Littérature scientifique sur le sujet « Machine virtuelle (VM) »
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Thèses sur le sujet "Machine virtuelle (VM)"
Kugel, Rudolf. « Ein Beitrag zur Problematik der Integration virtueller Maschinen ». Phd thesis, [S.l.] : [s.n.], 2005. http://deposit.ddb.de/cgi-bin/dokserv?idn=980016371.
Texte intégralDucasse, Quentin. « Sécurisation matérielle de la compilation à la volée des machines virtuelles langage ». Electronic Thesis or Diss., Brest, École nationale supérieure de techniques avancées Bretagne, 2024. https://theses.hal.science/tel-04690882.
Texte intégralLanguage Virtual Machines (VMs) are the run-time environment of popular high level managed languages. They offer portability and memory handling for the developer and are deployed on most computing devices. Their widespread distribution, handling of untrusted user inputs, and low-level task execution make them interesting to attackers. Software-only solutions that isolate their different components often incur a high performance overhead incompatible with just-in-time (JIT) compilation. Hardware-accelerated run time protections are pushed in vendor processors as a solution to conciliate strong security guarantees with performance. To allow experimentation in the design and comparison of such solutions, this thesis is interested in the RISC-V instruction set and its extension capabilities. We present Gigue, a workload generator that outputs binaries similar to JIT code directly executable on RISC-V softcores. It provides an interface for custom instructions and guarantees their execution. We present an instruction-level domain isolation solution added to Gigue binaries and implemented in an application-class processor with processor modifications. The solution adds negligible performance overhead while enforcing strong properties on domains. As an effort to motivate deployment in real use cases, we extend the Pharo JIT compiler to the RISC-V instruction set along with its testing infrastructure
Chouichi, Aabir. « Real-time detection and control of machine/chamber mismatching in the semi- conductor industry ». Thesis, Lyon, 2020. http://www.theses.fr/2020LYSEM001.
Texte intégralIn the manufacturing industries, the machines/chambers placed in parallel on the same production operation are expected to have similar capabilities and, most importantly, to yield identical product quality. However, this is usually not the case in real practice due to the systematic variations accumulated in time. Maintaining stable performance of parallel machines/chambers in the semiconductor industry is a critical challenge given the fact that, in the large-scale production environment, machines/chambers can process a large number of products simultaneously to maximize throughput and optimize machine utilization. Un- surprisingly, after processing very different settings, called recipes, the conditions of parallel machines/chambers will be no longer the same. This thesis proposes a methodology to detect and correct the performance differences in real-time by using all the available data, namely: measurements of physical parameters, data from sensors installed on machines, data from the control loops, and maintenance data. The core idea is to integrate the different sources of data, which are usually used separately, to identify the root causes of any significant differences among the machines/chambers that process identical recipes.The proposed approach starts by detecting existing gaps between parallel machines/ chambers by referring to the measurements of physical parameters since they reflect the quality of manufactured products. The sensor data are then analyzed to highlight the in- dicators that cause these discrepancies. These indicators are adjusted through an effective control mechanism composed of two parts: 1) virtual metrology and 2) process regulation. First, the impact of recipe changes on product quality is quantified by modeling the link between the inputs and outputs of the mismatched machines/chambers. The constructed models are then used to implement the revised control loops to match as much as possible the controllable input factors and compensate for the output errors
Ouarnoughi, Hamza. « Placement autonomique de machines virtuelles sur un système de stockage hybride dans un cloud IaaS ». Thesis, Brest, 2017. http://www.theses.fr/2017BRES0055/document.
Texte intégralIaaS 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 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 MAPEK (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
Albaaj, Hassan, et Victor Berggren. « Benchmark av Containers och Unikernels ». Thesis, Tekniska Högskolan, Jönköping University, JTH, Datateknik och informatik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-50214.
