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A classification of emerging and traditional grid systems
The grid has evolved in numerous distinct phases. It started in the early â90s as a model of metacomputing in which supercomputers share resources; subsequently, researchers added the ability to share data. This is usually referred to as the first-generation grid. By the late â90s, researchers had outlined the framework for second-generation grids, characterized by their use of grid middleware systems to âglueâ different grid technologies together. Third-generation grids originated in the early millennium when Web technology was combined with second-generation grids. As a result, the invisible grid, in which grid complexity is fully hidden through resource virtualization, started receiving attention. Subsequently, grid researchers identified the requirement for semantically rich knowledge grids, in which middleware technologies are more intelligent and autonomic. Recently, the necessity for grids to support and extend the ambient intelligence vision has emerged. In AmI, humans are surrounded by computing technologies that are unobtrusively embedded in their surroundings.
However, third-generation gridsâ current architecture doesnât meet the requirements of next-generation grids (NGG) and service-oriented knowledge utility (SOKU).4 A few years ago, a group of independent experts, arranged by the European Commission, identified these shortcomings as a way to identify potential European grid research priorities for 2010 and beyond. The experts envision grid systemsâ information, knowledge, and processing capabilities as a set of utility services.3 Consequently, new grid systems are emerging to materialize these visions. Here, we review emerging grids and classify them to motivate further research and help establish a solid foundation in this rapidly evolving area
Enabling Personalized Composition and Adaptive Provisioning of Web Services
The proliferation of interconnected computing devices is fostering the emergence of environments where Web services made available to mobile users are a commodity. Unfortunately, inherent limitations of mobile devices still hinder the seamless access to Web services, and their use in supporting complex user activities. In this paper, we describe the design and implementation of a distributed, adaptive, and context-aware framework for personalized service composition and provisioning adapted to mobile users. Users specify their preferences by annotating existing process templates, leading to personalized service-based processes. To cater for the possibility of low bandwidth communication channels and frequent disconnections, an execution model is proposed whereby the responsibility of orchestrating personalized processes is spread across the participating services and user agents. In addition, the execution model is adaptive in the sense that the runtime environment is able to detect exceptions and react to them according to a set of rules
Towards business model and technical platform for the service oriented context-aware mobile virtual communities
The focus of existing virtual communities is centered on a particular product or social interaction and the role of mobile devices is restricted to exchange a limited amount of contents. Herewith we envisage that the upcoming virtual communities will exploit the potential of social interaction and context information to offer personalized services to its members and mobile devices will play a significant role in this process. As a step towards this direction, in this paper we propose a business model for the mobile virtual communities in which the mobile device takes on the role of a content producer and content consumer. Though there are a number of research issues which need to be addressed to realize such virtual communities, in this paper we focus on the service requirements, architecture and open source software implementation of a technical platform for the content producer and consumer mobile devices
Context-Aware and Adaptable eLearning Systems
The full text file attached to this record contains a copy of the thesis without the authors publications attached. The list of publications that are attached to the complete thesis can be found on pages 6-7 in the thesis.This thesis proposed solutions to some shortcomings to current eLearning architectures. The proposed DeLC architecture supports context-aware and adaptable provision of eLearning services and electronic content. The architecture is fully distributed and integrates service-oriented development with agent technology. Central to this architecture is that a node is our unit of computation (known as eLearning node) which can have purely service-oriented architecture, agent-oriented architecture or mixed architecture. Three eLeaerning Nodes have been implemented in order to demonstrate the vitality of the DeLC concept. The Mobile eLearning Node uses a three-level communication network, called InfoStations network, supporting mobile service provision. The services, displayed on this node, are to be aware of its context, gather required learning material and adapted to the learner request. This is supported trough a multi-layered hybrid (service- and agent-oriented) architecture whose kernel is implemented as middleware. For testing of the middleware a simulation environment has been developed. In addition, the DeLC development approach is proposed. The second eLearning node has been implemented as Education Portal. The architecture of this node is poorly service-oriented and it adopts a client-server architecture. In the education portal, there are incorporated education services and system services, called engines. The electronic content is kept in Digital Libraries. Furthermore, in order to facilitate content creators in DeLC, the environment Selbo2 was developed. The environment allows for creating new content, editing available content, as well as generating educational units out of preexisting standardized elements. In the last two years, the portal is used in actual education at the Faculty of Mathematics and Informatics, University of Plovdiv. The third eLearning node, known as Agent Village, exhibits a purely agent-oriented architecture. The purpose of this node is to provide intelligent assistance to the services deployed on the Education Pportal. Currently, two kinds of assistants are implemented in the node - eTesting Assistants and Refactoring eLearning Environment (ReLE). A more complex architecture, known as Education Cluster, is presented in this thesis as well. The Education Cluster incorporates two eLearning nodes, namely the Education Portal and the Agent Village. eLearning services and intelligent agents interact in the cluster
Personalizable Service Discovery in Pervasive Systems
Today, telecom providers are facing changing challenges.
To stay ahead in the competition and provide market
leading offerings, carriers need to enable a global ecosystem of
third party independent application developers to deliver converged
services. This is the aim of leveraging a open standardsbased
service delivery platform. To identify and to cope with
those challenges is the main target of the EU funded project
IST DAIDALOS II. And a central point to satisfy the changing
user needs is the provision of a well working, user friendly and
personalized service discovery. This paper describes our work
in the project on a middleware in a framework for pervasive
service usage. We have designed an architecture for it, that
enables full transparency to the user, grants high compatibility
and extendability by a modular and pluggable conception and
allows for interoperability with most known service discovery
protocols. Our Multi-Protocol Service Discovery and the Four
Phases Service Filtering concept enabling personalization should
allow for the best possible results in service discovery
Service-oriented Context-aware Framework
Location- and context-aware services are emerging technologies in mobile and
desktop environments, however, most of them are difficult to use and do not
seem to be beneficial enough. Our research focuses on designing and creating a
service-oriented framework that helps location- and context-aware,
client-service type application development and use. Location information is
combined with other contexts such as the users' history, preferences and
disabilities. The framework also handles the spatial model of the environment
(e.g. map of a room or a building) as a context. The framework is built on a
semantic backend where the ontologies are represented using the OWL description
language. The use of ontologies enables the framework to run inference tasks
and to easily adapt to new context types. The framework contains a
compatibility layer for positioning devices, which hides the technical
differences of positioning technologies and enables the combination of location
data of various sources
Enabling Social Applications via Decentralized Social Data Management
An unprecedented information wealth produced by online social networks,
further augmented by location/collocation data, is currently fragmented across
different proprietary services. Combined, it can accurately represent the
social world and enable novel socially-aware applications. We present
Prometheus, a socially-aware peer-to-peer service that collects social
information from multiple sources into a multigraph managed in a decentralized
fashion on user-contributed nodes, and exposes it through an interface
implementing non-trivial social inferences while complying with user-defined
access policies. Simulations and experiments on PlanetLab with emulated
application workloads show the system exhibits good end-to-end response time,
low communication overhead and resilience to malicious attacks.Comment: 27 pages, single ACM column, 9 figures, accepted in Special Issue of
Foundations of Social Computing, ACM Transactions on Internet Technolog
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