grid-enabled virtual organizations for next-generation learning environments

784 IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS—PART A: SYSTEMS AND HUMANS, VOL. 41, NO. 4, JULY 2011

Grid-Enabled Virtual Organizations forNext-Generation Learning Environments

Matteo Gaeta, Member, IEEE, Pierluigi Ritrovato, Member, IEEE, and Domenico Talia, Member, IEEE

Abstract—Nowadays, we are witnesses of a transformation inthe e-learning arena. This transformation has different driversinvolving all the actors in the learning value chain, from finalusers to learning institutions through technology providers. Allthose actors share a common goal: making the learning processesmore effective through the information and communication tech-nologies. This is happening through the promotion of a paradigmshift from content-centered to process-centered solutions. In thispaper, we present the results from the European Learning GridInfrastructure project concerning models, processes, and servicessupported by a service-oriented software architecture for creatingdynamic and adaptive virtual organizations for learning usingGrid technologies.

Index Terms—Grid, service-oriented architecture (SOA),technology-enhanced learning (TEL), virtual organizations (VOs).

I. INTRODUCTION

R ESEARCH literature is rich in examples of failure casesof e-learning initiatives in several contexts. The main

identified reasons are mostly related to the adopted approachand used technologies. Currently, teaching and learning prac-tices are mainly based on the information transfer paradigmfocused on content and on the authoritative key figure ofa teacher who provides information. This hydraulic view oflearning has found its perfect technical mirror in the “page-oriented approach to the Web” where the goal is to producemore and “better” static pages for the consumption of interestedstudents. E-learning is thus considered to be an activity whichhelps teachers to produce and students to consume multimediabooks over the Web. This paradigm has been popular in manye-learning projects, not because it is effective but owing to thefact that it is easy to implement with basic Internet facilities anddoes not require any change in the traditional roles of the actors.

In order to advance effective learning, current research trendspromote a shift from contents to processes focused on the

Manuscript received December 19, 2008; accepted March 25, 2009. Dateof publication May 12, 2011; date of current version June 21, 2011. Thiswork was supported in part by the European Commission through the Infor-mation Society Technologies (IST) program of the Sixth Framework Programfor Research and Technical Development—project European Learning GridInfrastructure—under Contract IST-002205. This paper was recommended byEditor W. Pedrycz.

M. Gaeta and P. Ritrovato are with the Department of Electronic Engineeringand Information Engineering, University of Salerno, 84084 Fisciano, Italy,and also with the Centro di Ricerca in Matematica Pura ed Applicata,84084 Fisciano, Italy (e-mail: [email protected]; [email protected];[email protected]; [email protected]).

D. Talia is with the Department of Electronics, Information, and Systems,University of Calabria, 87036 Rende, Italy (e-mail [email protected]).

Color versions of one or more of the figures in this paper are available onlineat http://ieeexplore.ieee.org.

Digital Object Identifier 10.1109/TSMCA.2011.2132714

learner, on socioconstructivist forms of learning with an exten-sive use of collaboration and cooperation among peers, and onthe definition and support of different pedagogies. In this ap-proach, the learner has an active and central role in the learningprocesses aimed at facilitating the construction of the learner’sknowledge and skills, instead of a simple memorization ofinformation.

Such new trends, according to [1], demand for new require-ments such as the following:

1) wide geographical distribution of learners and tutorswho can potentially belong to many different educationalinstitutions;

2) multiple administrations from different organizationswith specific educational policies;

3) access from anywhere, on any learners’ computerplatform, and on any software;

4) support for a growing load of learning resources, services,and users who access resources and services;

5) transparent access and share of a huge variety of suchsoftware and hardware learning resources and services indynamic environments;

6) flexibility to reuse pieces of learning resources andservices of different granularities according to specificneeds;

7) support to the autonomous and dynamic creation of com-munities through the application of the virtual organiza-tion (VO) paradigm;

8) learning personalization and knowledge creation, acqui-sition, and evolution.

These requirements represent a great challenge for the tra-ditional software platforms and available tools but may be ful-filled by relying on distributed paradigms like the Grid. On theother side, as we will see, the Grid must be complemented withother technologies in order to be fully effective in supportingtechnology-enhanced learning (TEL) environments.

The Grid [4] and related evolutions [5], [6] are unanimouslyrecognized as the enabling technology for large-scale infras-tructure supporting “coordinated resource sharing and problemsolving in dynamic, multi-institutional virtual organizations”where the focus is on the concept of VO. This leadership,as reported in [7], is also confirmed by the large numberof research projects funded in Europe (Enabling Grids forE-sciencE), the U.S. (TeraGrid), Japan (National Research GridInitiative), India (GARUDA), and South America (E-sciencegrid facility for Europe and Latin America).

More recently, projects like Business Experiments in GRID(BEinGRID) (www.beingrid.com) and Business objective

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GAETA et al.: GRID-ENABLED VIRTUAL ORGANIZATIONS FOR NEXT-GENERATION LEARNING ENVIRONMENTS 785

driven Reliable and Intelligent Grid for real busiNess (BREIN)(www.eu-brein.com) are demonstrating the effectiveness ofthe adoption of Grid technologies in industrial and businesscontexts.

It is also worth mentioning the ERINA study (recommen-dations for Exploiting Research INfrastructure potential in keyAreas) proposed by the European Union (EU). The study aimsat investigating the use of a Grid-enabled research infrastruc-ture in three business contexts: e-learning, e-government, ande-health. The results are particularly encouraging with respectto e-learning: 1) seamless access to a wider market space oflearning resources; 2) mobility of teachers and students; and3) support in the creation of personal learning spacesfor the lifelong learning. Moreover, e-Learning is also“- Infrastructure-ready” and several services may be promptlybrought on top of the e-Infrastructures with sustainableperspectives.

As a follow-up of the EU–U.S. Cooperation Program onScience and Technologies for Learning established in 2001,where the main ideas of use of Grid for Learning were born,a special interest group (SIG) of the European Network ofExcellence “Kaleidoscope” has been defined. The Grid forLearning SIG aims to survey the field and to foster discussionsamong research groups spread in Europe on Grid applicationsto TEL. One of the results of these discussions is the definitionof the Grid for Learning: A Grid for Learning is an enablingarchitecture based on three pillars: Grid, Semantics and Edu-cational Modelling allowing the definition and the execution oflearning experiences obtained as cooperation and compositionof distributed heterogeneous actors, resources and services.

This paper aims at reporting the experiences and resultsachieved in the context of the European Learning Grid Infras-tructure (ELeGI) research project [2], [3] concerning the use ofGrid technologies for the creation of dynamic VOs for learning,where new advanced and personalized learning environmentsare created through the definition of virtual learning communi-ties (VLCs) by paving the way for a new approach to learningfrom both the didactical and pedagogical points of view.

A. Related Works

In the following, we outline the most recent and significantworks concerning the use of Grid technologies for learning.

The Grid-service-based portal for virtual learning campus[8] developed an environment that makes use of the Gridcapabilities so as to make the dynamic sharing and coordinationof heterogeneous resources possible, which are distributed onthe infrastructure. The project focuses on the development ofa video digital library based on Grid for a virtual campus thatallows easy access and implementation of several services. Inspite of being a project that aimed to take advantage of thecapabilities that Grid technology provides, it is limited to aunique type of educational resources, like video, which a setof services is developed for.