Texte intégralSyfte – Syftet med denna studie är att undersöka möjligheten att effektivisera lokala nätverk och databaser med hjälp av unikernels och att jämföra denna möjlighet med containrar. Detta kan även gälla utveckling av programvara för att säkerställa att programvaran exekveras på servern på exakt samma sätt som den tidigare gjort lokalt på utvecklarens lokala dator. Metod – Två experiment utförs för att undersöka om det går besvara syftet, kvantitativa data samlas in i båda fallen, datan är även redovisad kvantitativt. Python-script används föratt starta C-script som agerar klient och server. Tidtagning på algoritmer i unikernels respektive containrar samt minnesanvändning vid multipel instansiering mättes för att analyseras och jämföras. Resultat – Intermittenta svarstids-toppar gjorde datan från unikernels svår att korrekt utvärdera. Containrar hade ett lägre medelvärde på svarstider vid mindre krävande algoritm-användning. Unikernels medelvärde dyker under container-svarstiderna när mer krävande program simuleras. Några små buggar upptäcktesi Unikraft unikernels. Implikationer – Unikernels har egenskaper som gör de mer passande för vissa uppgifter jämfört med dess motsvarighet medan detsamma gäller för Containrar. Unikraft unikernels är instabila och ger därfören bild av att containrar vidmindre processorkrävande program faktiskt är snabbare än unikernels. Unikernels är bara snabbare och säkrare i den mån verktyget som bygger dem, gör det på ett sätt att de är stabila. Begränsningar – Avsaknaden av standarder, avsaknaden av ett communitysom kan svara på frågor tillsammans med att unikernelsär ett litet och nischat fält gör att unikernels har en relativ hög inlärningskurva. Nyckelord – Unikernel, Unikraft, Container, Docker
Ahvar, Ehsan. « Cost-efficient resource allocation for green distributed clouds ». Thesis, Evry, Institut national des télécommunications, 2017. http://www.theses.fr/2017TELE0001.
Texte intégralVirtual machine (VM) placement (i.e., resource allocation) method has a direct effect on both cost and carbon emission. Considering the geographic distribution of data centers (DCs), there are a variety of resources, energy prices and carbon emission rates to consider in a distributed cloud, which makes the placement of VMs for cost and carbon efficiency even more critical and complex than in centralized clouds. The goal of this thesis is to present new VM placement algorithms to optimize cost and carbon emission in a distributed cloud. It first focuses on cost efficiency in distributed clouds and, then, extends the goal to optimization of both cost and carbon emission at the same time. Thesis includes two main parts. The first part of thesis proposes, develops and evaluates static VM placement algorithms to reach the mentioned goal where an initial placement of a VM holds throughout the lifetime of the VM. The second part proposes dynamic VM placement algorithms where the initial placement of VMs is allowed to change (e.g., through VM migration and consolidation). The first contribution is a survey of the state of the art on cost and carbon emission resource allocation in distributed cloud environments. The second contribution targets the challenge of optimizing inter-DC communication cost for large-scale tasks and proposes a Network-Aware Cost-Efficient Resource allocation method, called NACER, for distributed clouds. The goal is to minimize the network communication cost of running a task in a distributed cloud by selecting the DCs to provision the VMs in such a way that the total network distance (hop count or any reasonable measure) among the selected DCs is minimized. The third contribution proposes a Network-Aware Cost Efficient VM Placement method (called NACEV) for Distributed Clouds. NACEV is an extended version of NACER. While NACER only considers inter-DC communication cost, NACEV optimizes both communication and computing cost at the same time and also proposes a mapping algorithm to place VMs on Physical Machines (PMs) inside of the selected DCs. NACEV also considers some aspects such as heterogeneity of VMs, PMs and switches, variety of energy prices, multiple paths between PMs, effects of workload on cost (energy consumption) of cloud devices (i.e., switches and PMs) and also heterogeneity of energy model of cloud elements. The forth contribution presents a Cost and Carbon Emission-Efficient VM Placement Method (called CACEV) for green distributed clouds. CACEV is an extended version of NACEV. In addition to cost efficiency, CACEV considers carbon emission efficiency and green distributed clouds. It is a VM placement algorithm for joint optimization of computing and network resources, which also considers price, location and carbon emission rate of resources. It also, unlike previous contributions of thesis, considers IaaS Service Level Agreement (SLA) violation in the system model. To get a better performance, the fifth contribution proposes a dynamic Cost and Carbon Emission-Efficient VM Placement method (D-CACEV) for green distributed clouds. D-CACEV is an extended version of our previous work, CACEV, with additional figures, description and also live VM migration mechanisms. We show that our joint VM placement-reallocation mechanism can constantly optimize both cost and carbon emission at the same time in a distributed cloud
Ahvar, Ehsan. « Cost-efficient resource allocation for green distributed clouds ». Electronic Thesis or Diss., Evry, Institut national des télécommunications, 2017. http://www.theses.fr/2017TELE0001.
