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Microsoft Windows Update est un service de mises à jour permettant d'obtenir des correctifs de sécurité, des améliorations ou encore de nouvelles fonctionnalités pour Windows. En 2005 sera créé Microsoft Update, incluant également des mises à jour pour Microsoft Office, Microsoft SQL Server et d'autres logiciels Microsoft. Microsoft Windows Update Microsoft Windows Update est un site Web permettant d'obtenir des mises à jour pour Windows. Apparu avec Windows 98, il est accessible via Microsoft Internet Explorer (4.0 à 8). Des contrôles ActiveX sont nécessaires pour utiliser le site. Microsoft Windows Update est un composant du menu Démarrer de Windows 98 jusqu'à Windows 7. À partir de Windows Vista, le service est intégré au Panneau de Configuration et ne se comporte plus comme un site Web. Sous Windows 8 et 10, il fait aussi partie intégrante de Windows, mais cette fois des Paramètres. En 2006 apparaît Microsoft Update, un service comme Microsoft Windows Update, avec, en p

Decomposition Strategies for Nonconvex Problems, a Parametric Approach

Jean-Hubert Hours

This thesis deals with the development of numerical methods for solving nonconvex optimisation problems by means of decomposition and continuation techniques. We first introduce a novel decomposition algorithm based on alternating gradient projections and augmented Lagrangian relaxations. A proof of local convergence is given under standard assumptions. The effect of different stopping criteria on the convergence of the augmented Lagrangian loop is investigated. As a second step, a trust region algorithm for distributed nonlinear programs, named TRAP, is introduced. Its salient ingredient is an alternating gradient projection for computing a set of active constraints in a distributed manner, which is a novelty for trust region techniques. Global convergence as well as local almost superlinear convergence are proven. The numerical performance of the algorithm is assessed on nonconvex optimal power flow problems. The core of this thesis is the development and analysis of an augmented Lagrangian algorithm for tracking parameter-dependent optima. Despite their interesting features for large-scale and distributed optimisation, augmented Lagrangian methods have not been designed and fully analysed in a parametric setting. Therefore, we propose a novel optimality-tracking scheme that consists of fixed number of descent steps computed on an augmented Lagrangian subproblem and one dual update per parameter change. It is shown that the descent steps can be performed by means of first-order as well as trust region methods. Using the Kurdyka-Lojasiewicz property, an analysis of the local convergence rate of a class of trust region Newton methods is provided without relying on the finite detection of an optimal active set. This allows us to establish a contraction inequality for the parametric augmented Lagrangian algorithm. Hence, stability of the continuation scheme can be proven under mild assumptions. The effect of the number of primal iterations and the penalty is analysed by means of numerical examples. Finally, the efficacy of the augmented Lagrangian continuation scheme is successfully demonstrated on three examples in the field of optimal control. The first two examples consists of a real-time NMPC algorithm based on a multiple-shooting discretisation. In particular, it is shown that our C++ software package is competitive with the state-of-the-art codes on NMPC problems with long prediction horizons, and can address a more general class of real-time NMPC problems. The third case study is the distributed computation of solutions to multi-stage nonconvex optimal power flow problems in a real-time setting.

EPFL2016

Automating Live Update for Generic Server Programs

Calin Iorgulescu

The pressing demand to deploy software updates without stopping running programs has fostered much research on live update systems in the past decades. Prior solutions, however, either make strong assumptions on the nature of the update or require extensive and error-prone manual effort, factors which discourage the adoption of live update. This paper presents Mutable Checkpoint-Restart ( MCR), a new live update solution for generic ( multiprocess and multithreaded) server programs written in C. Compared to prior solutions, MCR can support arbitrary software updates and automate most of the common live update operations. The key idea is to allow the running version to safely reach a quiescent state and then allow the new version to restart as similarly to a fresh program initialization as possible, relying on existing code paths to automatically restore the old program threads and reinitialize a relevant portion of the program data structures. To transfer the remaining data structures, MCR relies on a combination of precise and conservative garbage collection techniques to trace all the global pointers and apply the required state transformations on the fly. Experimental results on popular server programs ( Apache httpd, nginx, OpenSSH and vsftpd) confirm that our techniques can effectively automate problems previously deemed difficult at the cost of negligible performance overhead ( 2 percent on average) and moderate memory overhead ( 3.9 x on average, without optimizations).

Ieee Computer Soc2016

Mutable Checkpoint-Restart: Automating Live Update for Generic Server Programs

Calin Iorgulescu

The pressing demand to deploy software updates without stopping running programs has fostered much research on live update systems in the past decades. Prior solutions, however, either make strong assumptions on the nature of the update or require extensive and error-prone manual effort, factors which discourage live update adoption. This paper presents Mutable Checkpoint-Restart (MCR), a new live update solution for generic (multiprocess and multithreaded) server programs written in C. Compared to prior solutions, MCR can support arbitrary software updates and automate most of the common live update operations. The key idea is to allow the new version to restart as similarly to a fresh program initialization as possible, relying on existing code paths to automatically restore the old program threads and reinitialize a relevant portion of the program data structures. To transfer the remaining data structures, MCR relies on a combination of precise and conservative garbage collection techniques to trace all the global pointers and apply the required state transformations on the fly. Experimental results on popular server programs (Apache httpd, nginx, OpenSSH and vsftpd) confirm that our techniques can effectively automate problems previously deemed difficult at the cost of negligible run-time performance overhead (2% on average) and moderate memory overhead (3.9x on average).

ACM New York2014

Decomposition Strategies for Nonconvex Problems, a Parametric Approach

Jean-Hubert Hours

EPFL2016