In [9], a TEL platform is described, which bases on Grid ser-vice technologies. In this platform, the supply of virtual learn-ing services designated for students, instructors, and coursesuppliers is provided through a Grid infrastructure, allowing

ubiquitous access to information and taking advantage of thepotentiality of computer systems. Together with ELeGI, this isone of the first attempts that have recourse to the use of Gridresources. Moreover, it dictates the need for the developmentof a semantic model description that enables a more completedescription of learning resources.

ULabGrid [10], an infrastructure to develop distant labo-ratories for undergraduate students over a Grid, proposes anew architecture that allows the educators to design remotecollaborative laboratories for university students using the Gridinfrastructure through the Globus toolkit. This project is oneof the first in its type to try to combine the facilities providedby the Grid in a practical scenario in order to achieve resourcesharing and to motivate collaborative work. In this sense, thedesign of Grid-based collaborative learning scenarios should besupported by semantic descriptions that allow the best trackingof resources available in the network.

A further work proposes an agent-based robust collabora-tive virtual environment for TEL in the service Grid [11]. Inthis virtual environment, all Web resources and services areaccessed via service encapsulation, which may result in a morescalable and robust collaborative learning architecture. A veryremarkable aspect of this work is the way it uses to implementcomplex services from more basic ones, without using anysemantic description to facilitate the automatic composition ofcomplex services from lower level ones.

KGTutor, a knowledge-Grid-based intelligent tutoringsystem [12], proposes a model for the construction of intelligenttutoring in a more pleasant and effective way. The KGTutoris designed to provide better support to student-centered dis-tributed learning. Students’ characteristics, such as previousknowledge and learning styles, are used to choose, organize,and deliver learning materials to individual students. During thelearning process, the system can also provide objective evalu-ations and customized suggestions for each student accordingto his/her learning performance. This system provides a veryimportant work as far as student-centered learning is concerned,although it could be further strengthened through the use ofaspects of semantic description of learning services.

In [13], a Grid service framework for metadata managementin self e-learning networks (SeLeNes) demonstrates how themetadata use can be critical for Grid systems. More specifically,the semantic description constitutes a very beneficial extensionof Grid environments. The SeLeNe is used as a test applicationwhile a set of services is proposed which are implementedwith Open Grid Service Architecture (OGSA) [6]. The projectfocuses on providing services that use learning object metadata.These services are sufficiently generic so that they can beused by other Grid-based systems which need to make use ofsemantic descriptions.

The Semantic grid-based E-Learning Framework (ELF)(SELF) project [14] proposes a learning environment thatresults from the integration of several technologies, specifi-cally Semantic Web, Grid technology, collaborative tools aswell as customized tools, and knowledge management tech-niques. SELF provides a mechanism for the intelligent searchof services leveraging on semantic description tools. Thisproject presents an important reference to the use of different


technologies for the development of Grid-based learning sce-narios, even though the definition of its tools is not based onmodels of semantic description.

OntoEdu [15] is a flexible platform for online learning whichis based on diverse technologies like ubiquitous computing,ontology engineering, Web semantics, and computational Grid.It is composed of five parts: user adaptation, automatic compo-sition, educational ontology, a module of services, and a moduleof contents. Among these parts, the educational ontology isthe principal one. The main objectives of OntoEdu are meantto obtain reusability of concepts, adaptability for users anddevices, automatic composition, and scalability in functionalityand performance.

In [21], a workflow framework for the pervasive learningobject composition through the adoption of a Grid service flowlanguage is presented. The learning objects are distributed inheterogeneous environments which have been used in order toallow effective collaboration and reuse of learning objects; thisfact can help users learn with no limitations of time and space.

In the work referenced as “Semantic Search of Learning Ser-vices in a Grid-Based Collaborative System” [17], the authorshave constructed an ontological description for collaborativework tools that allow the user to make a manual search ofdiverse resources that these tools provide within a Grid en-vironment with minimum of technical knowledge. This workproposes a Grid-based tool called Gridcole, which can serve asa basis to implement different conceptual approaches of Grid-based semantic description of learning services, thus extendingand endowing it with an innovative, pervasive, and ubiquitousprojection.

Another relevant work on the investigation about the useof a Service Oriented Architecture (SOA) for e-learning isrepresented by ELF [18] developed in the frame of Joint In-formation Systems Committee (JISC). The JISC ELF providesa service-oriented factoring of core services required to supporte-learning applications, portals, and other user agents. Thebenefits for a learning community which adopts a service-oriented framework approach to the infrastructure development,and additional activities required to produce these benefitsare analyzed in [19]. In particular, the benefits concerningpolicy makers, organizations that deliver and manage learn-ing/training, suppliers and developers of e-learning services andcontent, and communities of practice are analyzed.

From the analysis of the state of the art, a new way toconceive the learning clearly emerges. The attention is shiftedfrom a strictly concept-oriented “teaching” to the user-centered“learning.” This shift asks for new technologies and approachesand highlights, at the same time, the following lacks:

1) mix of diverse technologies for addressing specific issues:difficult to dominate and to harmonize them in general-purpose e-learning solutions;

2) traditional use of Grid technologies: difficult to port clas-sical, computing-centered, and e-science scenarios in thee-learning context;

3) lack of a reference architecture where models, tech-nologies, and approaches are harmonized in a business-oriented way.

In the following sections, we present our approach adoptedto counter the aforementioned lacks and to demonstrate theeffectiveness in concrete scenarios.

II. VO AND VLCs: THE ELeGI VISION AND APPROACH

The new approach to learning finds lifeblood in the Web2.0 wave [20]. Within this new form of learning, technologieshave to support the creation of highly dynamic personalizedand distributed virtual environments, where different actors areallowed to provide resources and services, and well-definedlearning processes are consumed in a personalized, collabora-tive, and ubiquitous way [21].

As an answer to these new challenges, the ELeGI project hasbeen proposed. ELeGI was an integrated project funded by theEuropean Commission (February 2004–June 2007) and con-ceived in order to provide a solution to this new approach—asolution which makes use of learning models and related pro-cesses for the formal/informal learning, coupled with a softwarearchitecture based on Grid technology for the creation of adynamic and service-oriented infrastructure enabling VOs forlearning.

To achieve our learning vision, we need to create dynamicand contextualized environments for each learner (taking intoaccount his/her aptitude and social context, as well as providingtutoring and an enhanced presence), which can continuouslysupport him/her during the learning process.

From the organizational, infrastructure, and business point ofview, our vision considers two key abstractions: VO and VLCs.In the following, we will introduce, describe, and motivate bothabstractions.

A. VOs

In the ELeGI context, the VOs are a natural way to model,represent, and consume e-learning business processes. It isworth mentioning that the basic idea which suggested us toinvestigate the adoption of the VO for e-learning is to allowthe creation of a distributed learning environment where dif-ferent educational institutions, individual learners, tutors, etc.,can easily access and share computational and educationalresources.

According to the ELeGI Learning Model [22] and relatedbusiness implication, one of the key features is the continuousadaptation of the learning processes (in terms of resources, ser-vices, etc.) in order to accommodate the learner’s preferences(aptitudes, learning context, preferred learning style, progres-sions, etc.). This continuous adaptation cannot be achieved us-ing monolithic and product-centered solutions. On the contrary,it requires the creation of dynamic service-oriented environ-ments. Hence, we conceive the Grid in the learning domainas an enabling technology for “coordinated resource sharingand problem solving in dynamic, multi-institutional virtualorganizations, as proposed in [5].

