Mise en oeuvre d’une plateforme de gestion et de dissémination des connaissances pour des réseaux autonomiques

The growth of the Internet, the emergence of new needs expressed by the advent of smart devices ( smartphones, touchpads , etc. ) and the development of new underlying applications induce many changes in the use of information technology in our everyday life and in all sectors. This new use that match new needs required to rethink the foundation of the network architecture itself, which has resulted in the emergence of new concepts based on a "use-centeric" view instead of a "network-centric" view. In fact, the control mechanisms of the transmission network must not only exploit the information on data, control and management planes, but also the knowledge acquired or learned by inductive or deductive inference on the current state of the network (traffic, resources, the rendering of the application, etc.) to accelerate decision making by the control elements of the network. This thesis is dealing with this latter aspect, which makes it consistent with work done on autonomic networks. It is about conceiving and implementing methods for the management, distribution and exploitation of knowledge necessary for the proper functioning of the transmission network. The knowledge plane that we implemented is based on both the idea of developing a management within an adaptive hierarchical structure where only some selected nodes are responsible for the dissemination of knowledge and the idea of linking these nodes through a spanning set of specialized networks to facilitate the exploitation of this knowledge. Compared to traditionally used platforms, the one developed in this thesis clearly shows the interest of the developed algorithms in terms of access time, distribution and load sharing between the control nodes for knowledge management. For validation purposes, our platform was tested on two application examples : Cloud computing and smart gridsLa croissance du réseau Internet, l'émergence de nouveaux besoins par l'avènement des terminaux dits intelligents (smartphones, tablettes tactiles, etc.) et l'apparition de nouvelles applications sous-jacentes induisent de nombreuses mutations dans l'usage de plus en plus massif des technologies de l'information dans notre vie quotidienne et dans tous les secteurs d'activités. Ces nouveaux usages ont nécessité de repenser le fondement même de l'architecture réseau qui a eu pour conséquence l'émergence de nouveaux concepts basés sur une vue "centrée sur l'usage" en lieu et place d'une vue "centrée sur le réseau". De fait, les mécanismes de contrôle du réseau de transport doivent non seulement exploiter les informations relatives aux plans de données, de contrôle et de gestion, mais aussi les connaissances, acquises ou apprises par inférence déductive ou inductive, sur l'état courant du réseau (trafic, ressources, rendu de l'application, etc.) de manière à accélérer la prise de décision par les éléments de contrôle du réseau. Les travaux faits dans le cadre de cette thèse concernent ce dernier aspect et rejoignent plus généralement ceux tournés sur les réseaux autonomiques. Il s'agit dans cette thèse de mettre en oeuvre des méthodes relatives à la gestion, à la distribution et à l'exploitation des connaissances nécessaires au bon fonctionnement du réseau de transport. Le plan de connaissances mis en oeuvre ici se base à la fois sur l'idée de développer une gestion au sein d'une structure hiérarchisée et adaptative où seuls certains noeuds sélectionnés sont en charge de la dissémination des connaissances et l'idée de relier ces noeuds au travers d'un ensemble de réseaux couvrants spécialisés permettant de faciliter l'exploitation de ces connaissances. Comparée aux plateformes traditionnellement utilisées, celle développée dans le cadre de cette thèse montre clairement l'intérêt des algorithmes élaborés au regard des temps d'accès, de distribution et de partage de charge entre les noeuds de contrôle pour la gestion des connaissances. A des fins de validation, cette plateforme a été utilisée dans deux exemples d'application: le Cloud computing et les smartgrid

Compaction mechanics of plastically deformable dry granules

To improve the understanding of how dry granulation and in particular, granule solid fraction (SF) impact the compaction behavior of plastically deformable microcrystalline cellulose (MCC), in this study, the Drucker Prager Cap (DPC) model parameters were calibrated using monodisperse MCC dry granules as model granules. Dry granules were produced as directly compressed small cylindrical compacts of MCC with SF in the range of 0.40 to 0.70 which were monodisperse in both size and SF. Virgin MCC powder and granules were compressed into tablets with SF in the range of 0.70 to 0.90. The DPC parameters (cohesion, internal friction angle, cap eccentricity, and hydrostatic yield stress), Young's modulus and Poisson's ratio were experimentally determined from diametrical and uniaxial compression, and in-die compaction tests. Results showed that calibration of the shear failure surface only may be adequate for MCC granules when the DPC model is completely calibrated for virgin MCC. Increasing granule SF significantly decreased the cohesion only. All other parameters were impacted by the tablet SF only. In the 2D yield surface, only the shear failure surface expanded as the granule SF increased. MCC of any granulation status requires the same in-die compaction stress state for densification to a given tablet solid fraction

