Relevant bibliographies by topics / Virtualized Data Center

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Virtualized Data Center'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 May 2024

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Journal articles on the topic "Virtualized Data Center"

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Karamat Khan, Tehmina, Mohsin Tanveer, and Asadullah Shah. "Energy Efficiency in Virtualized Data Center." International Journal of Engineering & Technology 7, no. 4.15 (October 7, 2018): 315. http://dx.doi.org/10.14419/ijet.v7i4.15.23019.

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Industrial and academic communities have been trying to get more computational power out of their investments. Data centers have recently received huge attention due to its increased business value and achievable scalability on public/private clouds. Infra-structure and applications of modern data center is being virtualized to achieve energy efficient operation on servers. Despite of data center advantages on performance, there is a tradeoff between power and performance especially with cloud data centers. Today, these cloud application-based organizations are facing many energy related challenges. In this paper, through survey it has been analyzed how virtualization and networking related challenges affects energy efficiency of data center with suggested optimization strategies.
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Erickson, David, Brandon Heller, Shuang Yang, Jonathan Chu, Jonathan Ellithorpe, Scott Whyte, Stephen Stuart, Nick McKeown, Guru Parulkar, and Mendel Rosenblum. "Optimizing a virtualized data center." ACM SIGCOMM Computer Communication Review 41, no. 4 (October 22, 2011): 478–79. http://dx.doi.org/10.1145/2043164.2018530.

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Tan, Xiao Long, Wen Bin Wang, and Yu Qin Yao. "Research of Network Virtualization in Data Center." Applied Mechanics and Materials 644-650 (September 2014): 2961–64. http://dx.doi.org/10.4028/www.scientific.net/amm.644-650.2961.

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With the rapid grow of the volume of data and internet application, as an efficient and promising infrastructure, data center has been widely deployed .data center provide a variety of perform for network services, applications such as video stream, cloud compute and so on. All this services and applications call for volume, compute, bandwidth, and latency. Existing data centers lacks enough flexible so they provide poor support in QOS, deployability, manageability, and defense when facing attacks. Virtualized data centers are a good solution to these problems. Compared to existing data centers, virtualized data centers do better in resource utilization, scalability, and flexibility.
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Kanniga Devi R., Murugaboopathi Gurusamy, and Vijayakumar P. "An Efficient Cloud Data Center Allocation to the Source of Requests." Journal of Organizational and End User Computing 32, no. 3 (July 2020): 23–36. http://dx.doi.org/10.4018/joeuc.2020070103.

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A Cloud data center is a network of virtualized resources, namely virtualized servers. They provision on-demand services to the source of requests ranging from virtual machines to virtualized storage and virtualized networks. The cloud data center service requests can come from different sources across the world. It is desirable for enhancing Quality of Service (QoS), which is otherwise known as a service level agreement (SLA), an agreement between cloud service requester and cloud service consumer on QoS, to allocate the cloud data center closest to the source of requests. This article models a Cloud data center network as a graph and proposes an algorithm, modified Breadth First Search where the source of requests assigned to the Cloud data centers based on a cost threshold, which limits the distance between them. Limiting the distance between Cloud data centers and the source of requests leads to faster service provisioning. The proposed algorithm is tested for various graph instances and is compared with modified Voronoi and modified graph-based K-Means algorithms that they assign source of requests to the cloud data centers without limiting the distance between them. The proposed algorithm outperforms two other algorithms in terms of average time taken to allocate the cloud data center to the source of requests, average cost and load distribution.
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Tan, Tingxi, Rob Simmonds, Bradley Arlt, Martin Arlitt, and Bruce Walker. "Image management in a virtualized data center." ACM SIGMETRICS Performance Evaluation Review 36, no. 2 (August 31, 2008): 4–9. http://dx.doi.org/10.1145/1453175.1453177.

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Hanane Aznaoui and Canan Batur Şahin. "A Virtual Data Center Comparison Of Different Firewalls' Performance." Journal of Advancement in Computing 1, no. 1 (April 18, 2023): 1–8. http://dx.doi.org/10.36755/jac.v1i1.46.