In defining the VO, we have also taken into account someprocesses according to which the resources are accessed andorchestrated and business implications are considered. For thisreason, the participation into a VO is, usually, negotiated among


Fig. 1. VO creation from VBE.

members of a more static organization, called network ofenterprises or virtual breeding environment (VBE) as definedin the context of the European Commission-funded VirtualOrganisation cluSTER and European Collaborative NetworkedOrganizations Leadership Initiative (ECOLEAD). A VBE rep-resents an association or pool of organizations and their relatedsupporting institutions that have both the potential and thewill to cooperate with each other through the establishmentof a “base” long-term cooperation agreement and interoperableinfrastructure.

The dynamic behavior, pointed out previously, is reallyuseful for our purposes. The VBE can be constituted by educa-tional institutions, research centers, users associations, profes-sionals, etc., having potentialities to cooperate for educationalpurposes and creating a VO when a collaboration opportunityis identified by one of them.

The advantages coming from this approach for all the actorsinvolved in the VBE are evident. An institution can negotiateon demand the provision of computational/data resources andservices to run interactive scientific experiments as well asthe sharing of applications, instruments, and services so asto improve the realism of learning experiences. The learnercan ask for specific services to search for and create peers todiscuss with on specific issues (matchmaking), or take note ofthe discussion collaboratively (through the “on-the-fly” instan-tiation of a wikilike service and related Web-based distributedauthoring and versioning repository) and meet them throughvideoconferencing facilities.

To clarify the relationships between a VBE and a VO, inFig. 1, we present the picture from the ECOLEAD project thatgraphically shows how the VO creation process starts a VBE.

It clearly appears from the picture that a key driver for theVO creation is the collaboration opportunity. This can be ascientific or a business opportunity or, as in our VLC case, anopportunity based on educational needs of a group of students.

Furthermore, as said, the strategy represents a key differencebetween a VBE and a VO. VBEs are groups of organizationswhose agreements are based on a long-term strategy. Think,for instance, of a VBE as a collaborative network of all Italianuniversities cooperating among them with a clear long-termstrategy. Whenever a small number of them should identifya collaboration opportunity, they could form a VO, sharing

resources and knowledge for a common objective. Eventually,another key aspect of the VO creation from a VBE is thepreparedness of the VBE members. When the window ofopportunity is short, it would be necessary in order to supportrapid formation of VO that potential partners are ready for sucha collaboration. Preparedness includes common interoperableinfrastructure, common operating rules, and common coopera-tion agreement.

In addition to the aforementioned aspect (i.e., in our ap-proach, VO is created from VBE), another distinctive aspectof our approach is the separation of issues related to the man-agement of the enabling infrastructure from those concerningthe management of VO’s business processes. In our vision,it is desirable to learn in a simpler and natural way, using“high-level abstractions” (e.g., models, learning activities, andexperiments) that should be shared among all the participants.With the adoption of both VO paradigm and Grid technologies,we also foresee benefits of dematerialization of Informationand Communication Technology infrastructure, which means tominimize the overhead, also in terms of costs and managementof the shared distributed infrastructure where learning experi-ences can be deployed. This context allows our concept of VLCto come up and live.

This idea is currently under investigation also by other re-searchers in the field of learning. It is the case, for instance,of the learning network (LN) concept proposed by Koper andSloep [23]. In the report “Lifelong Learning in a Network,”the authors define “A Learning Network for Lifelong Learning(LN) is a network of distributed persons and organisationswho create, share, support and study learning resources (‘unitsof learning’) in a specific knowledge domain. These networkssupport the seamless, ubiquitous access to learning facilities atwork, at home and in schools and universities.”

Indeed, the feature that distinguishes the two concepts of“organization” is that the LN proposed in [23] can be con-sidered as an example of the VBE (more static) while a VLCarises when an opportunity to collaborate in order to achievea more specific educational goal is identified (more dynamicand transient). Another distinctive key feature of our approachlies in the definition and development of a state-of-the-artdistributed software architecture, based on the Grid technologyas described in [24].

B. VLCs

Currently, there are several definitions of VLCs, each of thememphasizing one aspect instead of others. All the definitionshave, in any case, a common root in the concept of virtualcommunity characterized by interaction, dynamism, and pur-poseful aspects. Another characteristic common to the variousdefinitions of VLC is the role played by those technologiesaiming at enabling and supporting the life inside a community,even though, in some cases, the technologies could also act asa barrier.

A definition of VLC that embraces a social constructivistinterpretation of learning and, hence, is very close to theELeGI’s vision of learning is provided by Schwier in [27]:“A virtual learning community is a particular type of virtual


Fig. 2. ELeGI software architecture.

learning environment. For a community to emerge, a learningenvironment must allow learners to engage each other inten-tionally and collectively in the transaction or transformation ofknowledge. It isn’t enough that material is presented to peopleand they interact with the instruction. It isn’t enough that thelearners interact with instructors to refine their understandingof material. Instead, for a virtual learning community to exist,it is necessary for individuals to take advantage of, and in somecases invent, a process for engaging ideas, negotiating meaningand learning collectively.”

Starting from this general definition, we define a VLC asfollows: a set of people and institutions that communicate/collaborate/cooperate in order to achieve a common educationalgoal by sharing a set of high-level learning abstractions (e.g.,models, ontology, and educational languages), processes, andservices as well as infrastructural resources.

From the ELeGI’s point of view, a VLC basically representsan instance of a VO for the e-learning domain. This is themain reason that our effort has been devoted to identify allthe required models and functionalities to allow the businessprocess management (i.e., in our case, learning processes) inthe operation phase of a VO.

In particular, through the VO and leveraging on Grid tech-nologies, we will represent all aspects related to the infrastruc-ture operational management (like the information technologyinfrastructure of modern enterprises), while through the VLC,we will present all aspects related to the business processmanagement (definition, enactment, etc.).

III. ELeGI SOFTWARE ARCHITECTURE

Fig. 2 shows the ELeGI software architecture. The architec-ture has been designed and developed: 1) taking into accountthe general learning model described in [22] that allows us toobtain a solution that is flexible with respect to pedagogies and2) on top of service-oriented Grid technologies.

The ELeGI software architecture can be considered as aframework for the development of e-learning applications. Infact, we provide both a rich set of available services and alsoskeletons, practices, and procedures supporting the construc-tion of solutions for the definition, creation, and delivery oflearning experiences. For instance, ELeGI states that serviceshave to adopt some Web Service (WS) standards (such asWS Resource Framework (WSRF), WS for Remote Portlets(WSRP), WS-Manageability, etc.) and also to implement driverinterfaces (drivers are services used to virtualize the educationalresources).

In order to speed up the implementation, we made recourseto the Grid Application Service Provision (ASP) (GRASP)middleware [28] and to the Grid-aware (GA) version of aninnovative learning platform named Intelligent Web Teacher(IWT) [29] for the implementation of Grid layer services andVLC layer services, respectively.

Before entering into details about the description of the Gridlayer, we provide some information on the process followed forthe ELeGI software architecture design.

A. Design Process

Our starting point is a theoretical framework composed ofmodels and processes, described in [22]. Starting from thisapproach, we can obtain a solution that is flexible with respectto the pedagogies, rather than to design a solution which iscloser to a specific pedagogical approach.

A further issue driving our approach arises from an optimiza-tion attempt concerning the setting of suitable dimension ag-gregations having “minimal” external interactions. This meansthat we found difficulties in adapting the traditional three-tiered architecture schemas to the ELeGI software architecture.To this purpose, we performed a classification of processesbelonging to the theoretic framework that have been furtheranalyzed.


