SBM) of

today, with its long-term lock-in type contract

between the subscriber and the ANP, with all its

constraints, to a new consumer-centric techno-

business model (CBM).

Figure 1 portrays schematic representations of

both techno-business models (SBM & CBM),

illustrating the main mobile service paths and

business agreement relationships. Transition to the

UCWW, where the new CBM environment may co-

exist side-by-side with the SBM environment, is

shown as a passage through a global standardization

frontier.

In SBM, the subscriber primarily gets wireless

services through his/her ‘home’ (cellular) ANP or

from visited-ANPs, if roaming agreements are in

place. WiFi hotspots, Femto-cells and the like, when

they offer services using the AAA infrastructure of a

user’s home-ANP, come under the visited-ANP

umbrella. Teleservice providers (TSPs) and value-

added service providers (VASPs) can also offer their

own services through access networks under

respective bilateral business agreements.

Figure 1: Subscriber-based (SBM) and consumer-centric (CBM) techno-business models.

The main downsides of SBM, mainly linked to

the ‘lock-in’ constraint of the (long-term) subscriber

contract with a home-ANP, include: roaming

charges which are often perceived as non-cost based,

domination of ANP marketplace by a few large

operators, poor market openness for new or niche

ANPs due to prohibitive start-up costs, limited

‘number portability & mobility’ among ANPs. In

regard to the latter, subscribers who desire to move

ANP, rather than porting their number, tend to the

A UCWW Cloud-Based System for Increased Service Contextualization in Future Wireless Networks

easier solution of buying a new (U)SIM card with

another phone number in the other network.

Spinning is another popular approach whereby

subscribers, using multiple-(U)SIM-card phones,

can choose to operate on any one of ANPs at any

time. However, this is still quite far removed from

the full ‘number portability & mobility’ within the

CBM, where consumers will be allowed always to

use the ‘best’ ANP for each particular service

instance.

Transition to UCWW and enabling the growth of

CBM open opportunities to address these issues. The

two principles underpinning this new CBM

environment are: (i) the decoupling and separation

of the administration and management of users’

AAA activity from the supply of a wireless access

(transport) service and its devolution to new non-

ANP trusted 3P-AAA entities, and (ii) the full

consumer ownership and portability of their globally

significant address.

Besides a range of new benefits for the

consumer, UCWW has the clear potential to

stimulate the creation of a number of new interesting

business opportunities and to create a more liberal,

more open and fairer wireless marketplace for

existing and new ANPs. The primary ANP business

success indicator will shift from subscriber numbers

to the volume of consumer transactions – a radical

change. This will increase the range of competitive

price/performance and price/QoS offerings,

specialist and niche access-network service

offerings, and so forth, all of which will drive

forward innovation in the mobile services market.

The preliminary blue-skies research work on

crystallizing and defining the UCWW concepts and

its key infrastructural pillars has been done already,

e.g., (O’Droma, 2007) & (O’Droma, 2010). In-depth

research, elaboration, design and implementation of

these novel infrastructural components along with

their integration into a pilot system prototype are the

next phase of this project. The main goals are the

following:

 Research, innovate, derive, design, implement,

field-trial, validate and evaluate the

performance of:

− A feasible UCWW software

architecture, operating within OSGi

(Alliance, 2007) and cloud

environments.

− New UCWW infrastructural protocol

interfaces and functionalities, especially

for those on the 3P-AAA (Ganchev,

2006) and the third-party charging and

billing (3P-C&B) (Jakab, 2011) service

provision infrastructural elements,

which satisfy and respect the network-

independent, autonomous, trusted, and

pervasive requirements and criteria of

the service providers entities;

− A prototype of the new universal CIM

card employing the new ‘personal IPv6’

identity, (Ganchev, 2007) & (Ganchev,

2009).

 Design and establish the technological

dimensions of the first scalable UCWW

cloud-based system and provide a field-trial

demonstration of its operation.

 On the back-end, design an UCWW cloud to

facilitate the storage of user data harvested via

mobile devices, and based on the analysis of

this data, to offer predictions as to the

applicability of services to particular users,

and enable ever-enhanced contextualization

and personalization functionalities and

services. By monitoring this information, the

system should accurately predict the types of

services most applicable to individuals, and in

turn, recommend these to the users.

Furthermore, efficient heuristic algorithms

must be designed to facilitate service

utilization predictions locally on the mobile

devices or as part of the UCWW cloud as an

alternative to mining the stored data.



Within the client devices, facilitate the

effective functional design of the user profiles

and GUI templates, targeted at the major

smartphone platforms (Android, iOS,

Windows Mobile), with each variation

interoperating with the UCWW back-end

cloud.

