Karim Bouamrane

Towards a New Model of Storage and Access to Data in Big Data and Cloud Computing

Thetechnologicalrevolutionintegratingmultipleinformationsourcesandextensionofcomputer scienceindifferentsectorsledtotheexplosionofthedataquantities,whichreflectsthescalingofvolumes,numbersandtypes.Thesemassiveincreaseshaveresultedinthedevelopmentofnewlocation techniquesandaccesstodata.Thefinalstepsinthisevolutionhaveemergednewtechnologies:Cloud andBigData.ThereferenceimplementationoftheCloudsandBigDatastorageisincontestablythe HadoopDistributedFileSystem(HDFS).Thislatterisbasedontheseparationofmetadatatodatathat consistsinthecentralizationandisolationofthemetadataofstorageservers.Inthispaper,theauthors proposeanapproachtoimprovetheservicemetadataforHadooptomaintainconsistencywithout muchcompromisingperformanceandscalabilityofmetadatabysuggestingamixedsolutionbetween centralizationanddistributionofmetadatatoenhancetheperformanceandscalabilityofthemodel. KeywoRDS Big Data, Clouds of Storage, Hadoop, HDFS, MapReduce, Metadata

Towards a New Multicriteria Decision Support Method Using Fuzzy Measures and the Choquet Integral

In literature, there is a large panoply of multicriteria analysis methods MCAM, each one is characterized by the nature of its input data, the way to edit its outputs and the operations used to perform calculations especially the performances aggregation. Aggregation is the operation consisting in grouping several quantities in a unique value in order to facilitate the manipulation and the interpretation of the original values. MCAM are classified according to the type of aggregation that they perform, so we can distinguish total, partial and local aggregation. Each MCAM has advantages and suffers from some limits. In this paper, the authors proposed a new multicriteria analysis method AMFI dedicated to solve ranking decision support problems. AMFI is based on the use of fuzzy measures and Choquet integral to represent interactions between criteria and improve the coherence of the results. The authors proceeded to a series of experimentations allowing highlighting theoretical elements of the proposed method and they performed sensitivity analysis to test its robustness.

Storage management of hazardous containers using the genetic algorithm

Abstract This work discusses the problem of dangerous containers storage in a container terminal. Container terminal represents an essential intermodal interfaces for global transportation network. Several materials handling possible to move containers at the port to better meet the needs of ships awaiting loading or unloading. Have a good organization of the terminals container storage area requires a special effort. Containers search times can be considerable and lead to delays causing financial penalties for terminal management operators. An optimal location for a container in a terminal is very important for companies because this operation reduces transportation costs. In this article, we propose an approach for the placement problem of hazardous containers through the description of an optimization model to solve and optimize available storage space. The interest of this work is to develop a computer tool to enable the identification of the best location of a hazardous container using the Genetic Algorithm.

ALEM: A Reference Model for Educational Adaptive Web Applications

The adaptive hypermedia systems or adaptive web applications is a research area between hypermedia and user modeling. It can customize hyperspace to different users. The existing reference models are generic and are not dedicated to educational systems. This chapter presents in the first part, a reference model that is specific to adaptive educational hypermedia systems. This model is called ALEM (Adaptive Learning Environment Model). It consists of a domain model, a learner model, a course structuring model and an adaptation model. The main contribution of this model is modeling the adaptive learning curriculum. Furthermore, we develop the UML Tutor application which is an educational adaptive hypermedia system based on our reference model.

Une nouvelle approche pour la régulation et la reconfiguration spatiale d’un réseau de transport urbain collectif

This article proposes the integration of an approach based on cellular automata for the regulation and the reconfiguration of urban transportation systems. The complexity of an UTS has a dramatic effect on disturbances. Incidents are very complicated when there are several areas particularly concerned or blocking a route for a longer or shorter. In this case, appropriate regulation action or any particular route changes are necessary. We focus in this paper to integrate this new approach in an UTS regulating platform SARRT to improve collective performance point of view response time and data storage. To implement this approach we use a Boolean Modeling Language (BML) adopted by the cellular inference engine (CIE).

Un système d'aide à la régulation pour un réseau de transport urbain collectif : Vers une approche de raisonnement à base de cas

This paper presents a classification system based on a case-based reasoning. This approach allowed us to associate a profile of scenario of regulation actions to regulate the disturbances that appear in an urban transportation system. Displacements of the people are always in the center of the concerns of the persons in charge for the local communities. The quality of transport is an essential element of competitiveness. This work contributes to the advance in the themes of the regulation of the traffic of an urban transportation system (bus and tram. This problem worries the companies of transport more and more, especially because users become increasingly demanding, that competition becomes increasingly hard and that the owners have few means of envisaging the appearance of the disturbances which affect the traffic.

A Traveller Information System: Minimisation of the Number of Graphs’ Nodes Involved When Processing Route Requests

Abstract The number of people using public transport is continuously increasing. Transport companies want to fulfil travellers’ expectations wherever possible. However, the great number of public transport companies operating in the same area can sometimes confuse travellers as to which route they should take and how to obtain the information relative to their journey. In this paper we suggest integrating several traveller information systems from different companies into the same multimodal information system, offering companies the choice not to share their data. This encourages them to join the system. Additionally, we have minimised the number of nodes involved when processing travellers’ requests in order to simplify the calculation process. To put our plan into action, we have opted for a multi-agent system coupled with the Voronoi decomposition for managing the network.

The MAV-ES Data Integration Approach for Decisional Information Systems DIS: A Case on Epidemiologic Monitoring

Massive data to facilitate decision making for organizations and their corporate users exist in many forms, types and formats. Importantly, the acquisition and retrieval of relevant supporting information should be timely, precise and complete. Unfortunately, due to differences in syntax and semantics, the extraction and integration of available semi-structured data from different sources often fail. Needs for seamless and effective data integration so as to access, retrieve and use information from diverse data sources cannot be overly emphasized. Moreover, information external to organizations may also often have to be sourced for the intended users through a smart data integration system. Owing to the open, dynamic and heterogeneity nature of data, data integration is becoming an increasingly complex process. A new data integration approach encapsulating mediator systems and data warehouse is proposed here. Aside from the heterogeneity of data sources, other data integration design problems include distinguishing the definition of the global schema, the mappings and query processing. In order to meet all of these challenges, the authors of this paper advocate an approach named MAV-ES, which is characterized by an architecture based on a global schema, partial schemas and a set of sources. The primary benefit of this architecture is that it combines the two basic GAV and LAV approaches so as to realize added-value benefits of the mixed approach.

Using a mapping knowledge base in a system for (semi-)automatic loading of XML data into relational databases

Very often the need is felt to store information extracted from the web, from databases or from documents and converted to XML (eXtensible Markup Language) in a database, in most cases, in a relational one, in order to be able to query this database for further operational or strategic decision-making. Unfortunately the XML files do not always have the same structure, and their elements (tags) do not always have the same name. In many companies, a correspondence (mapping) between elements of the XML files and the columns of the tables in the target database is still established manually. In this paper we present a system which loads the data contained in XML files into several tables of a relational database. The system supplies the user with mappings which are based on similarities with mappings already performed by the user in the past. User intervention is therefore required less frequently over time, resulting in full automation of the process of loading data into the target database.