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Whether virtual or real, every data centre depends on its network, and the firewall is a crucial component of that network for secure communication. Different types of firewalls, such as software firewalls, physical firewalls, virtual appliance firewalls, and kernel-integrated firewalls, can secure data centre connections. When choosing a firewall, there are many things to take into account, especially in a virtualized data centre where each firewall behaves differently depending on the situation. Reduced costs, effective administration extensibility, greater resource usage, scalability, and energy resilience are just a few benefits that virtualized data centres are supposed to produce. In this study, the use of firewalls is examined in relation to virtualized data centres. The effectiveness of several kinds of firewalls, including virtual firewalls, physical firewalls, and software .The performance of various types of firewalls, such as software firewalls, physical firewalls, virtual appliance firewalls, and kernel-integrated firewalls, is being analysed. Virtual data centre firewall implementation and performance comparisons explain how to design and which firewall type provides the best performance. In all conditions, it was shown that kernel-integrated firewalls worked properly. Virtual machine IP addresses and networks can vary, and the kernel-based firewall can dynamically update its rules to keep pace with such changes.
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Nine, Md S. Q. Zulkar, Abul Kalam Azad, Saad Abdullah, and Rashedur M. Rahman. "Fuzzy Dynamic Load Balancing in Virtualized Data Centers of SaaS Cloud Provider." International Journal of Fuzzy System Applications 4, no. 3 (July 2015): 50–71. http://dx.doi.org/10.4018/ijfsa.2015070104.

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Cloud computing provides a robust infrastructure that can facilitate computing power as a utility service. All the virtualized services are made available to end users in a pay-as-you-go basis. Serving user requests using distributed network of Virtualized Data Centers is a challenging task as response time increases significantly without a proper load balancing strategy. As the parameters involved in generating load in the Virtualized Data Center has imprecise effect on the overall load of Virtual Machine, a fuzzy load balancing strategy is required. This paper proposes two efficient fuzzy load balancing methods - Fuzzy Active Monitoring Load Balancer (FAM-LB) and Fuzzy Throttled Load Balancer (FT-LB) for the distributed SaaS cloud provider. The authors implemented a cloud model in simulation environment and compared the results of otheir novel approach with the existing techniques. Among them FT-LB has provided better performance compared to other scheduling algorithms.
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Sinha, RIshabh. "Understanding In-Depth About Data Centre Security: Core Concepts & Market Growth." International Journal for Research in Applied Science and Engineering Technology 10, no. 5 (May 31, 2022): 623–26. http://dx.doi.org/10.22214/ijraset.2022.42265.

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Abstract: Enterprises often perceive Data Centers as a key resource and demand dedicated security initiatives. Further, the emergence of security of the Data Center is playing a critical role in security-critical applications and data in a virtualized environment through optimal safeguarding. The providers of the Data Center have increased their focus. They have shown their participation in the market by enhancing products to augment the increasing demand for Data Center security solutions to address the rising needs of growing industries. This paper discusses various concepts of Data Center security along with its projected market growth on a global level. Keywords: Data Centers, Data Center Security, Data Center Security Importance, Data Center Security Market Growth, Data Center Security Practices
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Assaf, Eshrak, Amr Badr, and Ibrahim Farag. "Application of Computational Intelligence to Virtualized Data Center Management." International Journal of Computer Applications 55, no. 10 (October 20, 2012): 42–49. http://dx.doi.org/10.5120/8793-2780.

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Islam, Mohammad A., Shaolei Ren, Niki Pissinou, A. Hasan Mahmud, and Athanasios V. Vasilakos. "Distributed temperature-aware resource management in virtualized data center." Sustainable Computing: Informatics and Systems 6 (June 2015): 3–16. http://dx.doi.org/10.1016/j.suscom.2014.03.002.

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Dissertations / Theses on the topic "Virtualized Data Center"

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Tayachi, Zeineb. "Sûreté de fonctionnement et provisionnement éco-énergétique dans les centres de données virtualisés IaaS." Electronic Thesis or Diss., Paris, CNAM, 2021. http://www.theses.fr/2021CNAM1292.