Fig. 3. Layered classification of ELeGI processes.

Aside from the ones coming from a theoretical framework,other processes have been identified in order to support theprevious ones, and a set of user-related processes (knowledgerepresentations authoring, complex learning object authoring,learning experience delivery, etc.) has been identified to havea comprehensive view of the ELeGI formal learning platformand to drive a correct definition of the ELeGI formal learningservice interfaces.

In the following, we outline the approach followed for thedesign of the overall architecture. From a graphical point ofview, the following picture presents a classification of theidentified processes.

Before going deeper into details with the explanation ofdifferent phases of our design approach, we would like to statethe following definitions.

1) Processes of layer 1 represent macrofunctionalities pro-vided to users through graphical user interfaces (GUIs).

2) Processes of layers 2 and 3 come from the definedtheoretical framework and are realized by a subset ofsubsystems of the ELeGI formal learning architecture.

3) Processes of layer 4 are considered infrastructure pro-cesses provided by existing middleware.

4) Processes of layers 2 and 3 are decomposed into fine-grained functionalities.

5) Architecture subsystems have to be decomposed into ser-vices (one or more) grouping fine-grained functionalitiesthat come from processes of layers 2 and 3.

The approach that we adopted in the design consists inanalyzing the processes layered in Fig. 3 and decomposingthem into fine-grained functionalities that can be classifiedinto intralayer (invoked inside the same layer) and interlayerfunctionalities (invoked across layers).

The classifications of the ELeGI formal learning processesare the following.

1) Authoring-related processes (layer 1a)—all the pro-cesses controlled by means of GUIs and regarding the au-thoring of knowledge structures (macro-ontology, genericcontextualized ontology, context profile, etc.), learningobjects (and/or content without explicit didactic value),and didactic model structures.

2) Learning-experience-related processes (layer 1b)—allthe processes controlled by GUI and regarding the man-agement of learning experiences. For instance, teacherscan assemble learning experiences packaged as units oflearning (UoLs) and populate them. Learners can executea learning experience coming from a UoL.

3) Learning-related processes (layer 2)—these are themain processes of ELeGI (i.e., the ones coming di-rectly from the theoretical framework [22]) and includeall processes offering support for user-interaction-relatedprocesses at layer 1. At layer 2, we have the following:1) Knowledge Building Process; 2) UoL Building Pro-cess; and 3) UoL Delivery Process.

4) Environment-related processes (layer 3)—the pro-cesses at this layer provide environments sustaining thelearning experiences (learners’ enrollment, users’ groupcomposition, metadata-based discovery of content, andso on).

5) Grid middleware processes (layer 4)—OGSA com-plaint processes for managing the service-oriented infras-tructure (e.g., discovery, instantiation, notification, etc.)

In order to identify and design the ELeGI VCL services(within subsystems coming from the software architecture) andtheir interactions, we started from the analysis of all processesat layers 1, 2, and 3. In particular, the design activity goesthrough the following three phases: 1) analysis of layers 2and 3; 2) analysis of layer 1; and 3) analysis of serviceinteractions.

B. Grid Layer: Enabling the VO Creation

The Grid layer provides a set of services for the infrastructureand VO operational management. It is based on the WSRFversion of the GRASP middleware [28]. In the GRASP project,our objective was to develop a Grid middleware for the nextgeneration of ASP, where services are provided by differentindependent organizations, so we addressed issues related totransparent hosting and management of applications.

GRASP explored the use of WSs as a means for providinga timely and effective technological basis supporting the


Fig. 4. GRASP pillars.

evolution of ASP market toward a sustainable utility computingmodel.

Fig. 4 shows a graphical view of the three key pillars ofGRASP.

The GRASP core capabilities are the following:

1) service location: process of automatically discovering thelogical location of services;

2) (dynamic) service instantiation: process of dynamicallycreating (potentially transient) ready-to-use instances ofservices within a VO, selecting the most appropriatehosting environment (HE);

3) (service) task-based interactions: how to support and tomanage necessary interactions for executing a serviceinstance;

4) service orchestration: coordination of subservices collec-tively executing a complex business workflow;

5) service level agreement (SLA) management: SLA tem-plates used for selecting an appropriate HE, monitoring ofservices to ensure compliance, and mapping of monitoreddata to SLA concepts;

6) accounting: collection of raw performance/resource data(shared with SLA monitoring);

7) billing: merging different costing methods and applyingpricing algorithms;

8) application security: securing complete application ser-vices handling securely the VO lifetime, including inclu-sion and expulsion of component Grid service instancesthat collectively execute the application.

C. VO Formation and Life-Cycle Management

Concerning the VO dynamic formation and management,GRASP middleware provides two basic services: VO Set-upand Application Virtualization (implemented in the context ofthe BEinGRID project).

1) VO Set-up: The VO Set-up is a WS that is providingfunctionalities to support the VO life cycle, particularly thephases of VO identification and formation, where members of

the VO have to be identified and a circle of trust among themhas to be created.

The component allows the management of VO-related reg-istries and secure federation life cycle. In terms of functionali-ties, the main ones are the following:

1) secure federation life-cycle management in a business-to-business environment;

2) member, policy, and role management;3) selection of VO members on the basis of capabilities that

they can offer;4) management of VO registries (VO member registry and

VO service instance registry).

The design and development of this component are motivatedby business scenarios where there is the need for a solutionallowing to publish/discover enterprises and capabilities andto create secure federation among autonomous administrativedomains.

The VO Set-up component presents several benefits anddistinctive features such as the following:

1) adoption of standards—the component is based onenterprises’ widely adopted standards such as WS-Interoperability; Universal Description, Discovery, andIntegration (UDDI); and Security Assertion MarkupLanguage (SAML);

2) extensibility—it is very easy to add new criteria forpartner identification and selection;

3) ability to associate trust relationships with a businesscontext;

4) agility in responding to new needs/requirements and im-proved time to market (by setting up a VO when a newopportunity arises);

5) dealing with geographical and organizational distributionof teams.

The component is useful in several concrete scenarios, wherethere is a low level of dynamicity in the VO creation process(meaning that other steps of the creation process, such as agree-ment negotiations and policy definition, may be performedoffline) and where potential partners of a VO already know eachother perhaps due to previous collaboration. This case is reallysimilar to the VBE concept previously explained.

The VO Set-up assumption, in fact, is that the selection ofpotential members of a VO happens on the basis of capabilitiesthat they can bring in the new collaboration and the associatedquality of services. This requires the presence of a yellowpage registry from which the VO initiator can select and invitepotential members. The approach followed by the VO Set-up component is borrowed by the one proposed in [37]. Inparticular, our approach is linked to the so-called service-market-based or service federation approach. According to thisapproach, the potential collaborative behavior of each companyis “materialized” by a set of services, and the VO members areconsidered as service providers (SPs).

The approach assumes the existence of an entity that keeps acatalogue of services where SP companies publish their serviceofferings (that is the yellow page previously mentioned).

Another added value of the VO Set-up is that, in contrast tothe current state of the art, which is mainly based on results


Fig. 5. Application Virtualization.

coming from the efforts of the e-science community (e.g., VOmembership service [32]), the solutions proposed take intoconsideration needs and requirements of the business world.This aspect has a deep impact on the design and implementationof the proposed software components.