 Finally, making this UCWW cloud-based

system commercially viable will be

investigated. Clearly legacy mobile operators

are likely to be reluctant to open their own

customer profile database to competitors in

whatever way that might happen; or not

happen, as it is not in anyway essential to the

proposal. UCWW cloud providers will market

their services directly to consumers. In such a

market, legacy providers would already be in

prime position – to manage and market their

own UCWW cloud services. Hence, the

proposals in this paper could make the shift to

UCWW more attractive for these operators.

With such realization potency in mind, the

deployment of service contextualization

mechanisms will be investigated from an

operator's point of view.

Second International Conference on Telecommunications and Remote Sensing

3 THE UCWW CLOUD AS A

CONTEXT-AWARE

MIDDLEWARE

From one point of view, the UCWW cloud that we

envision can operate as a middleware of a context-

aware system. In its traditional sense, a context-

aware system is a distributed system, which consists

of hardware devices (sensors) to sense or collect

context data, applications which make use of this

data, and middleware that manages the flow of

context data from the points of collection to the

applications. In our case mobile devices such as

smartphones and tablet computers play the role both

of the sensors of context data and the platform that

runs applications which use this data. Besides the

context that relates to the mobile services available

and on offer, the context data may relate to the user

(e.g., the user location, local time, current battery

charge and other operational characteristics of the

user’s mobile device, etc.), and/or relate to the

constraints of the wireless access network currently

utilized by the user (e.g., QoS level and pricing

scheme,), Figure 2.

Figure 2: Context types and context awareness in UCWW.

According to the characterization of context-

aware systems proposed in (Henricksen, 2005), the

various functions and components of such systems

can be organized into a five-layer architectural

model, with layers (each providing services for the

layer above it) as follows:

 Layer 4: Application components.

 Layer 3: Decision support tools/subsystem.

 Layer 2: Context repositories.

 Layer 1: Context processing components.

 Layer 0: Context sensors.

At the lowest layer, the mobile devices collect

context data from the environment, and at the

highest layer applications, which run on those

mobile devices, make use of this data. Layers 1-3

form the middleware of the system, which can be

entirely or partially implemented as cloud services.

In particular, we propose layers 2 and 3 to be

entirely implemented within the cloud, while layer 1

can be partially implemented at the mobile devices

for increasing the overall efficiency of the system.

Surveys of context-aware middleware,

(Henricksen, 2005) & (Romero, 2008), summarize

the functional and non-functional requirements for a

context-aware middleware. Besides the functions,

already listed above (i.e., processing of context data,

storing context data in repositories, and providing

decision support tools), a context-aware middleware

may also be expected to address the following

issues:

 Heterogeneity: In our particular case, this

means to support a variety of mobile devices

and operating systems.

 Adaptation: In order to adapt to the user’s

habits, the system needs to perceive the

context of the environment (via sensors) and

quickly react and adapt to changes in the

context. This is particularly important for our

system because we expect frequent and

constant changes in the context due to the

mobile nature of the user devices (sensors).

 Scalability: The performance of the system

when interacting with a large number of users

should be on the same scale as when

interacting with a small number of users. In a

typical scenario, there could be a few

thousands of sensors at a site (e.g., a large

airport) and potentially millions of users at

various sites who simultaneously query the

decision support subsystem (c.f. the query

configuration in Figure 3).

 Privacy: The privacy of the users’ data must

be maintained according to their preferences.

Levels of confidentiality, options in regard to

this, and distribution of responsibility are

challenging issues in this context.

 Traceability and control: Users should be able

to control any automatic functions of the

system and the systems should provide means

of making those decisions transparent to users.

 Application building support

: It is also

essential for our system to provide application

programming interfaces (APIs), which enable

software developers to build a variety of

smartphone applications which interact with

the context-aware middleware.

 Easy deployment and configuration.

 Tolerance to component faults.

A UCWW Cloud-Based System for Increased Service Contextualization in Future Wireless Networks

There have been a few generic context-aware

middleware solutions proposed in the research

literature, including Gaia (Román, 2002),

Reconfigurable Context-Sensitive Middleware

(RCSM) (Yau, 2002), PACE (Henricksen, 2005),

CARISMA (Capra, 2003). While using these as a

base for comparison, we propose to design a cloud

which provides the features expected from a context-

aware middleware and at the same time is highly

specialized for the particular nature of the UCWW.

Furthermore, we consider a concept of context

which allows the decision support subsystem to

make smart decisions based on mining of data stored

in the cloud repositories. We propose the context to

include both the data sensed by the sensors in the

environment (as in a typical context-aware system),

and the history of the user and the collective history

of users who have used the system in the same

environment. To the best of our knowledge, this is a

novel approach in providing context-aware services

with elements of personalized information retrieval

(PIR) in a mobile network environment.