Contributions aux réseaux intelligents - The Next Generation Networking and Internet

The continuous growth of data traffic, the emergence of network virtualization and the ever-increasing use of mobile devices in modern networks have highlighted the various problems associated with the conventional Internet architecture. Therefore, monitoring and controlling tasks are becoming increasingly complex and specialized. In this context, it has become urgent to rethink the philosophy and architecture of network control mechanisms by making them more autonomous and adaptive to the dynamic contexts. To design these new networks, several research strategies have been proposed to address the scalability, reliability and availability challenges of real-time traffic, thus ensuring the quality of the user experience. This Habilitation thesis summarizes my research work in these areas over the last few years (2013-2022). It describes my main contributions in what is now called "new generation networks or adaptive networks". It also presents my work methods and philosophy, based on these last years' experience, as well as some perspectives for future worksLa croissance continue du trafic de données, l'émergence de la virtualisation des réseaux ainsi que l'utilisation sans cesse croissante d'équipements mobiles dans les réseaux modernes ont mis en lumière les nombreux problèmes inhérents à l'architecture conventionnelle de l'Internet. Ainsi, la tâche de gestion et de contrôle des informations devient de plus en plus complexe et spécialisée. Dans ce contexte, il est devenu urgent de repenser la philosophie et l’architecture des mécanismes de contrôle des réseaux en rendant ces derniers plus autonomes avec une adaptabilité accrue à leurs contextes dynamiques. Pour concevoir ces nouveaux réseaux, plusieurs stratégies de recherche ont été proposées afin de relever les défis de l'évolutivité, de la fiabilité et de la disponibilité du trafic en temps réel, garantissant ainsi La qualité de l'expérience de l'utilisateur. Cette thèse d'Habilitation à Diriger des Recherches résume mes travaux de recherche effectués dans ces thématiques au cours de ces dernières d’années (2013-2022). Elle décrit mes principales contributions dans ce qui est appelé aujourd’hui « les réseaux intelligents ou encore les réseaux de nouvelle génération ou pour certains les réseaux adaptatifs». Elle met en avant également ma méthode et ma philosophie de travail, fruit de mon expérience de ces dernières années ainsi que certaines perspectives pour des travaux futurs