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Le Cloud computing offre aux utilisateurs l’opportunité d’exploiter des services qui peuvent être des infrastructures, des plateformes, des applications,... Ceci représente un gain de temps et d’argent considérable puisque l’utilisateur n’a besoin ni d’investir dans une infrastructure onéreuse, ni de gérer sa maintenance, de plus il paye juste les ressources utilisées. Afin de prendre en charge des applications à grande échelle et stocker de gros volumes de données, les centres de données ont été largement déployés par des fournisseurs cloud. Cependant, les études ont montré une mauvaise utilisation des ressources qui ne sont pas exploitées pleinement. Les technologies de virtualisation ont permis d’améliorer la situation en déployant des centres de données virtualisés. Ces derniers sont des centres de données où tout ou une partie du matériel (par exemple, serveurs, routeurs, commutateurs et liens) est virtualisé à l’aide d’un logiciel appelé hyperviseur qui divise l’équipement en plusieurs instances virtuelles isolées et indépendantes (comme des machines virtuelles). Toutefois les performances des équipements peuvent être atténuées à cause de plusieurs phénomènes tels que le vieillissement logiciel. L’objectif de cette thèse est d’évaluer les performances de deux composants clés dans les centres de données qui sont le serveur virtualisé et le commutateur virtuel. Puisque, l’architecture de ces systèmes est complexe, on a opté pour utiliser les formalismes de modélisation avant de mettre en place des solutions pratiques. Notre première contribution concerne la modélisation et l’évaluation de la performabilité d’un serveur virtualisé qui implémente une politique de gestion de l’énergie et utilise le rajeunissement logiciel comme une technique proactive afin de prévenir les aléas de vieillissement logiciel. Cette modélisation est basée sur une approche modulaire utilisant le SRN (Stochastic Reward Nets) qui décrit les différents états du SVS ainsi que les transitions régissant le passage d’un état à l’autre. L’analyse numérique permet de capturer l’impact de la variation de la charge de travail et le trafic en rafale sur les métriques de performabilité, ce qui permet de bien définir les paramètres du système. La seconde contribution porte sur l’évaluation des performances d’un commutateur virtuel qui détermine les performances du réseau puisqu’il établit la communication entre des VMs. Le modèle analytique proposé représente l’architecture interne de cenoeud critique avec plusieurs cartes d’interface réseau (représentant des ports) et plusieurs cœurs de processeur (CPU). Chaque CPU sert un ensemble de ports. Le modèle est basé sur les files d’attente avec serveur en vacance et des arrivées groupées. Les résultats numériques montrent l’impact de la taille du groupe et la politique d’acceptation sur les performances du commutateur. Ces résultats peuvent être intéressants lors du dimensionnement des ressources d’un commutateur virtuel
Cloud computing allows users to exploit services such as infrastructures, platforms, applications, ...This allows a considerable cost and time saving since users do not need buying and managing of equipment. Moreover, they just pay the resources used (pay-as-you go). With the increasing large-scale applications and the need to store huge quantities of data, data centers have been widely deployed. However, studies have shown the under utilization of resources. Therefore, Cloud providers resort to virtualization technologies that are adopted by data center architectures and virtualized data centres have been deployed. A Virtualized Data Center is a data center where some or all of the hardware (e.g, servers, routers, switches, and links) are virtualized by using software called hypervisor that divides the equipment into multiple isolated and independent virtual instances (e.g virtual machines (VMs)). However, equipment performance can be mitigated due to several phenomena such as software aging. In this thesis, we focus on performance evaluation of two components in the data centers which are the virtualized server and the virtual switch, by usingmodeling formalisms. The first contribution concerns performability modeling and analysis of server virtualized systems subject to software aging, software rejuvenation and implements an energy management policy. A modular approach based on SRNs is proposed to investigate dependencies between several server virtualized modules. Numerical analysis shows how workload with bursty nature impacts performability metrics. This can handle decision making related to rejuvenation scheduling algorithms and to select the suitable rejuvenation mechanism. The second contribution concerns virtual switch (VS) which is considered as key element in data center networks since it achieves the communication between virtual machines. An analytical queueing model with batch arrivals and server vacations is proposed to evaluate VS performance with several network interface cards and several CPU cores. Performance metrics are obtained as a function of two proposed batch acceptance strategies and mean batch size. Numerical results aremeaningful when sizing virtual switch resources
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Goiri, Íñigo. "Multifaceted resource management on virtualized providers." Doctoral thesis, Universitat Politècnica de Catalunya, 2011. http://hdl.handle.net/10803/80487.