Texte intégralVirtual machine (VM) placement (i.e., resource allocation) method has a direct effect on both cost and carbon emission. Considering the geographic distribution of data centers (DCs), there are a variety of resources, energy prices and carbon emission rates to consider in a distributed cloud, which makes the placement of VMs for cost and carbon efficiency even more critical and complex than in centralized clouds. The goal of this thesis is to present new VM placement algorithms to optimize cost and carbon emission in a distributed cloud. It first focuses on cost efficiency in distributed clouds and, then, extends the goal to optimization of both cost and carbon emission at the same time. Thesis includes two main parts. The first part of thesis proposes, develops and evaluates static VM placement algorithms to reach the mentioned goal where an initial placement of a VM holds throughout the lifetime of the VM. The second part proposes dynamic VM placement algorithms where the initial placement of VMs is allowed to change (e.g., through VM migration and consolidation). The first contribution is a survey of the state of the art on cost and carbon emission resource allocation in distributed cloud environments. The second contribution targets the challenge of optimizing inter-DC communication cost for large-scale tasks and proposes a Network-Aware Cost-Efficient Resource allocation method, called NACER, for distributed clouds. The goal is to minimize the network communication cost of running a task in a distributed cloud by selecting the DCs to provision the VMs in such a way that the total network distance (hop count or any reasonable measure) among the selected DCs is minimized. The third contribution proposes a Network-Aware Cost Efficient VM Placement method (called NACEV) for Distributed Clouds. NACEV is an extended version of NACER. While NACER only considers inter-DC communication cost, NACEV optimizes both communication and computing cost at the same time and also proposes a mapping algorithm to place VMs on Physical Machines (PMs) inside of the selected DCs. NACEV also considers some aspects such as heterogeneity of VMs, PMs and switches, variety of energy prices, multiple paths between PMs, effects of workload on cost (energy consumption) of cloud devices (i.e., switches and PMs) and also heterogeneity of energy model of cloud elements. The forth contribution presents a Cost and Carbon Emission-Efficient VM Placement Method (called CACEV) for green distributed clouds. CACEV is an extended version of NACEV. In addition to cost efficiency, CACEV considers carbon emission efficiency and green distributed clouds. It is a VM placement algorithm for joint optimization of computing and network resources, which also considers price, location and carbon emission rate of resources. It also, unlike previous contributions of thesis, considers IaaS Service Level Agreement (SLA) violation in the system model. To get a better performance, the fifth contribution proposes a dynamic Cost and Carbon Emission-Efficient VM Placement method (D-CACEV) for green distributed clouds. D-CACEV is an extended version of our previous work, CACEV, with additional figures, description and also live VM migration mechanisms. We show that our joint VM placement-reallocation mechanism can constantly optimize both cost and carbon emission at the same time in a distributed cloud
Saleil, Baptiste. « Simple optimizing JIT compilation of higher-order dynamic programming languages ». Thèse, 2019. http://hdl.handle.net/1866/22661.
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