A knowledge management and dissemination platform for autonomic networks

La croissance du réseau Internet, l'émergence de nouveaux besoins par l'avènement des terminaux dits intelligents (smartphones, tablettes tactiles, etc.) et l'apparition de nouvelles applications sous-jacentes induisent de nombreuses mutations dans l'usage de plus en plus massif des technologies de l'information dans notre vie quotidienne et dans tous les secteurs d'activités. Ces nouveaux usages ont nécessité de repenser le fondement même de l'architecture réseau qui a eu pour conséquence l'émergence de nouveaux concepts basés sur une vue "centrée sur l'usage" en lieu et place d'une vue "centrée sur le réseau". De fait, les mécanismes de contrôle du réseau de transport doivent non seulement exploiter les informations relatives aux plans de données, de contrôle et de gestion, mais aussi les connaissances, acquises ou apprises par inférence déductive ou inductive, sur l'état courant du réseau (trafic, ressources, rendu de l'application, etc.) de manière à accélérer la prise de décision par les éléments de contrôle du réseau. Les travaux faits dans le cadre de cette thèse concernent ce dernier aspect et rejoignent plus généralement ceux tournés sur les réseaux autonomiques. Il s'agit dans cette thèse de mettre en oeuvre des méthodes relatives à la gestion, à la distribution et à l'exploitation des connaissances nécessaires au bon fonctionnement du réseau de transport. Le plan de connaissances mis en oeuvre ici se base à la fois sur l'idée de développer une gestion au sein d'une structure hiérarchisée et adaptative où seuls certains noeuds sélectionnés sont en charge de la dissémination des connaissances et l'idée de relier ces noeuds au travers d'un ensemble de réseaux couvrants spécialisés permettant de faciliter l'exploitation de ces connaissances. Comparée aux plateformes traditionnellement utilisées, celle développée dans le cadre de cette thèse montre clairement l'intérêt des algorithmes élaborés au regard des temps d'accès, de distribution et de partage de charge entre les noeuds de contrôle pour la gestion des connaissances. A des fins de validation, cette plateforme a été utilisée dans deux exemples d'application: le Cloud computing et les smartgridsThe growth of the Internet, the emergence of new needs expressed by the advent of smart devices ( smartphones, touchpads , etc. ) and the development of new underlying applications induce many changes in the use of information technology in our everyday life and in all sectors. This new use that match new needs required to rethink the foundation of the network architecture itself, which has resulted in the emergence of new concepts based on a "use-centeric" view instead of a "network-centric" view. In fact, the control mechanisms of the transmission network must not only exploit the information on data, control and management planes, but also the knowledge acquired or learned by inductive or deductive inference on the current state of the network (traffic, resources, the rendering of the application, etc.) to accelerate decision making by the control elements of the network. This thesis is dealing with this latter aspect, which makes it consistent with work done on autonomic networks. It is about conceiving and implementing methods for the management, distribution and exploitation of knowledge necessary for the proper functioning of the transmission network. The knowledge plane that we implemented is based on both the idea of developing a management within an adaptive hierarchical structure where only some selected nodes are responsible for the dissemination of knowledge and the idea of linking these nodes through a spanning set of specialized networks to facilitate the exploitation of this knowledge. Compared to traditionally used platforms, the one developed in this thesis clearly shows the interest of the developed algorithms in terms of access time, distribution and load sharing between the control nodes for knowledge management. For validation purposes, our platform was tested on two application examples : Cloud computing and smart grid

Multivariate Synergies in Pharmaceutical Roll Compaction : The quality influence of raw materials and process parameters by design of experiments

Roll compaction is a continuous process commonly used in the pharmaceutical industry for dry granulation of moisture and heat sensitive powder blends. It is intended to increase bulk density and improve flowability. Roll compaction is a complex process that depends on many factors, such as feed powder properties, processing conditions and system layout. Some of the variability in the process remains unexplained. Accordingly, modeling tools are needed to understand the properties and the interrelations between raw materials, process parameters and the quality of the product. It is important to look at the whole manufacturing chain from raw materials to tablet properties. The main objective of this thesis was to investigate the impact of raw materials, process parameters and system design variations on the quality of intermediate and final roll compaction products, as well as their interrelations. In order to do so, we have conducted a series of systematic experimental studies and utilized chemometric tools, such as design of experiments, latent variable models (i.e. PCA, OPLS and O2PLS) as well as mechanistic models based on the rolling theory of granular solids developed by Johanson (1965). More specifically, we have developed a modeling approach to elucidate the influence of different brittle filler qualities of mannitol and dicalcium phosphate and their physical properties (i.e. flowability, particle size and compactability) on intermediate and final product quality. This approach allows the possibility of introducing new fillers without additional experiments, provided that they are within the previously mapped design space. Additionally, this approach is generic and could be extended beyond fillers. Furthermore, in contrast to many other materials, the results revealed that some qualities of the investigated fillers demonstrated improved compactability following roll compaction. In one study, we identified the design space for a roll compaction process using a risk-based approach. The influence of process parameters (i.e. roll force, roll speed, roll gap and milling screen size) on different ribbon, granule and tablet properties was evaluated. In another study, we demonstrated the significant added value of the combination of near-infrared chemical imaging, texture analysis and multivariate methods in the quality assessment of the intermediate and final roll compaction products. Finally, we have also studied the roll compaction of an intermediate drug load formulation at different scales and using roll compactors with different feed screw mechanisms (i.e. horizontal and vertical). The horizontal feed screw roll compactor was also equipped with an instrumented roll technology allowing the measurement of normal stress on ribbon. Ribbon porosity was primarily found to be a function of normal stress, exhibiting a quadratic relationship. A similar quadratic relationship was also observed between roll force and ribbon porosity of the vertically fed roll compactor. A combination of design of experiments, latent variable and mechanistic models led to a better understanding of the critical process parameters and showed that scale up/transfer between equipment is feasible

