Problèmes d’interférences arabe/français dans les productions écrites d’élèves de secondaire

RÉSUMÉ. L’expression écrite est une activité complexe qui occupe une place importante dans l’enseignement/apprentissage du français langue étrangère en Algérie. Enseigner le français aux arabophones donne lieu à des contacts entre l’arabe langue maternelle et le français langue étrangère. Ces contacts engendrent des erreurs qui influencent les écrits des apprenants. Cet article vise à repérer, analyser et comprendre les erreurs interférentielles dans les productions écrites des élèves algériens. Le but ultime étant d’y remédier. Pour ce faire, une analyse d’erreurs sera appliquée à un corpus de 30 copies de productions écrites réalisées par des élèves de 3éme année secondaire ainsi qu’une analyse contrastive des systèmes des deux langues en question : l’Arabe et le Français. L’analyse des données recueillies a révélé que ce problème pourrait être provoqué par 3 facteurs : les pratiques scripturales des élèves notamment la difficulté de mettre en œuvre les étapes du processus de production textuelle, les confrontations des deux systèmes linguistiques arabe et français au moment de l’apprentissage ainsi que les pratiques enseignantes, telle que l’évaluation, qui ne ciblent pas les erreurs interférentielles. Mots-clés : contact des langues, erreurs, évaluation, interférences, langue étrangère, langue maternelle, production écrite. ABSTRACT. Written expression is a complex activity that occupies an important place in the teaching / learning of French as a foreign language in Algeria. Teaching French to Arabic speakers leads to contacts between Arabic mother tongue and French as a foreign language. These contacts generate errors that influence student’s writings. This article aims to identify, analyze and understand interferential errors in the written productions of Algerian students. The ultimate goal is to fix it. To do this, an analysis of errors will be applied to a corpus of 30 copies of written productions made by students of the 3rd year secondary as well as a contrastive analysis of the systems of the two languages in question: Arabic and French.The analysis of the collected data revealed that this problem could be caused by 3 factors: the scriptural practices of the pupils notably the difficulty to implement the stages of the process of textual production, the confrontations of the two linguistic systems Arabic and French also to teaching practices, such as evaluation, that do not target interferential errors. Keywords: error, evaluation, foreign language, interference, language contact, mother tongue, written production

Service migration versus service replication in Multi-access Edge Computing

Envisioned low-latency services in 5G, like automated driving, will rely mainly on Multi-access Edge Computing (MEC) to reduce the distance, and hence latency, between users and the remote applications. MEC hosts will be deployed close to mobile base stations, constituting a highly distributed computing platform. However, user mobility may raise the need to migrate a MEC application among MEC hosts to ensure always connecting users to the optimal server, in terms of geographical proximity, Quality of Service (QoS), etc. However, service migration may introduce: (i) latency for users due to the downtime duration; (ii) cost for the network operator as it consumes bandwidth to migrate services. One solution could be the use of service replication, which pro-actively replicates the service to avoid service migration and ensure low latency access. Service replication induces cost in terms of storage, though, requiring a careful study on the number of service to replicate and distribute in MEC. In this paper, we propose to compare service migration and service replication via an analytical model. The proposed model captures the relation between user mobility and service duration on service replication as well as service migration costs. The obtained results allow to propose recommendations between using service migration or service replication according to user mobility and the number of replicates to use for two types of service.This work was partially funded by the European Union’s Horizon 2020 research and innovation program under the 5GTransformer project (grant no. 761536

Cost-efficient Slicing in Virtual Radio Access Networks

Network slicing is a promising technique that has vastly increased the man- ifoldness of network services to be supported through isolated slices in a shared radio access network (RAN). Due to resource isolation, effective re- source allocation for coexisting multiple network slices is essential to maxi- mize network resource efficiency. However, the increased network flexibility and programmability offered by virtualized radio access networks (vRANs) come at the expense of a higher consumption of computing resources at the network edge. Additionally, the relationship between resource efficiency and computing cost minimization is still fuzzy. In this paper, we first perform extensive experiments using the vRAN testbed we developed and assess the vRAN resource consumption under different settings and a varying number of users. Then, leveraging our experimental findings, we formulate the prob- lem of cost-efficient network slice dimensioning, named cost-efficient slicing (CES), which maximizes the difference between total utility and CPU cost of network slices. Numerical results confirm that our solution leads to a cost-efficient resource slicing, while also accomplishing performance isolation and guaranteeing the target data rate and delay specified in the service level agreements

Exposing radio network information in a MEC-in-NFV environment: the RNISaaS concept

IEEE Conference on Network Softwarization (2019)The Radio Network Information Service (RNIS) is one of the key services provided by a Multi-access Edge Computing Platform (MEP), as specified in the relevant ETSI MEC standards. It is responsible for interacting with the Radio Access Network (RAN), collecting RAN-level information about User Equipment (UE) and exposing it to mobile edge applications, which can in turn utilize it to dynamically adjust their behavior to optimally match the RAN conditions. Putting the provision of RNIS in the context of the emerging MEC-in-NFV environment, where the components and services of the MEC architecture, including the MEP itself, are integrated in an NFV environment and are delivered on top of a virtualized infrastructure, we present our standards-compliant RNIS implementation based on OpenAirInterface and study critical performance aspects for its provision as a virtual function. Since the RNIS design and operation follows the publish-subscribe model, we provide alternative implementations using different message brokering technologies (RabbitMQ and Apache Kafka), and compare their use and performance in an effort to evaluate their suitability for providing RNIS in an as-a-service manner.This work has been partially funded by the EC H2020 5G-Transformer Project (grant no. 761536)

