Availability modeling and evaluation of web-based services - A pragmatic approach

Cette thèse porte sur le développement d’une approche de modélisation pragmatique permettant aux concepteurs d’applications et systèmes mis en oeuvre sur le web d’évaluer la disponibilité du service fourni aux utilisateurs. Plusieurs sources d’indisponibilité du service sont prises en compte, en particulier i) les défaillances matérielles ou logicielles affectant les serveurs et ii) des dégradations de performance (surcharge des serveurs, temps de réponse trop long, etc.). Une approche hiérarchique multi-niveau basée sur une modélisation de type performabilité est proposée, combinant des chaînes de Markov et des modèles de files d’attente. Les principaux concepts et la faisabilité de cette approche sont illustrés à travers l’exemple d’une agence de voyage. Plusieurs modèles analytiques et études de sensibilité sont présentés en considérant différentes hypothèses concernant l’architecture, les stratégies de recouvrement, les fautes, les profils d’utilisateurs, et les caractéristiques du trafic. ABSTRACT : This thesis presents a pragmatic modeling approach allowing designers of web-based applications and systems to evaluate the service availability provided to the users. Multiple sources of service unavailability are taken into account, in particular i) hardware and software failures affecting the servers, and ii) performance degradation (overload of servers, very long response time, etc.). An hierarchical multi-level approach is proposed based on performability modeling, combining Markov chains and queueing models. The main concepts and the feasibility of this approach are illustrated using a web-based travel agency. Various analytical models and sensitivity studies are presented considering different assumptions with respect to the architectures, recovery strategies, faults, users profile and traffic characteristics

Cross-Domain AI for Early Attack Detection and Defense Against Malicious Flows in O-RAN

Only the chairs can edit In the fight against cyber attacks, Network Softwarization (NS) is a flexible and adaptable shield, using advanced software to spot malicious activity in regular network traffic. However, the availability of comprehensive datasets for mobile networks, which are fundamental for the development of Machine Learning (ML) solutions for attack detection near their source, is still limited. Cross-Domain Artificial Intelligence (AI) can be the key to address this, although its application in Open Radio Access Network (O-RAN) is still at its infancy. To address these challenges, we deployed an end-to-end O-RAN network, that was used to collect data from the RAN and the transport network. These datasets allow us to combine the knowledge from an in-network ML traffic classifier for attack detection to bolster the training of an ML-based traffic classifier specifically tailored for the RAN. Our results demonstrate the potential of the proposed approach, achieving an accuracy rate of 93%. This approach not only bridges critical gaps in mobile network security but also showcases the potential of cross-domain AI in enhancing the efficacy of network security measures

Optimizing C-RAN Backhaul Topologies: A Resilience-Oriented Approach Using Graph Invariants

ABSTRACT: At the verge of the launch of the first commercial fifth generation (5G) system, trends in wireless and optical networks are proceeding toward increasingly dense deployments, supporting resilient interconnection for applications that carry higher and higher capacity and tighter latency requirements. These developments put increasing pressure on network backhaul and drive the need for a re-examination of traditional backhaul topologies. Challenges of impending networks cannot be tackled by star and ring approaches due to their lack of intrinsic survivability and resilience properties, respectively. In support of this re-examination, we propose a backhaul topology design method that formulates the topology optimization as a graph optimization problem by capturing both the objective and constraints of optimization in graph invariants. Our graph theoretic approach leverages well studied mathematical techniques to provide a more systematic alternative to traditional approaches to backhaul design. Specifically, herein, we optimize over some known graph invariants, such as maximum node degree, topology diameter, average distance, and edge betweenness, as well as over a new invariant called node Wiener impact, to achieve baseline backhaul topologies that match the needs for resilient future wireless and optical networks

Modélisation et évaluation de la disponibilité de services mis en oeuvre sur le web (une approche pragmatique)

Cette thèse porte sur le développement d'une approche de modélisation pragmatique permettant aux concepteurs d'applications et systèmes mis en oeuvre sur le web d'évaluer la disponibilité du service fourni aux utilisateurs. Plusieurs sources d'indisponibilité du service sont prises en compte, en particulier i) les défaillances matérielles ou logicielles affectant les serveurs et ii) des dégradations de performance (surcharge des serveurs, temps de réponse trop long, etc.). Une approche hiérarchique multi-niveau basée sur une modélisation de type performabilité est proposée, combinant des chaînes de Markov et des modèles de files d'attente. Les principaux concepts et la faisabilité de cette approche sont illustrés à travers l'exemple d'une agence de voyage. Plusieurs modèles analytiques et études de sensibilité sont présentés en considérant différentes hypothèses concernant l'architecture, les stratégies de recouvrement, les fautes, les profils d'utilisateurs, et les caractéristiques du trafic.This thesis presents a pragmatic modeling approach allowing designers of web-based applications and systems to evaluate the service availability provided to the users. Multiple sources of service unavailability are taken into account, in particular i) hardware and software failures affecting the servers, and ii) performance degradation (overload of servers, very long response time, etc.). An hierarchical multi-level approach is proposed based on performability modeling, combining Markov chains and queueing models. The main concepts and the feasibility of this approach are illustrated using a web-based travel agency. Various analytical models and sensitivity studies are presented considering different assumptions with respect to the architectures, recovery strategies, faults, users profile and traffic characteristics.TOULOUSE-ENSEEIHT (315552331) / SudocSudocFranceF