Quel système de stockage pour les architectures Fog ?

National audienceDans ce papier, nous nous intéressons au stockage distribué dans un contexte de « Fog Computing ». Nous définissons un ensemble de critères (localité des données, confinement du trafic, fonctionnement en mode déconnecté, mobilité des utilisateurs) que doit satisfaire un système de stockage adapté à ce contexte. Nous vérifions in vivo sur la plateforme Grid'5000 si les deux systèmes de stockage en mode objet Rados et IPFS respectent en particulier le confinement du trafic réseau entre les sites de Fog. Ce critère a un impact majeur sur les performances en écriture et en lecture. Par l'expérience, nous concluons que les deux systèmes comportent des lacunes et nécessitent des améliorations, notamment au niveau de la gestion des métadonnées. La méthode peut être étendue à l'ensemble des critères énoncés ainsi qu'à d'autres solutions logicielles de stockage

A Ring to Rule Them All - Revising OpenStack Internals to Operate Massively Distributed Clouds: The Discovery Initiative - Where Do We Are ?

STACK_HCERES2020The deployment of micro/nano data-centers in network point of presence offers an opportunity to deliver a more sustainable and efficient infrastructure for Cloud Computing. Among the different challenges we need to address to favor the adoption of such a model, the development of a system in charge of turning such a complex and diverse network of resources into a collection of abstracted computing facilities that are convenient to administrate and use is critical.In this report, we introduce the premises of such a system. The novelty of our work is that instead of developing a system from scratch, we revised the OpenStack solution in order to operate such an infrastructure in a distributed manner leveraging P2P mechanisms. More precisely, we describe how we revised the Nova service by leveraging a distributed key/value store instead of the centralized SQL backend. We present experiments that validated the correct behavior of our prototype, while having promising performance using several clusters composed of servers of the Grid’5000 testbed. We believe that such a strategy is promising and paves the way to a first large-scale and WAN-wide IaaS manager.La tendance actuelle pour supporter la demande croissante d'informatique utilitaire consiste à construire des centres de données de plus en plus grands, dans un nombre limité de lieux stratégiques. Cette approche permet sans aucun doute de satisfaire la demande actuelle tout en conservant une approche centralisée de la gestion de ces ressources, mais elle reste loin de pouvoir fournir des infrastructures répondant aux contraintes actuelles et futures en termes d'efficacité, de juridiction ou encore de durabilité. L'objectif de l'initiative DISCOVERY est de concevoir le LUC OS, un système de gestion distribuée des ressources qui permettra de tirer parti de n'importe quel noeud réseau constituant la dorsale d'Internet afin de fournir une nouvelle génération d'informatique utilitaire, plus apte à prendre en compte la dispersion géographiquedes utilisateurs et leur demande toujours croissante.Après avoir rappelé les objectifs de l'initiative DISCOVERY et expliqué pourquoi les approches type fédération ne sont pas adaptées pour opérer une infrastructure d'informatique utilitaire intégrée au réseau, nous présentons les prémisses de notre système. Nous expliquerons notamment pourquoi et comment nous avons choisi de démarrer des travaux visant à revisiter la conception de la solution Openstack. De notre point de vue, choisir d'appuyer nos travaux sur cette solution est une stratégie judicieuse à la vue de la complexité des systèmes de gestion des plateformes IaaS et de la vélocité des solutions open-source

Kinerja Ombudsman Republik Indonesia Perwakilan Provinsi Riau dalam Penanganan Laporan Masyarakat Kota Pekanbaru

The act of maladministration is a behavior that is not in according with the principle of exellent public services that resulted in material or immaterial losses to society. Maladministration is also incompatible with the principles of good governance , clean and efficient . Representatives of Ombudsman of the Republic of Indonesia Riau Province is a representative of the Ombudsman of the Republic of Indonesia in Riau that serves to monitor and prevent acts of maladministration which occurred in the province of Riau . Representatives of Ombudsman of the Republic of Indonesia Riau Province oversee implementation of public service with follow up reports / complaints from the community to produce a decision in the form of recommendations and suggestions . The purpose of this study was to analyze the performance and also the factors that influence the performance of the Ombudsman of the Republic of Indonesia Representative Riau Province in Handling Reports Pekanbaru city community .The concept of theory that researchers use is performance. By looking at the responsiveness , responsibility and accountability of the Ombudsman Representative Riau Province . This study uses qualitative research methods with an assessment of descriptive data . In collecting the data , researchers use interviewing techniques , observation , documentation and literature. By using key informants as a source of information and triangulation techniques as a source of data authenticity .After doing research, it was found that the performance of the Ombudsman of the Republic of Indonesia Representative Riau Province in the handling of public reports Pekanbaru city has been running well , but still not optimal due to the completion of reports requires a procedure that is quite complex and is still the lack of public knowledge of Pekanbaru on the existence of the Ombudsman as well as the functions and tasks

