Secure Real-Time Integration of Services in a OSGi Distributed Environment

Márquez, José Manuel; Jimenez, Javi; Agudo, Isaac

doi:10.1109/ncm.2008.173

Cited by 2 publications

(2 citation statements)

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“…OSGI has been used in many ERT systems such as the winning Eclipse integrated development, automation and telecommunication and etc. Dependencies between components are defined by bundles in the OSGI nomenclature [18].…”

Section: Osgimentioning

confidence: 99%

An Implementation of Embedded Real Time System Framework in Service Oriented Architecture

Aghajani

Jawawi

2012

2012 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery

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Currently, the complexity of embedded software is increased, hence, more efficient design approaches are demanded. Although component based design is well-defined for developing Embedded Real Time (ERT) systems, the design and implementation of ERT component software is slow and complex. Distributed ERT systems can reduce the complexity of a component and increase its reliability and re-usability as well. Currently, Service Oriented Architecture (SOA) is an excellent technology for the implementation of distributed software. Some platforms are introduced to implement the components in SOA concept such as Service Component Architecture (SCA) and OSGI (Open Services Gateway Initiative). SCA provides a hierarchical component composition, distributed configurations and an interconnection with various means to design and combine services. However, SCA is unable to discover and reference services dynamically. In contrast, OSGI focuses on loading the service component. The services can be stopped, loaded and unloaded in frameworks supported by OSGI. Hence, this paper proposes an integration of SCA and OSGI to introduce a new framework for the implementation of distributed ERT systems.

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Section: Osgimentioning

confidence: 99%

An Implementation of Embedded Real Time System Framework in Service Oriented Architecture

Aghajani

Jawawi

2012

2012 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery

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“…The collaboration with the University of Vigo involves developing a SCORM player for embedded devices based on a very simple Java desktop package which will later be produced as a web-based version. Both approaches also deploy OSGi bundles, thereby allowing a real-time integration of the services and applications contained in therein [16]. With respect to how an ACO algorithm is implemented to create adaptive paths, our approach can be compared with other similar published approaches.…”

Section: Related Workmentioning

confidence: 99%

Designing adaptive learning itineraries using features modelling and swarm intelligence

Vazquez¹,

Ramírez

Abril

et al. 2011

Neural Comput & Applic

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In this paper, Bayesian network (BN) and ant colony optimization (ACO) techniques are combined in order to find the best path through a graph representing all available itineraries to acquire a professional competence. The combination of these methods allows us to design a dynamic learning path, useful in a rapidly changing world. One of the most important advances in this work, apart from the variable amount of pheromones, is the automatic processing of the learning graph. This processing is carried out by the learning management system and helps towards understanding the learning process as a competence-oriented itinerary instead of a stand-alone course. The amount of pheromones is calculated by taking into account the results acquired in the last completed course in relation to the minimum score required and by feeding this into the learning tree in order to obtain a relative impact on the path taken by the student. A BN is used to predict the probability of success, by taking historical data and student profiles into account. Usually, these profiles are defined beforehand; however, in our approach, some characteristics of these profiles, such as the level of knowledge, are classified automatically through supervised and/or unsupervised learning. By using ACO and BN, a fitness function, responsible for automatically selecting the next course in the learning graph, is defined. This is done by generating a path which maximizes the probability of each user's success on the course. Therefore, the path can change in order to adapt itself to learners' preferences and needs, by taking into account the pedagogical weight of each learning unit and the social behaviour of the system.

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Secure Real-Time Integration of Services in a OSGi Distributed Environment

Cited by 2 publications

References 1 publication

An Implementation of Embedded Real Time System Framework in Service Oriented Architecture

An Implementation of Embedded Real Time System Framework in Service Oriented Architecture

Designing adaptive learning itineraries using features modelling and swarm intelligence

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