Hatim Hafiddi

Context modeling and reasoning for building context aware services

The rapid evolution of software paradigms, wireless technologies and mobile devices induced the emergence of new applications called context-aware services oriented applications. Such applications provide appropriate services or relevant information to the user or other applications to perform a specific task. An important challenge in such applications development process is context modeling and reasoning. Ontology based models presents the most promising instrument for context modeling and offers possibility of applying ontology reasoning techniques. the aim of context reasoning is converting low-level context to highlevel context in order to provide customized services to users. In this paper, we present an architecture for the development of context aware services based on ontologies. We also highlight our context metamodel and discuss about reasoning process for e-health systems.

How can Service Oriented Systems make beneficial use of Model Driven Architecture and aspect paradigm

Today, Service Oriented Architectures (SOA) are being widely deployed to improve systems development and interoperability. In addition, the increasing use of mobile devices and infrastructure has enabled users to access services from any location and any time. The convergence of mobile technologies and service paradigm has promoted the birth of a new design and development paradigm known as Context-Aware Service (CAS). CAS based systems are context-aware and therefore they can offer pertinent services for their users depending on their context. Dealing with such systems requires an approach that addresses challenges such as context management and service adaptation to the context. In this paper, we present how can the development process of Context-Aware Service Oriented Systems (CASOS) benefit from the model and aspect paradigms?

A model driven approach for context-aware services development

Nowadays, context-awareness constitutes an essential aspect for service oriented applications development. Indeed, applications are supposed to react to context changes in order to provide end-users with pertinent services. To deal with such requirement, Context-Aware Service (CAS) has emerged as an underlying software engineering paradigm for context-aware applications development. In this paper, we present a model driven approach that highlights the fundamental context-awareness challenges for CAS development. So, we first present our context metamodel based on a practical specification of the context. Then, we propose a CAS specification and metamodel and show how can Aspect Paradigm (AP) be used to fulfill service adaptation to its execution contexts. We illustrate our approach by an E-tourism motivating scenario.

Towards an ontology based architecture for context-aware services composition

An important challenge in pervasive computing environments is to automatically enable software applications by dynamically composing services. Service composition is a way to plan a business process to fulfill business goals that cannot be achieved by individual business services. Given a representation of services in OWL-S, service composition can be modeled as an Artificial Intelligence planning (AI planning) problem. Based on the initial context and the goal context, planning-based service composition launches a goal-oriented composition procedure to generate a plan for the service composition. In this paper, we present an overview of the architecture for the composition of context aware services based on ontologies, we also present our Composition Planner that allows to generate a plan corresponding to the request of the users according to their context.

A Synergy of Semantic and Context Awareness for Service Composition in Ubiquitous Environment

Service composition in an important facet in service oriented architecture, it’s about the idea of assembling atomic services to satisfy a demand rather than building new applications from ‘scratch’, From the user’s perspective it’s a complex task due to the increasing number of services in the web and their heterogeneity. This complexity is increasing in the internet of Things era wehere computing devices are everywhere. In this work we propose an approach for composition of context aware services in a semantic manner, Artificial Intelligence planning is used to automate the composition starting from a defined objectif containing user request and context parameters. Service are described by extending OWL-S with contextual conditions. The proposed architecture was evaluated through an e-health scenario where chronic patients can benefit from a remote and automated medical supervision and emergency handling.

MiCATS: Middleware for Context-Aware Transactional Services

In context-aware service-based environments, fulfilling user’s recommendations bring about several challenges that are mainly due to the dynamic nature and limited underlying resources of these environments. In this paper, we mainly focus on the transactional aspects of context-aware services. To cope with the aforementioned issues, we opt for a middleware-based solution (MiCATS). We therefore present our novel approach for managing context-aware transactions which allows for adaptation to the requirements of applications and mobile context in terms of transactional properties. Then, we introduce our context-aware transactional service model (CATSM) and a context-aware architecture based on adaptation policies. The proposed contributions are implemented within a middleware platform.

An Intelligent Approach for Context-Aware Service Selection using Machine Learning

Service selection is a process to choose the services that best suit user functional and Non-functional Properties (NFP). With the increasing number of available services, users are offered a choice of competitively functional (or even identical) services. Therefore, this choice strongly depends on the NFPs and the user preferences (context) that differentiate between several competitive services. The service selection can be performed automatically and transparently to the user. In this paper, An extension of OWL-S service is proposed to take context information into account during the selection. Afterwards, we presents an intelligent approach for context-aware service selection based on Markov Decision Process, we show how to solve it using reinforcement learning techniques.

Using Context Ontology and Linear SVM for Chronic Kidney Disease Prediction

In the e-Health learning area, the use of chronic patient context has become very important given the increase in the number of individuals who suffer from these diseases and the unavailability of medications. Specifically, chronic kidney failure is one of the diseases that goes undetected and undiagnosed until it is well advanced. The need for preventive prediction remains an essential task for the well-being of patients at risk. In this paper, we aim to explore the added value of using ontology-based prediction, focusing on Linear SVM, to deal with Chronic Kidney Disease Problems.

Toward a unified framework for Cloud Computing governance: An approach for evaluating and integrating IT management and governance models

Abstract Cloud Computing is currently one of the major trends in the computer industry. It offers a wide range of both opportunities and challenges. The lack of governance causes a slowdown in the adoption process, especially with an absence of a comprehensive approach supporting the Cloud Computing governance objectives. Regarding this issue, our goal is to develop a new management and governance framework based on endorsed IT models; namely ITIL, COBIT, and ISO/IEC 27001/2. These models have been developed for different purposes and aspects of IT governance. The proposed framework is an attempt to a unified approach by taking into consideration the models’ dissimilarities. Before we go further with the final unification stage, this studys main objective is to develop both the evaluation and the integration approaches with regwards to the IT models. The results, therefore, are to shed light on the relevant outcomes emanate from an elaboration within an entirely unified CC governance framework.

COBIT Evaluation as a Framework for Cloud Computing Governance

The present paper aims at providing an approach for evaluating COBIT as a base framework for cloud computing governance. For that purpose, the authors firstly conducted a systematic research reviews to identify, analyze, and structure the main cloud computing governance requirements. Secondly, with respect to the systematic research review, a mapping of COBIT control objectives to the corresponding cloud computing governance requirements is proposed. Thirdly, the evaluation of the mapped control objectives against the cloud computing governance requirements is performed to identify and analyze the framework gaps. The paper results are relevant outcomes for the extension of COBIT processes and capabilities and thus can provide a base framework for building a holistic cloud computing governance approach.