Saline: Improving Best-Effort Job Management in Grids

Although virtualization technologies have recently gained a lot of interest in Grid computing as they allow flexible resource management, the most common way to exploit grids still relies on dedicated services like resource management systems (RMSs) to get resources at a particular time. To improve resource usage, most of these systems provide a best-effort mode where lowest priority jobs can be executed when resources are idle. This particular mode does not provide any guarantee of service and jobs may be killed at any time by the RMS when the nodes they use are subject to higher priority reservations. This behaviour potentially leads to a huge waste of computation time or at least requires users to deal with checkpoints of their best-effort jobs. In this paper, we present Saline, a generic and non-intrusive framework to manage best-effort jobs at grid level through virtual machines (VMs) usage. We discuss the main challenges concerning the design of such a grid system, focusing on VM snapshot management and network configuration. Results of preliminary experiments show the interest of our proposal to ensure an efficient execution of best-effort jobs through the whole grid

Flauncher and DVMS -- Deploying and Scheduling Thousands of Virtual Machines on Hundreds of Nodes Distributed Geographically

International audienceAlthough live migration of virtual machines has been an active area of research over the past decade, it has been mainly evaluated by means of simulations and small scale deployments. Proving the relevance of live migration at larger scales is a technical challenge that requires to be able to deploy and schedule virtual machines. In the last year, we succeeded to tackle such a challenge by conducting experiments with Flauncher and DVMS, two frameworks that can respectively deploy and schedule thousands of virtual machines over hundreds of nodes distributed geographically across the Grid'5000 testbed

Changement de contexte pour tâches virtualisées à l'échelle des grappes

National audienceDe nos jours, la gestion des ressources d'une grappe est effectuée en allouant des tranches de temps aux applications, spécifiées par les utilisateurs et de manière statique. Pour un utilisateur, soit les ressources demandées sont sur-estimées et la grappe est sous-utilisée, soit sous-dimensionnées et ses calculs sont dans la plupart des cas perdus. L'apparition de la virtualisation a apporté une certaine flexibilité quant à la gestion des applications et des ressources des grappes. Cependant, pour optimiser l'utilisation de ces ressource, et libérer les utilisateurs d'estimations hasardeuses, il devient nécessaire d'allouer dynamiquement les ressources en fonction des besoins réels des applications : Être capable de démarrer dynamiquement une application lorsqu'une ressource se libère ou la suspendre lorsque la ressource doit être ré-attribuée. En d'autres termes, être capable de développer un système comparable au changement de contexte sur les ordinateurs standards pour les applications s'exécutant sur une grappe. En s'appuyant sur la virtualisation, développer un tel mécanisme de manière générique devient envisageable. Dans cet article nous proposons une infrastructure offrant la notion de changement de contexte d'applications virtualisées appliquée aux grappes. Cette solution a permis de développer un ordonnanceur exécutant simultanément un maximum d'applications virtualisées. Nous montrons qu'une telle solution augmente le taux d'occupation de notre grappe et réduit le temps de traitement des applications

Cluster-Wide Context Switch of Virtualized Jobs

International audienceClusters are mostly used through Resources Management Systems (RMS) with a static allocation of resources for a bounded amount of time. Those approaches are known to be insufficient for an efficient use of clusters. To provide a finer RMS, job preemption, migration and dynamic allocation of resources are required. However due to the complexity of developing and using such mechanisms, advanced scheduling strategies have rarely been deployed. This trend is currently evolving thanks to the use of migration and preemption capabilities of Virtual Machines (VMs). However, although the manipulation of jobs composed of VM enables to change the state of the jobs according to the scheduling objective, changing the state and the location of numerous VMs at each decision is tedious and degrades the overall performance. In addition to the scheduling policy implementation, developers have to focus on the feasibility of the actions while executing them in the most efficient way. In this paper, we argue such an operation is independent from the policy itself and can be addressed through a generic mechanism, the cluster-wide context switch. Thanks to it, developers can implement sophisticated algorithms to schedule jobs without handling the issues related to their manipulations. They only focus on the implementation of their algorithm to select the jobs to run while the cluster-wide context switch system performs the necessary actions to switch from the current to the new situation. As a proof of concept, we evaluate the interest of the cluster-wide context switch through a sample scheduler that executes jobs as early as possible, even partially, regarding to their current resources requirements and their priority

