• Prochain séminaire

    November 16th 2017 par B. Berruet : Indoor localization performance analysis  with CSI-based feature extraction algorithms

    The expansion of location-based applications for monitoring the crowd and giving specific services in personal assitance activities requires the development of solutions working with the ambient connectivity and without industrial installations. That requirement is widely covered by the global navigation satellite systems (GNSS) present all around the world but the GNSS signals is severely attenuated in the urban canyon or the indoor environments. The wireless communication systems such as the WiFi or the bluetooth low enery (BLE) become then for the industrial and the academic researches as an alternative solution to the GNSS in these complex scenarios. Hence, many propositions emerge from the ashes based on different localization approaches. My thesis looks for developing a system respecting the IoT and ambient connectivity paradigms: Battery saving, low-cost and fast deployement. From this, the fingerprinting approach based on the channel state information (CSI) completes the above requirements. CSI reveals the influence of the channel propagation on the transmitted signal such as the multiple paths taken by this one or the fading. The fingerprinting approach consists in acquiring the CSI at regularly spaced positions in the study field. In this way, the system try to determine a function from the signal space to the spatial space. One solution is to implement machine learning techniques. My last works was to study the spectral methods such as the principal component analysis (PCA) in order to improve the machine learning algorithm.

  • Ils ont soutenu…

    • Omar DIB a soutenu le 6 novembre 2017 sa thèse de Doctorat intitulée : Reroutage dynamique des passagers dans les réseaux de transport multimodaux
    • Oumaya BAALA a soutenu le 10 novembre son Habilitation à Diriger des Recherches intitulée : De la modélisation et de l’optimisation de la qualité des systèmes multi-échelles
  • Rentrée 2017, nous souhaitons la bienvenue aux nouveaux membres OPERA !

    • Hamza Ouarnoughi, docteur en Informatique, nous rejoint en tant qu’Attaché Temporaire d’Enseignement et de Recherche pour renforcer l’équipe projet MISC. Il contribuera également aux enseignements du département INFO.
    • Cherifa Boucetta, docteur en Informatique, nous rejoint en tant qu’Attaché Temporaire d’Enseignement et de Recherche pour renforcer l’équipe projet IoT. Elle contribuera également aux enseignements du département INFO.
  • Séminaire passé

    26 octobre 2017 par L. Li : Conception de la chaîne d’approvisionnement de l’hydrogène

    Résumé :

    L’hydrogène est considéré depuis longtemps comme un carburant écologique plein d’avenir parce qu’il ne produit aucune émission polluante. Après de grandes avancées technologiques relatives à l’hydrogène ces dernières années, de nouvelles problématiques émergent. Un des grands défis actuels concerne le déploiement des infrastructures associées. Dans ce contexte, le travail de recherche porte sur la conception d’une chaîne d’approvisionnement de l’hydrogène. La première partie du travail a porté sur un état de l’art du domaine et fera l’objet de l’exposé.

  • Séminaire passé

    21 septembre 2017 par H. Ouarnoughi : Autonomic VM placement on hybrid storage system in IaaS cloud

    Résumé :

    IaaS cloud providers offer virtualized resources (CPU, storage, and network) as Virtual Machines (VM). The growth and highly competitive nature of this economy has compelled them to optimize the use of their data centers, in order to offer attractive services at a lower cost. In addition to investments related to infrastructure purchase and cost of use, energy efficiency is a major point of expenditure (2\% of world consumption) and is constantly increasing. Its control represents a vital opportunity. From a technical point of view, the control of energy consumption is mainly based on consolidation approaches. These approaches, which exclusively take into account the CPU use of physical machines (PM) for the VM’s placement, present however many drawbacks. Indeed, recent studies have shown that storage systems and disk I/O represent a significant part of the data center energy consumption (between 14% and 40%).

    In this thesis we propose a new autonomic model for VM placement optimization based on MAPE-K (Monitor, Analyze, Plan, Execute, Knowledge) whereby in addition to CPU, VM I/O and related storage systems are considered. Our first contribution proposes a multilevel VM I/O tracer which overcomes the limitations of existing I/O monitoring tools. In the Analyze step, the collected I/O traces are introduced in a cost model which takes into account the VM I/O profile, the storage system characteristics, and the cloud environment constraints. We also analyze the complementarity between the two main storage classes, resulting in a hybrid storage model exploiting the advantages of each. Indeed, Hard Disk Drives (HDD) represent energy-intensive and inefficient devices compared to compute units. However, their low cost per gigabyte and their long lifetime may constitute positive arguments. Unlike HDD, flash-based Solid-State Disks (SSD) are more efficient and consume less power, but their high cost per gigabyte and their short lifetime (compared to HDD) represent major constraints.
    The Plan phase has initially resulted in an extension of CloudSim to take into account VM I/O, the hybrid nature of the storage system, as well as the implementation of the previously proposed cost model. Secondly, we proposed several heuristics based on our cost model, integrated and evaluated using CloudSim. Finally, we showed that our contribution improves existing approaches of VM placement optimization by a factor of three.

  • Séminaire passé

    01 juin 2017 par J. Guo : A partition-based exact method for graph coloring problem and its application to dynamic resource allocation

    Résumé :

    Graph coloring problem is a well-known traditional NP-complete problem and designing effective exact algorithms for it is still an interesting topic. By analyzing the graph structure, an exact algorithm called TexaCol is proposed which is capable of getting all solutions of the legal k-coloring for a graph G as well as the chromatic polynomial of G. The algorithm includes three steps: the maximal clique decomposition, the suite construction and the vertices coloring. Furthermore, two exact graph coloring algorithms, PexaCol and AexaCol, have been designed, which are able to obtain partial best solutions and all best solutions of G respectively. Finally, on the basis of these static methods, a dynamic graph coloring algorithm is proposed to effectively solve the dynamic cluster resource assignment problem for Device-to-Device networks. The results show that this dynamic algorithm has good performance in resource utilization, runtime and scalability.