In fact, while most of the e-science solutions proposeand implement coarse-grained models to address issues re-lated to membership and management of resources in a VO(for instance, allowing the access to a whole resource for jobsubmission), in our case, we have requirements that foreseea fine-grained approach (for instance, allowing the access tospecific capabilities offered by an SP) demanding, thus, asolution supporting flexible integration and appropriate accesscontrol (AC) models such as the one reported in [33] for virtualenterprises.

The main benefits relate to the federation part of the compo-nent. These allow, on the one hand, to manage the life cycle ofcircles of trust between providers, and therefore the life-cyclemanagement of federation of trust realms and, on the otherhand, to manage the life cycle of identities and privileges ofusers and resources within such federations of trust realms.

The obvious benefits include the following:

1) facilitating the creation of communities of identityproviders that enable identity brokerage and managementby supporting open standards such as Liberty Alliance,SAML, and WS-Federation, and therefore giving rise tonew means of revenue generation;

2) enabling the customer to choose the identity provider thatis more appropriate for a specific collaboration instead ofbeing locked into what is incorporated in their SOA plat-form by some middleware vendor or instead of departingin expensive product integration projects that give themidentity provision and federation, at a very high cost, forthe specific application at hand.

2) Application Virtualization: This component provides away to integrate and expose application capabilities through a

single access point that is configured to manage their executionand forward requests to the application capabilities.

In a VO, in fact, there can be the need to expose applicationcapabilities, for direct usage or for composition, as network-hosted services in order to avoid direct and unmanaged accessof VO members to VO resources.

It is appropriate to use this component when there is the needto do the following:

1) decouple service access logic from the rest of theapplication;

2) hide the complexities of accessing a service from theapplication;

3) have a single point providing common management;4) avoid direct access to resources.

Fig. 5 shows a high-level diagram of the component.The Application Virtualization component follows the façade

pattern by Gamma et al. [34] and is in charge of invokingother classes of the system in order to execute the virtualizationprocess.

Application Virtualization, Runtime Monitor, and Manage-ment Service can iterate (in some way) the observer pattern.Management Service instances notify the Runtime Monitorwith updates of some parameters, and Runtime Monitor cannotify violation to Application Virtualization.

If the Application Virtualization component is also the gate-way (single access point to the GRASP virtual HE), when arequest for accessing a service arrives, the Application Virtual-ization can operate according to the chain of responsibility [34]and pass the request along a chain of handlers. The involvedbuilding blocks are as follows.

1) Application Virtualization—this implements the virtu-alization process steps. It delegates requests to appropri-ate subsystem objects. It returns the client a referenceto access the created application instance through thegateway. It can be configured to be the gateway, and whena request for accessing a service arrives, it can pass therequest along a chain of handlers.


Fig. 6. Interactions among services of a GRASP VO.

2) Endpoint Reference Mapping—this is in charge ofmapping the endpoint reference (EPR) of created appli-cation service instances to the EPR of the gateway. It isalso in charge of activating and deactivating applicationservice instances if, respectively, the process creation andtermination of service instances succeed.

3) Policy and Rules—this is in charge of applying thepolicies and rules associated to the application serviceinstance.

4) Runtime Monitor—this is in charge of collecting man-agement information of application service instances. Itevaluates the execution of application service instancesagainst parameters of contracts associated to it. It notifiespossible violations.

5) Registry—a registry of the created application instances.6) Management Service—this notifies the Runtime Moni-

tor about changing of status of some application serviceinstance parameters.

The obvious benefits include cost reduction, operationalmanagement risk mitigation through outsourcing, and reducingtime-to-market timescales.

In addition, the Application Virtualization offers to thecustomer (i.e., application SP) the ability to select amongcompeting offerings of infrastructure services such as identityproviders and access and policy management SPs. Such a

choice offers to the customer, on the one hand, the potential toavoid to be locked into investing in proprietary SOA solutionsthat fit a market sector but are not good for another.

D. VO Deployment Using GRASP

From the infrastructure and deployment viewpoint, a VOconsists of a set of independent administrative domains, calledHEs that share services and resources to achieve a commongoal. The VO may be formed by multiple HEs, and each ofthem may have multiple hosts. In this way, we can hide/protectresources inside the HE providing some access points.

Fig. 6 graphically shows the structure of a VO with internalroles and interactions between roles. The internal roles areshaped like rectangles while the relations between internal rolesand entities (e.g., service instance and service directory) aredrawn using dashed lines. The clouds containing “i” insiderepresent an information service that can be distributed in thewhole VO and can retrieve information on physical resources[30] and, according to recent research works [31], on a poolof virtual resources. Moreover, the results provided in [31]provide a concrete contribution to the paradigm shift from Gridcomputing toward the cloud one.

A VO foresees at least one service locator in order to findinside the VO the SP that is able to satisfy the service requestorrequest. The service requestor interacts with the HE suitable


Fig. 7. Service interaction flow.

to provide a required service/resource. Of course, an SP couldbelong to a HE as well as to a service requestor. Roles aredynamic and not assigned a priori.

E. VLC Layer: Management and Business Services

This layer can be logically divided into two sublayers, asshown in Fig. 2—ELeGI software architecture. The first oneis the VLC Management Service sublayer. It provides servicesand tools to support the creation, operation, evolution, andmaintenance of a VLC. The most important subsystem of thislayer is the VLC Management subsystem, offering functional-ities for VLC Administration, VLC Policy Management, andVLC Member Profile Management. This layer also providesfunctionalities for semantic annotation, discovery, and com-position of educational contents and services, functionalitiesallowing asynchronous and synchronous communications.

The second one, namely, the VLC Business Service sublayer,provides services and tools to support the execution of learningprocesses. Of course, there are services and tools to createand manage Ontology, Learner’s Profile, and Didactic Modelthat represent the three basic structures of the ELeGI LearningModel [22]. The Personalization subsystem aims at dynami-cally adapting and delivering educational contents and services,matching the learner’s needs and preferences according tohis/her profile [25]. The Learning Experience Management sub-system allows applications or other services to access and man-age courses, modules, and other learning experience, while theContents and Services Orchestration subsystem deals with is-sues of execution of workflow of learning activities that are de-scribed using IMS Learning Design (IMS-LD) constructs [26].

IV. CASE STUDY: CREATION AND DELIVERY OF A

PERSONALIZED LEARNING EXPERIENCE IN A VLC

The case study that we describe here relates to the creationand delivery of a personalized learning experience, about Tor-ricelli’s law, in a VLC.

For the case study, a VLC has been instantiated creating threedifferent HEs on three members’ hosts of the VLC that are

geographically distributed among Italy (Centro di Ricerca inMatematica Pura ed Applicata (CRMPA) in Salerno), Germany(Ruhr-Universität Bochum (RUB) in Bochum), and the U.K.(Knowledge Media Institute (KMI) in Milton). On each HE,different ELeGI services have been deployed.

Each node of the VLC is a HE (Fig. 7). In the case study,CRMPA (Salerno) takes the role of a learning experienceprovider that is able to provide personalized learning experi-ences. According to the ELeGI Learning Model, a learningexperience is created reusing several assets (such as educationalresources and services) that are dynamically bound at runtimeinto a workflow of learning activities described using IMS-LDspecification).

To personalize the learning experience, CRMPA works ontwo distinct and complementary levels. The first is a pedagog-ical level, meaning that personalized learning paths are createdon the basis of a learner’s knowledge, didactic models, andlearning styles. This is achieved using personalization service.