SimGrid VM: Virtual Machine Support for a Simulation Framework of Distributed Systems

International audienceAs real systems become larger and more complex, the use of simulator frameworks grows in our research community. By leveraging them, users can focus on the major aspects of their algorithm, run in-siclo experiments (i.e., simulations), and thoroughly analyze results, even for a large-scale environment without facing the complexity of conducting in-vivo studies (i.e., on real testbeds). Since nowadays the virtual machine (VM) technology has become a fundamental building block of distributed computing environments, in particular in cloud infrastructures, our community needs a full-fledged simulation framework that enables us to investigate large-scale virtualized environments through accurate simulations. To be adopted, such a framework should provide easy-to-use APIs as well as accurate simulation results. In this paper, we present a highly-scalable and versatile simulation framework supporting VM environments. By leveraging SimGrid, a widely-used open-source simulation toolkit, our simulation framework allows users to launch hundreds of thousands of VMs on their simulation programs and control VMs in the same manner as in the real world (e.g., suspend/resume and migrate). Users can execute computation and communication tasks on physical machines (PMs) and VMs through the same SimGrid API, which will provide a seamless migration path to IaaS simulations for hundreds of SimGrid users. Moreover, SimGrid VM includes a live migration model implementing the precopy migration algorithm. This model correctly calculates the migration time as well as the migration traffic, taking account of resource contention caused by other computations and data exchanges within the whole system. This allows user to obtain accurate results of dynamic virtualized systems. We confirmed accuracy of both the VM and the live migration models by conducting several micro-benchmarks under various conditions. Finally, we conclude the article by presenting a first use-case of one consolidation algorithm dealing with a significant number of VMs/PMs. In addition to confirming the accuracy and scalability of our framework, this first scenario illustrates the main interest of SimGrid VM: investigating through in-siclo experiments pros/cons of new algorithms in order to limit expensive in-vivo experiments only to the most promising ones

Changement de contexte pour tâches virtualisées à l'échelle des grappes

National audienceDe nos jours, la gestion des ressources d'une grappe est effectuée en allouant des tranches de temps aux applications, spécifiées par les utilisateurs et de manière statique. Pour un utilisateur, soit les ressources demandées sont sur-estimées et la grappe est sous-utilisée, soit sous-dimensionnées et ses calculs sont dans la plupart des cas perdus. L'apparition de la virtualisation a apporté une certaine flexibilité quant à la gestion des applications et des ressources des grappes. Cependant, pour optimiser l'utilisation de ces ressource, et libérer les utilisateurs d'estimations hasardeuses, il devient nécessaire d'allouer dynamiquement les ressources en fonction des besoins réels des applications : Être capable de démarrer dynamiquement une application lorsqu'une ressource se libère ou la suspendre lorsque la ressource doit être ré-attribuée. En d'autres termes, être capable de développer un système comparable au changement de contexte sur les ordinateurs standards pour les applications s'exécutant sur une grappe. En s'appuyant sur la virtualisation, développer un tel mécanisme de manière générique devient envisageable. Dans cet article nous proposons une infrastructure offrant la notion de changement de contexte d'applications virtualisées appliquée aux grappes. Cette solution a permis de développer un ordonnanceur exécutant simultanément un maximum d'applications virtualisées. Nous montrons qu'une telle solution augmente le taux d'occupation de notre grappe et réduit le temps de traitement des applications

Adding Storage Simulation Capacities to the SimGrid Toolkit: Concepts, Models, and API

International audienceFor each kind of distributed computing infrastructures, i.e., clusters, grids, clouds, data centers, or supercomputers, storage is a essential component to cope with the tremendous increase in scientific data production and the ever-growing need for data analysis and preservation. Understanding the performance of a storage subsystem or dimensioning it properly is an important concern for which simulation can help by allowing for fast, fully repeatable, and configurable experiments for arbitrary hypothetical scenarios. However, most simulation frameworks tailored for the study of distributed systems offer no or little abstractions or models of storage resources.In this paper, we detail the extension of SimGrid, a versatile toolkit for the simulation of large-scale distributed computing systems, with storage simulation capacities. We first define the required abstractions and propose a new API to handle storage components and their contents in SimGrid-based simulators. Then we characterize the performance of the fundamental storage component that are disks and derive models of these resources. Finally we list several concrete use cases of storage simulations in clusters, grids, clouds, and data centers for which the proposed extension would be beneficial