Latency and Availability Driven VNF Placement in a MEC-NFV Environment

Multi-access Edge Computing (MEC) is gaining momentum as it is considered as one of the enablers of 5G ultra-Reliable Low-Latency Communications (uRLLC) services. MEC deploys computation resources close to the end user, enabling to reduce drastically the end-to-end latency. ETSI has recently leveraged the MEC architecture to run all MEC entities, including MEC applications, as Virtual Network Functions (VNF) in a Network Functions Virtualization (NFV) environment. This evolution allows taking advantage of the mature architecture and the enabling tools of NFV, including the potential to apply a variety of service-tailored function placement algorithms. However, the latter need to be carefully designed in case of MEC applications such as uRLLC, where service access latency is critical. In this paper, we propose a novel placement scheme applicable to a MEC in NFV environment. In particular, we propose a formulation of the problem of VNF placement tailored to uRLLC as an optimization problem of two conflicting objectives, namely minimizing access latency and maximizing service availability. To deal with the complexity of the problem, we propose a Genetic Algorithm to solve it, which we compare with a CPLEX implementation of our model. Our numerical results show that our heuristic algorithm runs efficiently and produces solutions that approximate well the optimal, reducing latency and providing a highly-available service.This work has been partially supported by the European Union’s H2020 5G-Transformer Project (grant no. 761536

Dynamic slicing of RAN resources for heterogeneous coexisting 5G services

This paper has been presented at: IEEE Global Communications Conference, GLOBECOM 2019Network slicing is one of the key components allow-ing to support the envisioned 5G services, which are organized in three different classes: Enhanced Mobile Broadband (eMBB), massive Machine Type Communication (mMTC), and Ultra-Reliable and Low-Latency Communication (URLLC). Network Slicing relies on the concept of Network Softwarization (Software Defined Networking - SDN and Network Functions Virtualization - NFV) to share a common infrastructure and build virtual instances (slices) of the network tailored to the needs of dif-ferent 5G services. Although it is straightforward to slice and isolate computing and network resources for Core Network (CN) elements, isolating and slicing Radio Access Network (RAN) resources is still challenging. In this paper, we leverage a two-level MAC scheduling architecture and provide a resource sharing algorithm to compute and dynamically adjust the necessary radio resources to be used by each deployed network slice, covering eMBB and URLLC slices. Simulation results clearly indicate the ability of our solution to slice the RAN resources and satisfy the heterogeneous requirements of both types of network slices.This work was partially supported by the European Union’s Horizon 2020 Research and Innovation Program under the 5G!Drones (Grant No. 857031) and 5G-TRANSFORMER (Grant No. 761536) projects

Characterizing the Computational and Memory Requirements of Virtual RANs

The virtualization of radio access networks (RANs) is emerging as a key component of future wireless systems, as it brings agility to the RAN architecture and offers degrees of design freedom. In this paper, we investigate and characterize the computational and memory requirements of virtual RANs. To this end, we build a virtual RAN test-bed leveraging the srsRAN open-source mobile communication platform and general-purpose processor-based servers. Through extensive experiments, we profile the consumption of computing and memory resources, and we assess the system performance. Further, we build regression models to predict the system behavior as the number of connected users increases, under diverse radio transmission settings. In so doing, we develop a methodology and prediction models that can help designing and optimizing virtual RANs

Split Federated Learning for 6G Enabled-Networks: Requirements, Challenges and Future Directions

Sixth-generation (6G) networks anticipate intelligently supporting a wide range of smart services and innovative applications. Such a context urges a heavy usage of Machine Learning (ML) techniques, particularly Deep Learning (DL), to foster innovation and ease the deployment of intelligent network functions/operations, which are able to fulfill the various requirements of the envisioned 6G services. Specifically, collaborative ML/DL consists of deploying a set of distributed agents that collaboratively train learning models without sharing their data, thus improving data privacy and reducing the time/communication overhead. This work provides a comprehensive study on how collaborative learning can be effectively deployed over 6G wireless networks. In particular, our study focuses on Split Federated Learning (SFL), a technique recently emerged promising better performance compared with existing collaborative learning approaches. We first provide an overview of three emerging collaborative learning paradigms, including federated learning, split learning, and split federated learning, as well as of 6G networks along with their main vision and timeline of key developments. We then highlight the need for split federated learning towards the upcoming 6G networks in every aspect, including 6G technologies (e.g., intelligent physical layer, intelligent edge computing, zero-touch network management, intelligent resource management) and 6G use cases (e.g., smart grid 2.0, Industry 5.0, connected and autonomous systems). Furthermore, we review existing datasets along with frameworks that can help in implementing SFL for 6G networks. We finally identify key technical challenges, open issues, and future research directions related to SFL-enabled 6G networks