The second level is instead a selection of suitable resources(contents and services) to be dynamically bound into learningactivities. For this second aspect, CRMPA has to negotiatethose contents and services with other providers namely KMI(providing an enhanced presence service) and RUB (offering asimulation engine as well as computational resources to run thesimulation).

In the context of this paper, we are mainly interested inpresenting the findings linked to identification and formationphases of a VLC (e.g., membership identification and selection)and to the operational phase in terms of services’ interactions inorder to deliver the personalized learning experience (businessprocess of our VLC).

Indeed, the case study has also proven other relevant ELeGIresults such as the methodology that we defined to personalizethe learning experience [35].

A. Identification and Formation of the VLC

When the CRMPA HE receives a request for provision ofa personalized learning experience about Torricelli’s law, it


Fig. 8. Service interaction flow.

foresees a collaboration opportunity with other known organi-zations and decides to trigger the creation of a VLC.

CRMPA, KMI, and RUB are members of a VBE, andthey are registered into a catalogue, together with potentialresources/services/contents that they can provide.

The learning activities’ workflow is first personalized at thepedagogical level for a specific learner. This results in the defi-nition of a learning path suitable to explain the Torricelli’s lawand in the inclusion of metadata describing suitable contentsand services (in our case, the learner profile says that she prefersexperientially based approaches, in the context of a highereducation course, leading to the necessity of a simulation andenhanced presence service for tutoring). Those metadata arematched against the description of providers into the catalogueso that potential collaborators may be identified.

From a technological viewpoint, this has been performedusing UDDI as a catalogue and defining a suitable categoriza-tion schema that is able to help match services and contentsrequired in the workflow with the ones potentially offered bythe organizations.

After the identification, CRMPA starts the negotiation ofSLAs with the two identified providers (RUB and KMI). Whenan agreement is reached, the three organizations finalize theVLC formation. This means that, as members of the VLC,through the membership and role management service, they areregistered together with their roles and capabilities into a VLCregistry.

B. Operation Phase of the VLC

The goal of the created VLC is to deliver a personalizedlearning experience to explain Torricelli’s law. The workflow oflearning activities is parsed by a Content and Service Orches-trator that is able to enact the learning activity flow. In ELeGI,this service is based on the well-known CopperCore engine forIMS-LD, modified in order to understand the service descrip-tion schema needed for the dynamic binding of resources at

runtime, using the Grid middleware capabilities as describedin [35].

The Content and Service Orchestrator interacts with GRASPmiddleware services in order to localize and instantiate, in aubiquitous and seamless way, educational resources and ser-vices needed for the learning activities (steps 2 and 3 in Fig. 7).

When the learner starts the learning activity that includessimulation execution, the mathematical model describingTorricelli’s law (VCLab educational resources, formalized in aMatlab file) is localized using learning metadata services (steps4 and 5 in Fig. 8), accessed through Data Services and trans-ferred to the RUB node that provides the VCLab engine (VirtualLaboratory for Automatics and Control Engineering, basedon Matlab, provides students with easy access to engineeringapplications anytime and from any computing environment)and computational resources to execute the simulation (step 7in Fig. 8).

The learner, during the learning experience, can require atutoring session via the enhanced presence service based onBuddySpace (an advanced and enhanced presence instant mes-saging service) deployed at the KMI node. The Globus Toolkit4 Grid middleware is used on this node.

C. Test Scenario Execution

Performance testing on the ELeGI deployment infrastructure(where some of the elements are described in Table I) has beenexecuted.

The results are particularly encouraging in spite of the use ofseveral virtual machines: the prototype nature of software andthe use of several already existing applications like IWT (learn-ing content management system), GRASP (Grid middleware),CopperCore (Content and Service Orchestrator), and VCLab(virtual experiment simulation), to mention only a few.

For many of the tested scenarios, the infrastructure demon-strates a high level of robustness and, in general, a goodscalability.


TABLE ISOME ELEMENTS OF THE ELeGI DEPLOYMENT INFRASTRUCTURE

Fig. 9. Learning experience delivery scenario test.

Fig. 9 shows the test results in executing the learning ex-perience delivery scenario. The components engaged in thisscenario are as follows: IWT-GA IMS-LD Player and itsWSRP.Net Consumer, CopperCore environment and services,learning experience management service for the UoL retrieval,and VCLab engine service and related driver together withits WSRP.Net Producer. As explained previously, the VCLabdriver is discovered and instantiated using the Grid middleware.

It is worth mentioning that, in the scenario execution, notonly the VCLab driver is discovered and instantiated (on the

fly) through the Grid middleware but also the VCLab’s resourcedelivery is also performed including the Matlab execution of the3-D experiment code (Torricelli’s law resource), together with,approximately, a hundred messages among services exchangedin the infrastructure.

V. CONCLUSION AND FUTURE WORKS

The ELeGI project experiences and results have shown thecapabilities provided by a service-oriented Grid-based soft-ware infrastructure for supporting the creation of personalizedand adaptive process-centered and pedagogy-driven distributedlearning environments modeled through VOs.

With respect to the VO operational phases, we have proventhe benefits of Grid technologies in terms of dynamic localiza-tion and run-time binding of educational resources and servicesas well as the adaptation of learning experiences to both learnerbehavior and context.

The approach adopted to identify the VLC members is quitesimple but effective. Furthermore, the idea of exploiting a cat-alogue where providers can publish their offers is aligned withthe current state of the art. In [36] and [37], in fact, some R&Dapproaches to create a VO are described. Among those, we areclose to the so-called service market based on service federationapproach. The use of semantic and knowledge technologies forimproving the mechanism for the selection of VLC members(overcoming the limitation of the adopted approach) and life-cycle management integrated in Grid middleware are underinvestigation in the context of other European Commission-


funded research projects like BREIN and BEinGRID, wherethe authors are involved in.

The experience done also provided useful feedbacks abouttwo capabilities of the GRASP middleware: security mecha-nism and SLA monitoring for accounting and billing. Con-cerning the security mechanism, based on the Dynamic SecurePerimeter [38], it demonstrates to be too heavy in terms ofmessages exchanged. In the context of the BEinGRID project,we have reviewed our approach and tested new technologies(message gateway accelerator) and, lastly, refined the VOSet-up component according to models for fine-grained AC,such as the ones presented in [33].

Concerning the SLA monitoring mechanism, it seems towork fine in a homogeneous environment but is not completelyapplicable in high heterogeneous environments (unless of con-crete simplifications) with negative impact on business aspects(accounting and billing).

Lastly, also preliminary results and evaluation of the Ap-plication Virtualization component evidenced the necessity forsuch a good scheduling mechanism to optimize resource allo-cation. To this purpose, further investigations will consider theadoption of optimization methods similar to the ones proposedin [39] that appear to be suitable with respect to our conflictingrequirements of addressing new demand on resources (e.g., toexecute a simulation or a virtual scientific experiment as part ofa learning experience) while preserving reliability in deliveringa learning experience.

ACKNOWLEDGMENT

This paper does not represent the opinion of the EuropeanCommunity, and the European Community is not responsiblefor any use that might be made of data appearing therein.

REFERENCES

[1] N. Capuano, M. Gaeta, and P. Ritrovato, “The anatomy of the learningGrid,” in The Learning Grid Handbook, Concepts, Technologies andApplications, vol. 2, S. Salerno, M. Gaeta, P. Ritrovato, N. Capuano,F. Orciouli, S. Miranda, and A. Pierri, Eds. Amsterdam,The Netherlands: IOS Press, 2008, ser. The Future of Learning,pp. 3–19.