When NLP meets SDN : an application to Global Internet eXchange Network

Software-Defined Networking (SDN) and its extension Intent-Based Networking (IBN) are network paradigms that enable dynamic, programmatically efficient network configuration. IBN allows network operators to express an outcome or business objective without the low-level configurations necessary to program the network to achieve these demands. Existing research proposals for IBN introduce several systems to translate users intents into network infrastructure configurations. Despite the positive aspects of these proposals, they still suffer from many drawbacks. Some require users to learn a new intent definition language. Some others may lack the appropriate grammar to make these frameworks recognize the intent correctly. In this paper, we introduce a framework leveraging the capabilities of Natural Language Processing (NLP) for network management from an operator utterances. In order to understand natural language, our framework uses the sequence-to-sequence (seq2seq) learning model based on recurrent neural networks (LSTM). The model has been improved by using word embedding and user feedback. As a proof of concept, we implement our framework for network management in a Global Internet eXchange Network and evaluate its practicality regarding NLP accuracy and network performance

"Knowledge Dissemination for Autonomic Networks"

International audienc

Knowledge Dissemination for Autonomic Networks

International audienceAutonomic computing is a new paradigm inspired by the biological world. It allows networks to self-organize control decisions. To ensure an efficient self-organization, an autonomic network must define a new distributed and decentralized plane containing all the network knowledge, called "knowledge plane". In this paper, we propose a new knowledge dissemination mechanisms in order to maintain this knowledge plane. The developed approach is composed by three modules to address scalability and interoperability issues: (1) cluster the network nodes and elect a leader for each cluster to contain the knowledge, (2) use an overlay network to disseminate knowledge between leaders for interoperability concerns and, (3)disseminate only useful knowledge to nodes in each cluster to reduce the amount of knowledge to be distributed. To evaluate our approach, we construct a knowledge plan based on QoE measurement. Numerical results obtained for IPTV different traffics level merged on operators network show that our approach improves clearly performances regarding load balancing charges

Knowledge Dissemination for Autonomic Network

International audienceAutonomic computing is a new paradigm inspired by the biological world. It allows networks to self-organize control decisions. To ensure an efficient self-organization, an autonomic network must define a new distributed and decentralized plane containing all the network knowledge, called "knowledge plane". In this paper, we propose a new knowledge dissemination mechanisms in order to maintain this knowledge plane. The developed approach is composed by three modules to address scalability and interoperability issues: (1) cluster the network nodes and elect a leader for each cluster to contain the knowledge, (2) use an overlay network to disseminate knowledge between leaders for interoperability concerns and, (3)disseminate only useful knowledge to nodes in each cluster to reduce the amount of knowledge to be distributed. To evaluate our approach, we construct a knowledge plan based on QoE measurement. Numerical results obtained for IPTV different traffics level merged on operators network show that our approach improves clearly performances regarding load balancing charges

Adaptive State Consistency for Distributed ONOS Controllers

International audienceLogically-centralized but physically-distributed SDN controllers are mainly used in large-scale SDN networks for scalability, performance and reliability reasons. These controllers host various applications that have different requirements in terms of performance, availability and consistency. Current SDN controller platform designs employ conventional strong consistency models so that the SDN applications running on top of the distributed controllers can benefit from strong consistency guarantees for network state updates. However, in large-scale deployments, ensuring strong consistency is usually achieved at the cost of generating performance overheads and limiting system availability. That makes weaker optimistic consistency models such as the eventual consistency model more attractive for SDN controller platform applications with high-availability and scalability requirements. In this paper, we argue that the use of the standard eventual consistency models, though a necessity for efficient scalability in modern SDN systems, provides no bounds on the state inconsistencies tolerated by the SDN applications. To remedy that, we propose an adaptive consistency model for the distributed ONOS controllers following the notion of continuous and compulsory (per-controller) eventual consistency, where network application states adapt their eventual consistency level dynamically at run-time based on the observed state inconsistencies under changing network conditions. When compared to the ONOS approach to static eventual consistency, our approach proved efficient in minimizing state synchronization overheads while taking into account application state consistency SLAs and without compromising the application requirements of high-availability, in the context of large-scale SDN networks