Achraf Mtibaa

Ontology-Based Context-Aware SLA Management for Cloud Computing

Cloud Computing represents a new on-demand computing approach that tries to provide resources responding to some pre-set non-functional proprieties specified and negotiated by means of Service Level Agreement (SLAs). In order to avoid costly SLA violations and to duly react to failures and environmental changes, it is necessary to implement some advanced SLA enactment strategies. However, contextual information of the cloud consumer, which has not been deeply elaborated yet, may change at any time, which would significantly affect the Quality of Service (QoS). Therefore, in this paper, our aim is to ameliorate SLA by considering the semantic meaning of SLA concepts and contextual information from cloud consumers. In this regard, we propose a new ontology-based context-aware SLA management for cloud computing. Our approach aims to dynamically adapt cloud services to different variations of consumer’s context while meeting their needs using the benefits of inference in ontology. This maintains a reliable QoS and respects the SLA parameters. The efficiency and effectiveness of the proposed approach is demonstrated in this paper through a simulation.

CSLAOnto: A Comprehensive Ontological SLA Model in Cloud Computing

Cloud computing is an emerging topic in the information technology sector. The rapid evolution of this technology led to the emergence of new interaction models between its actors. However, the absence of a universally accepted format of the service level agreement (SLA) governing the relationships between the different actors of cloud increases its complexity. In addition, the dynamic nature of the cloud could lead to severe SLA violations. This undesirable but currently unavoidable situation may lead to penalizing providers and forcing customers to evaluate their SLAs permanently. In this paper, we propose a generic and semantically richer ontology-based model for SLA to improve its definition and its evaluation in cloud computing. Through this model, we have developed a prototype to validate our model and our monitoring process where SLA evaluation and guarantee actions triggering are automatically performed.

SLA Ontology-Based Elasticity in Cloud Computing

Service Level Agreements (SLA) is the principal means of control which defines the Quality of Service (QoS) requirements in cloud computing. These requirements have to be guaranteed in order to avoid costly SLA violations. However, elasticity strategies, which have not been deeply considered yet in SLA documents, may significantly ameliorate the QoS. Therefore, in this paper, our aim is to guarantee the QoS by introducing the semantic meaning of the elasticity strategies in SLA. In this regard, we propose an ontology-based elasticity approach which allows getting an elastic cloud service by dynamically apply corrective actions. These corrective actions present the elasticity strategies applied following a violation or in prediction of a violation. Our proposed approach allows getting an interactive and flexible SLA document in order to maintain a reliable QoS and respect the SLA parameters.

Ontology-Based User Modeling for Handicraft Woman Recommendation

Intelligent systems are good in presenting adapted information and services to the systems users’ contexts. In fact, they are often based on contextual and profiling information. Thus it is necessary for these systems to have an explicit model for the user profile as well as for the user context. Ontology-based user profile and context modeling is especially important for reasoning systems that can benefit from inference on ontology representing different knowledge. In this paper, we propose an ontology-based user model to represent both user profile and context. Then, we give some rules for users’ recommendation in the handicraft domain which is the domain of research project that we are involved in. The aim of the research project is to help handicraft women from emerging countries to use new technologies in order to improve their socio-economic level. Our ontology enriched by SWRL (Semantic Web Rule Language) rules has the advantage to infer adapted services to handicraft woman through a system.

Semantic Web Technologies in Cloud Computing: A Systematic Literature Review

During the last years we have seen a dramatic increase of new Cloud providers, applications, services, management platforms, data, etc. reaching a level of complexity that implies the necessity of new solutions to deal with such vast, shared and heterogeneous services and resources. Consequently, challenges often related to interoperability, portability, security, discovery, selection, negotiation and description of cloud service and resource may take place. In this sense, Semantic Web Technologies, holding a great potential to cloud computing, have been proven as an efficient means to relive these challenges. This paper examines and explores the role of Semantic Web Technologies in the cloud from a wide variety of literatures. Various approaches, architectures, and frameworks are screened and evaluated based on eight prime research questions. At the end of the review, research opportunities in the form of a roadmap are discussed.

Detecting Cloud (Anti)Patterns: OCCI Perspective

Open Cloud Computing Interface (OCCI) follows a set of guidelines (i.e. best practices) to create interoperable APIs over Cloud resources. In this paper, we identify a set of patterns that must be followed and anti-patterns that should be avoided to comply with the OCCI guidelines. To automatically detect (anti)patterns, we propose a Semantic-based approach, relying on SWRL (Semantic Web Rule Language) rules and in SQWRL (Semantic Query-Enhanced Web Rule Language) queries to describe the (anti)patterns symptoms. An evaluation, conducted on real world Cloud service APIs, shows the feasibility of the proposed approach by assessing their compliance to OCCI standard.

Ontology-Based Context-Aware Social Networks

Due to the increasing progress of context-aware platforms with social networks many works use these platforms with mobile devices. Thus, we expose, in this paper, a survey of some of these works. Knowledge representation in the social networks has a great interest to obtain a set of information with a valuable signification. Therefore, we expose a state-of-the-art about the knowledge extraction using ontologies in social networks. Then, we propose, in this paper, an approach to combine these technologies (context, mobile and ontology) together to have a contextualized ontology helping to assist a mobile user in his information retrieval from the social network. We conclude by giving an idea about our future works.

A Multi-representation Ontology for the Specification of Multi-context Requirements

There are many problems associated with requirements engineering. In fact, some concepts can be seen differently according to the users context. The requirement specification generates several problems of incoherence, ambiguity and difficulty when users admit different contexts. These problems may lead to poor requirements and unsatisfactory or unacceptable future system. For this reason, we propose a multi-representation ontology to solve these conflicts and problems. In this paper, we propose our motivation and we expose our top-down approach for building a multi-representation ontology dedicated to multi-context requirements specification in the e-learning field.

A parallel framework for HCC detection in DCE-MRI sequences with wavelet-based description and SVM classification

In this article, we propose a complete framework devoted to detect liver HCC (Hepato-Cellular Carcinoma) tumors within DCE-MRI (Dynamic Contrast Enhanced-MRI) sequences. Our system employs different phases of these hepatic image sequences (depending on time after contrast agent injection) to describe local patches with wavelet-based descriptors. By using a SVM (Support Vector Machine)-based classification, we are able to distinguish healthy patches from pathological ones. Moreover, thanks to a parallel image processing strategy, we are able to reduce significantly the running time so that our system may be utilized as a computer aided diagnosis tool in the future. Our experiments show that our contribution is an accurate system for HCC detection, with a small cohort of patients, but representing a high volume of image data to be processed. This work encourages us to conduct deeper researches for detecting complex HCC cases for larger patients cohorts.

Cloud SLA Terms Analysis Based On Ontology

Abstract Services in cloud computing run under specified constraints defined in Service Level Agreement (SLA) which becomes the basic core that guarantee the Quality of Service (QoS). However, the ambiguity in agreement terms makes the consumer face new challenges especially in understanding and analyzing SLA document. These challenges increasingly rise when the consumer uses services from multiple providers; since each one has its own SLA terminology. In this paper, we have significantly automated the process of managing and analyzing cloud SLA using semantic web technologies like OWL (Ontology Web Language), SWRL (Semantic Web Rule Language) and SQWRL (Semantic Query-Enhanced Web Rule Language). We describe the cloud SLA modeling and analyzing approach that assists consumers automatically analyze terms of various SLA documents. A prototype implementation demonstrates the feasibility and the efficiency of our approach.