[2] 1-58603-534-7M. Gaeta, P. Ritrovato, and S. Salerno, “Making e-learninga service oriented utility: The European Learning Grid Infrastructureproject,” in Towards the Learning GRID: Advances in Human Learn-ing Services. Amsterdam, The Netherlands: IOS Press, Aug. 2005,ser. Frontiers in Artificial Intelligence and Applications, pp. 63–75.

[3] M. Gaeta, F. Orciouli, and P. Ritrovato, “How to use Grid technologyfor creating contextualized and adaptive learning experiences: The Eu-ropean Learning Grid Infrastructure software architecture,” in Proc.14th Int. Conf. Distrib. Multimedia Syst., Boston, MA, Sep. 4–6, 2008,pp. 390–395.

[4] I. Foster and C. Kesselman, The Grid: Blueprint for a New ComputingInfrastructure. San Mateo, CA: Morgan Kaufmann, 1999.

[5] I. Foster, C. Kesselman, and S. Tuecke, “The anatomy of the Grid: En-abling scalable virtual organizations,” Int. J. Supercomput. Appl., vol. 15,no. 3, pp. 200–222, 2001.

[6] I. Foster, C. Kesselman, J. Nick, and S. Tuecke, The Physiology ofthe Grid: An Open Grid Service Architecture for Distributed Sys-tem Integration, 2002. [Online]. Available: www.globus.org/alliance/publications/papers/ogsa.pdf

[7] M. P. Singh and S. S. Vazhkudai, “Special issue Guest’s Editors on “Vir-tual Organizations”,” IEEE Internet Comput., vol. 12, no. 2, pp. 10–12,Mar./Apr. 2008.

[8] ISBN 3-540-24013-6E. Sherly, G. Bindya, L. Deepa, and K. S. Resmy, “AGrid service based portal for virtual learning campus,” in Proc. 5th Int.

Conf. PDCAT , vol. 3320, Lecture Notes in Computer Science, K. Liew,H. Shen, S. See, W. Cai, P. Fan, and S. Horiguchi, Eds., Singapore,Dec. 8–10, 2004, pp. 86–89, Berlin, Germany: Springer-Verlag.

[9] Z. Luo, Y. Fei, and J. Liang, “On demand e-learning with service Gridtechnologies,” in Proc. Edutainment, 2006, pp. 60–69.

[10] O. Ardaiz, P. Artigas, L. Diaz de Cerio, F. Freitag, A. Gallardo,R. Messeguer, L. Navarro, D. Royo, and K. Sanjeevan, “ULabGrid,an infrastructure to develop distant laboratories for undergrad studentsover a Grid,” in Lecture Notes in Computer Science, vol. 2970. Berlin,Germany: Springer-Verlag, 2003, pp. 265–272.

[11] C. Huang, F. Xu, X. Xu, and X. Zheng, “Towards an agent-based robustcollaborative virtual environment for e-learning in the service Grid,”in Lecture Notes in Computer Science, vol. 4088. Berlin, Germany:Springer-Verlag, 2006, pp. 702–707.

[12] H. Zhuge and Y. Li, “KGTutor: A knowledge Grid based intelligent tutor-ing system,” in Lecture Notes in Computer Science, vol. 3007. Berlin,Germany: Springer-Verlag, 2004, pp. 473–478.

[13] G. Samaras, K. Karenos, and E. Christodoulou, “A Grid service frame-work for metadata management in self-e-learning networks,” in Proc.2nd Eur. AxGrid Conf., vol. 3165, Lecture Notes in Computer Science,Nicosia, Cyprus, Jan. 2004, pp. 105–111.

[14] Z. Abbas, M. Umer, M. Odeh, R. McClatchey, A. Ali, andF. Ahmad, “A semantic Grid-based e-learning framework (SELF),”in Proc. CLAG/5th Int. Symp. Cluster Comput. Grid, Cardiff, U.K.,May 2005, pp. 11–18.

[15] C. Guangzuo, C. Fei, C. Hu, and L. Shufang, “OntoEdu: A case study ofontology-based education Grid system for e-learning,” in Proc. Int. Conf.GCCCE, Hong Kong, 2004, Invited report.

[16] C. Liao and F. O. Yang, “A workflow framework for pervasive learningobjects composition by employing Grid services flow language,” in Proc.IEEE ICALT , 2004, pp. 840–841.

[17] G. Vega-Gorgojo, M. L. Bote-Lorenzo, E. Gómez-Sánchez,Y. A. Dimitriadis, and J. I. Asensio-Pérez, “Semantic search of learningservices in a Grid-based collaborative system,” in Proc. 5th IEEE/ACMInt. Symp. CCGrid/CLAG, Cardiff, U.K., May 2005, pp. 19–26.

[18] [Online]. Available: http://www.jisc.ac.uk/whatwedo/programmes/elearningframework.aspx

[19] S. Wilson, K. Blinco, and S. Rehak, Service-Oriented Frameworks: Mod-elling the Infrastructure for the Next Generation of e-Learning Sys-tems, A paper prepared on behalf of DEST (Australia), JISC-CETIS(U.K.), and Industry Canada, Jul. 2004. [Online]. Available: http://www.jisc.ac.uk/uploaded_documents/AltilabServiceOrientedFrameworks.pdf

[20] S. Downes, E-learning 2.0, eLearn Mag., 2005, no. 10, Oct. 2005.[Online]. Available: http://www.elearnmag.org/subpage.cfm?section=articles&article=29-1

[21] D. Dagger, A. O’Connor, E. Walsh, S. Lawless, and V. P. Wade, “Service-oriented e-learning platforms: From monolithic systems to flexible ser-vices,” IEEE Internet Comput., vol. 11, no. 3, pp. 28–35, May/Jun. 2007.

[22] G. Albano, M. Gaeta, and S. Salerno, “E-learning: A model and processproposal,” Int. J. Knowl. Learn., vol. 2, no. 1/2, pp. 73–88, 2006, ISSN(Online): 1741-1017, ISSN (Print): 1741-1009.

[23] E. J. R. Koper and P. Sloep, “Learning networks: Connecting peo-ple, organizations, autonomous agents and learning resources to es-tablish the emergence of effective lifelong learning,” OTEC, Heerlen,The Netherlands, 2003, Open Univ. Netherlands Rep., (OTEC RTDProgramme Plan 2003–2008), to be published.

[24] A. Gaeta, M. Gaeta, F. Orciuoli, and P. Ritrovato, “Defining a serviceoriented architecture for e-learning: The European Learning Grid In-frastructure project experience,” Int. J. Technol. Enhanced Learn., ISSN(Online): 1753-5263, ISSN (Print): 1753-5255, to be published.

[25] G. Albano, M. Gaeta, and P. Ritrovato, “IWT: An innovative solution forAGS e-learning model,” Int. J. Knowl. Learn., vol. 3, no. 2/3, pp. 209–224, 2007, ISSN (Online): 1741-1017, ISSN (Print): 1741-1009.

[26] 1617-4909P. Ritrovato, M. Gaeta, and A. Gaeta, “A Grid based softwarearchitecture for delivery of adaptive and personalised learning experi-ences,” ACM Personal Ubiquitous Comput. J., vol. 13, no. 3, pp. 207–217,Mar. 2009.

[27] R. A. Schwier, “Virtual learning communities,” in Critical Issues inInstructional Technology, G. Anglin, Ed. Portsmouth, NH: TeacherIdeas Press, 2004.