Extension of the UCWW cloud’s functionality is

also envisaged which will open opportunities for

trusted third-party communication service providers

(Toseef, 2011). These will negotiate with providers

on behalf of users for their service requests and they

may assist in handling seamless handovers to ensure

uninterrupted service delivery to users.

4. DECISION SUPPORT

SUBSYSTEM

Figure 3 summarizes the flow of context data

between a smart mobile device and the UCWW

cloud as well as the mechanism of sending requests

and receiving responses from the decision support

subsystem. The role of the decision support

subsystem is to provide ratings (ranking) of the

service providers available for particular type of

service requested by the user. In order to make

accurate predictions, the decision support system

makes use of additional context data, which may

include any of the following:

 User-specified parameters such as the upper

bound on the price, lower bound on QoS, etc.;

 Current user location, current time, battery

charge and potentially other parameters of the

environment;

 The request and decision history of the user

who is requesting the decision;

 The request and decision history of users who

have requested the same service in the same or

similar context.

 ‘User-unaware’ context autonomous cloud

functionality, including new wireless services

of which a user(s) may be totally unaware but

may likely prefer as a replacement for existing

services. An example could be the vast array

of government services coming down the line,

e.g., G-Cloud in the UK (c.f.

gcloud.civilservice.gov.uk

Context Data

Manager

Decision

Support

Subsystem

Data

Storage

context data

Smart

Mobile

Device

decision re

uest

response: rating of service providers

UCWW cloud

Figure 3: Communication between a smart mobile

device and the UCWW cloud.

Context data can be sent from the mobile device

to the cloud either together with the request for

decision or asynchronously when changes in the

context occur. Any context data gets processed by

the context data manager which prepares the data for

storage and makes changes to the data storage.

When a request for a decision arrives, it is accepted

by the decision support subsystem, which in turn

requests the current context from the context data

manager before making a decision. After a decision

is made, the decision support subsystem notifies the

context data manager so that the decision can be

stored in the data storage. In accordance with the

requirements listed in the previous section, the

decision support subsystem may also accept requests

to explain its decision. In satisfying such requests, it

is assisted by the context data manager, which can

provide the correct historic information that was

used in making the decision. Such mechanisms

would also serve service auditing processes, service

level agreements, etc.

Systems which retrieve information that is both

relevant to the submitted queries and personalized

for the user are known as PIR systems. They have

been the subject of extensive research in the last

couple of decades with a major application in web

search as well as in other areas such as eLearning

and news dissemination (Ghorab, 2012). A

community-based PIR (Teevan, 2009) & (Sugiyama,

2004) would suit our needs best because ideally we

would like to offer personalized results to the user

Second International Conference on Telecommunications and Remote Sensing

based on their previous behaviour and experience

but also based on the experience of other users who

have used the service in a similar context. An early

research action is to decide what information about

users should be tracked, how this information will be

gathered and stored in a user model and then how

user models will be used for retrieving personalized

results.

In summary, we propose to build the data

repository according to existing models employed

for community-based PIR. The decision support

subsystem will be tuned by experimenting with a

variety of data mining algorithms (Witten, 2011) and

finding an acceptable compromise between speed

and accuracy of the predicted rating of providers.

Once the decision support subsystem’s software tool

can make accurate predictions – whether by running

heuristic algorithms for solving optimization

problems (Papadimitriou, 1998) locally on the smart

mobile device or by using a service provided by the

cloud, or a combination of both –, these predictions

can be delivered to the application level and

incorporated into the client’s GUI, aiding the user in

making a choice for a particular service or, where

the user so desires, configuring the system to make

automatic choices.

5 IMPLEMENTATION ISSUES

While UCWW is a completely distributed wireless

communications environment as described earlier,

one could conceptually consider the software

underpinning its various infrastructural elements

within a conceptual software architectural model.

This may help facilitate comprehensive, systematic,

organized and managed software designs and

solutions, with a view also towards increasing

software re-use. Hence below a speculative 3-tier

architecture model is suggested (Figure 4).

5.1 UCWW software architecture

model

The 3-tier UCWW software architecture model

typically would include, at the application tier level,

such key elements as the 3P-AAA/3P-C&B

applications, the CIM card, a multi-agent platform,

and a Hadoop cloud environment (Borthakur, 2007).

Figure 4: The UCWW software architecture model.

The UCWW middleware is being developed with

three clusters, namely Kafka (kafka.apache.org),

Storm (storm-project.net), and Hadoop HDFS

(Figures 5 & 6). Kafka is a high-throughput

distributed messaging system, used as a load

balancing cluster for parallel data loading into

Hadoop. The data output from Kafka is sent to the

Storm cluster for real-time processing. Then the

useful dataset is serialized to HBase in the Hadoop

cluster. The Hive (hive.apache.org

), Cloudera

Impala (ccp.cloudera.com

), and Flume

(flume.apache.org

) will be used for data mining.