[28] T. Dimitrakos, M. Gaeta, G. Laria, D. Mac Randal, P. Ritrovato, B. Serhan,F. Yuan, S. Wesner, and K. Wulf, “An emerging architecture enabling Gridbased application service provision,” in Proc. 7th IEEE Int. Conf. EDOC,Brisbane, Australia, Sep. 16–19, 2003, pp. 240–250.

[29] 1-58603-534-7N. Capuano, A. Gaeta, G. Laria, F. Orciuoli, andP. Ritrovato, “How to use GRID technology for building next generationlearning environments,” in Towards the Learning GRID: Advances in


Human Learning Services, vol. 127, Frontiers in Artificial Intelligenceand Applications, P. Ritrovato, C. Allison, S. A. Cerri, T. Dimitrakos,M. Gaeta, and S. Salerno, Eds. Amsterdam, The Netherlands: IOS Press,Nov. 2005, pp. 182–192, 252 pp.

[30] 3-540-25424-2R. Baraglia, D. Laforenza, A. Gaeta, M. Gaeta, andP. Ritrovato, “Design of OGSA-compliant Grid information service using.NET technologies,” in Proc. 6th Int. Conf. VECPAR, vol. 3402, LNCS,M. Daydé, J. Dongarra, V. Hernández, and J. M. L. M. Palma, Eds.,Valencia, Spain, 2005, pp. 247–259, Berlin, Germany: Springer-Verlag,Revised Selected and Invited Papers.

[31] L. Wang, G. von Laszewski, D. Chen, J. Tao, and M. Kunze, “Pro-vide virtual machine information for Grid computing,” IEEE Trans.Syst., Man, Cybern. A, Syst., Humans, vol. 40, no. 6, pp. 1362–1374,Nov. 2010.

[32] Virtual Organization Membership Service (VOMS). [Online]. Available:http://edg-wp2.web.cern.ch/edg-wp2/security/voms/voms.html

[33] T.-Y. Chen, Y.-M. Chen, and C.-B. Wang, “A formal virtual enterpriseaccess control model,” IEEE Trans. Syst., Man, Cybern. A, Syst., Humans,vol. 38, no. 4, pp. 832–851, Jul. 2008.

[34] E. Gamma, R. Helm, R. Johnson, and J. Vlissides, Design Patterns:Elements of Reusable Object-Oriented Software. Reading, MA:Addison-Wesley, 1995, 0201633612.

[35] A. Gaeta, M. Gaeta, G. Meo, F. Orciuoli, P. Ritrovato, andS. Stefanucci, “Creation and delivery of adaptive unit of learning us-ing the ELeGI software architecture: The VSE model implementationcase study,” in Proc. e-Challenges, Barcelona, Spain, Oct. 25–27, 2006,pp. 1459–1466.

[36] L. M. Camarinha-Matos, I. Silveri, H. Afsarmanesh, and A. I. Oliveira,“Towards a framework for creation of dynamic virtual organizations, incollaborative networks and their breeding environments,” in Proc. IFIP,2005, vol. 186, pp. 69–80.

[37] D23.1—Requirements and Mechanisms for VO Planning andLaunching—Deliverable of the ECOLEAD Project. [Online]. Available:http://www.ve-forum.org/projects/284/Deliverables/D231VOcreation.pdf

[38] I. Djordjevic, T. Dimitrakos, D. Mac Randal, P. Ritrovato, and N. Romano,“Dynamic security perimeters for inter-enterprise service integration,”Future Gener. Comput. Syst., vol. 23, no. 4, pp. 633–657, May 2007.

[39] S.-Y. Lin, S.-C. Horng, and C.-Z. Lin, “Expanding service capacities andincreasing service reliabilities for the Grid-based utility computing,” IEEETrans. Syst., Man, Cybern. A, Syst., Humans, vol. 41, no. 1, pp. 149–160,Jan. 2011.

Matteo Gaeta (M’05) received the Laurea degreein computer science from the University of Salerno,Fisciano, Italy, in 1989.

He is currently an Associate Professor of infor-mation processing systems with the Department ofElectronic Engineering and Information Engineer-ing, University of Salerno, Fisciano, Italy. His re-search interests include complex information sys-tems architecture, software engineering, systems ofknowledge representation, Semantic Web, virtual or-ganization, and Grid computing. He gained a large

experience in the implementation and design of complex information systems.He is the author of more than 80 papers, published on journals, proceedings, andbooks. He is the Scientific Coordinator and Manager of several internationalresearch projects and the Coordinator of the Ministry for Education, HigherEducation, and Research Working Group. He is a Member of the Panel forthe Scientific Assessment of Research and Testing Projects of the Ministry ofAgriculture and Forestry, a Member of the Experts Register of the Departmentfor Education and Skills, and a Member of the Innovation Technology ExpertsRegister of the Department for the Economy Development.

Pierluigi Ritrovato (M’08) received the Laurea de-gree in computer science from the University ofSalerno, Fisciano, Italy, in 1992.

He is currently an Assistant Professor in computerscience with the University of Salerno, Fisciano,Italy. In the last five years, he has been focusinghis scientific research on distributed learning man-agement systems and Grid technologies for business,taking into account aspects related to the operationalmanagement of virtual organization, automatic ser-vice discovery, and composition, as well as the study

and evaluation on how to improve and extend the general Grid architecture inorder to create domain specific solutions for learning and training, contributingalso to the knowledge and Semantic Grid definition. The most relevant researchprojects where he has been and is currently involved in are as follows:European Learning Grid Infrastructure with the role of Scientific Coordinator,the Kaleidoscope Network of Excellence as Coordinator of the LearningGrid Special Interest Group, and Business Experiment in Grid which is abig integrated project (75 partners from all European Union countries). Heis the Editor of the books Towards the Learning Grid: Advances in HumanLearning Services and The Learning Grid Handbook: Concepts, Technologiesand Applications both published by IOS Press.

Prof. Ritrovato has represented Modelli Matematici ed Applicazioni as amember of the Steering Committee of the Networked European Software andServices Initiative European Technology Platform.

Domenico Talia (M’90) received the Laurea degreein physics from the University of Calabria, Rende,Italy.

He is currently a Full Professor of computerengineering with the Department of Electronics,Information, and Systems, University of Calabria.His research interests include Grid computing, dis-tributed knowledge discovery, parallel data mining,parallel programming languages, and peer-to-peersystems. He published five books and more than 250papers in international journals, such as Communi-

cations of the ACM, Computer, ACM Computing Surveys, Future GenerationComputer Systems (FGCS), Parallel Computing, IEEE INTERNET COMPUT-ING, IEEE MICRO, IEEE TRANSACTIONS ON KNOWLEDGE AND DATA EN-GINEERING (TKDE), IEEE TRANSACTIONS ON SOFTWARE ENGINEERING,and IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS—PART

B: CYBERNETICS, and in conference proceedings. He is a member of theeditorial boards of the FGCS journal, the International Journal of Web andGrid Services, the Scalable Computing journal, and the Web Intelligence andAgent Systems international journal.

Prof. Talia is the Director of Istituto di Calcolo e Reti ad Alte Prestazioni,Consiglio Nazionale delle Ricerche. He is a member of the editorial boardof the IEEE TKDE. He is also a member of the Executive Committee of theCoreGRID Network of Excellence, a program committee member of severalconferences, and is a member of the Association for Computing Machinery andthe IEEE Computer Society.

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