5.2 3P-AAA/3P-C&B

Based on the 3P-AAA/3P-C&B infrastructure, an

amendment to ITU-T's SBM authentication

architecture for interworking in NGN is being

designed, developed and implemented (O’Droma,

2008), based on the ITU-T Draft Rec. Q.3202.1

A UCWW Cloud-Based System for Increased Service Contextualization in Future Wireless Networks

(ITU-T, 2008) SBM 3P-AAA model. A JDiameter

(JDiameter, 2013) based 3P-AAA framework is

being realized. The 3P-AAA/3P-C&B platform will

be realized in a lab environment with corresponding

mix of client applications for smartphones.

Figure 5: The UCWW middleware.

Figure 6: Context data processing in the UCWW

middleware.

5.3 CIM

The universal CIM card acts as a user data server in

the UCWW system. A number of security

applications run on a single virtual machine to

maintain the user profiles, associated credit-card

information, user’s personal IPv6 address, 3P-

AAA/3P-C&B related data, X.509 certification,

personal cloud container, etc., and ROM and

EEPROM on the CIM card. These applications will

communicate with each other using shared interface

objects (SIO), (Avvenuti, 2012). A firewall is

defined by each application to provide application-

level security.

A personal cloud container is being designed to

include a UCWW personal cloud identifier, personal

data category, session ID, cookies, etc. The client

application is being developed to work within a

Google Android (Fledel, 2012) environment (Figure

7). A SIMAlliance Open Mobile API specification

(SIMAlliance, 2013) will be integrated into the

Android platform to enable user devices to

communicate with secure elements of the CIM.

Figure 7. The CIM module on Android.

Second International Conference on Telecommunications and Remote Sensing

6 CONCLUSIONS AND FUTURE

WORK

The UCWW infrastructural entities and protocols

are all novel. Hence also all of the work on this

project is innovative and advancing knowledge in

the area. Our work will show that this completely

original way of organizing the global mobile

telecoms business is feasible. The innovative

infrastructural and technological changes to be

realized in the pilot field trial will demonstrate how

UCWW will enable greater service choice,

contextualization and management capabilities for

consumers, much more openness in the wireless

access market for the supply of mobile services, and

a technologically friendly environment for the

incorporation of new and revolutionary ideas in

wireless communications. It will demonstrate for

instance, the inherent full number-portability and the

disappearance of roaming charges. The work will

yield foundational contributions to global NGN

standardization work within ITU-T’s Future

Networks workgroup.

The UCWW is a big undertaking with huge and

complex international socio-economic implications

for the wireless communications business, and

encompassing the present and future rapid growth of

wireless communications and cloud-based

computing technologies. Our aim is to design a

context-aware middleware for the UCWW by

having most of its functions offered as cloud

services and the rest running locally on mobile

devices. In addition, we plan to create a set of

sample GUIs, which possess the necessary

intelligence to harvest the requisite information to

facilitate service predictions (Raskin, 2000). The

design and development of an efficient context-

aware middleware for the UCWW cloud requires

taking into account a number of aspects:

 On the back-end, the designed UCWW cloud

must facilitate the storage of data harvested

via mobile devices, and based on the analysis

of this data, offer predictions as to the

applicability and ABC&S suitability of

services to particular users. Over time the data

collected relating to particular users can give

an accurate view of particular cohorts, based

on common interests, repetitive access of

particular services, etc. By monitoring this

information, the system can accurately predict

the types of services most applicable to

individuals, and in turn, recommend these to

the users. Furthermore, efficient heuristic

algorithms must be investigated to facilitate

service utilization predictions locally on the

mobile devices or as part of the UCWW cloud

as an alternative to mining the stored data.

 The option of this UCWW cloud collaboration

with wireless billboard channel (WBC)

service providers (Flynn, 2006) holds

potential. Through it, consumers may have

their UCWW cloud distilled information,

relevant to their particular (or upcoming)

location and time, delivered to them in a

personalized frame through an appropriate

WBC.

 Within the client devices, an effective

functional design of the GUI must be

facilitated. With this in mind, different mobile

platforms will be targeted, particularly in the

case of the smartphones market, where

Android-based devices, iPhones, Windows

phones etc. each have a market share.

ACKNOWLEDGEMENTS

The authors wish to acknowledge the support of the

Telecommunications Research Centre (TRC), UL,

Ireland and the NPD of the Plovdiv University under

Grant No. NI11-FMI-004.

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