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Last decade, providers started using Virtual Machines (VMs) in their datacenters to pack users and their applications. This was a good way to consolidate multiple users in fewer physical nodes while isolating them from each other. Later on in 2006, Amazon started offering their Infrastructure as a Service where their users rent computing resources as VMs in a pay-as-you-go manner. However, virtualized providers cannot be managed like traditional ones as they are now confronted with a set of new challenges. First of all, providers must deal efficiently with new management operations such as the dynamic creation of VMs. These operations enable new capabilities that were not there before, such as moving VMs across the nodes, or the ability to checkpoint VMs. We propose a Decentralized virtualization management infrastructure to create VMs on demand, migrate them between nodes, and checkpointing mechanisms. With the introduction of this infrastructure, virtualized providers become decentralized and are able to scale. Secondly, these providers consolidate multiple VMs in a single machine to more efficiently utilize resources. Nevertheless, this is not straightforward and implies the use of more complex resource management techniques. In addition, this requires that both customers and providers can be confident that signed Service Level Agreements (SLAs) are supporting their respective business activities to their best extent. Providers typically offer very simple metrics that hinder an efficient exploitation of their resources. To solve this, we propose mechanisms to dynamically distribute resources among VMs and a resource-level metric, which together allow increasing provider utilization while maintaining Quality of Service. Thirdly, the provider must allocate the VMs evaluating multiple facets such as power consumption and customers' requirements. In addition, it must exploit the new capabilities introduced by virtualization and manage its overhead. Ultimately, this VM placement must minimize the costs associated with the execution of a VM in a provider to maximize the provider's profit. We propose a new scheduling policy that places VMs on provider nodes according to multiple facets and is able to understand and manage the overheads of dealing with virtualization. And fourthly, resource provisioning in these providers is a challenge because of the high load variability over time. Providers can serve most of the requests owning only a restricted amount of resources but this under-provisioning may cause customers to be rejected during peak hours. In the opposite situation, valley hours incur under-utilization of the resources. As this new paradigm makes the access to resources easier, providers can share resources to serve their loads. We leverage a federated scenario where multiple providers share their resources to overcome this load variability. We exploit the federation capabilities to create policies that take the most convenient decision depending on the environment conditions and tackle the load variability. All these challenges mean that providers must manage their virtualized resources in a different way than they have done traditionally. This dissertation identifies and studies the challenges faced by virtualized provider that offers IaaS, and designs and evaluates a solution to manage the provider's resources in the most cost-effective way by exploiting the virtualization capabilities.
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Kundu, Sajib. "Improving Resource Management in Virtualized Data Centers using Application Performance Models." FIU Digital Commons, 2013. http://digitalcommons.fiu.edu/etd/874.

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The rapid growth of virtualized data centers and cloud hosting services is making the management of physical resources such as CPU, memory, and I/O bandwidth in data center servers increasingly important. Server management now involves dealing with multiple dissimilar applications with varying Service-Level-Agreements (SLAs) and multiple resource dimensions. The multiplicity and diversity of resources and applications are rendering administrative tasks more complex and challenging. This thesis aimed to develop a framework and techniques that would help substantially reduce data center management complexity. We specifically addressed two crucial data center operations. First, we precisely estimated capacity requirements of client virtual machines (VMs) while renting server space in cloud environment. Second, we proposed a systematic process to efficiently allocate physical resources to hosted VMs in a data center. To realize these dual objectives, accurately capturing the effects of resource allocations on application performance is vital. The benefits of accurate application performance modeling are multifold. Cloud users can size their VMs appropriately and pay only for the resources that they need; service providers can also offer a new charging model based on the VMs performance instead of their configured sizes. As a result, clients will pay exactly for the performance they are actually experiencing; on the other hand, administrators will be able to maximize their total revenue by utilizing application performance models and SLAs. This thesis made the following contributions. First, we identified resource control parameters crucial for distributing physical resources and characterizing contention for virtualized applications in a shared hosting environment. Second, we explored several modeling techniques and confirmed the suitability of two machine learning tools, Artificial Neural Network and Support Vector Machine, to accurately model the performance of virtualized applications. Moreover, we suggested and evaluated modeling optimizations necessary to improve prediction accuracy when using these modeling tools. Third, we presented an approach to optimal VM sizing by employing the performance models we created. Finally, we proposed a revenue-driven resource allocation algorithm which maximizes the SLA-generated revenue for a data center.
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Feller, Eugen. "Autonomic and Energy-Efficient Management of Large-Scale Virtualized Data Centers." Phd thesis, Université Rennes 1, 2012. http://tel.archives-ouvertes.fr/tel-00785090.

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Large-scale virtualized data centers require cloud providers to implement scalable, autonomic, and energy-efficient cloud management systems. To address these challenges this thesis provides four main contributions. The first one proposes Snooze, a novel Infrastructure-as-a-Service (IaaS) cloud management system, which is designed to scale across many thousands of servers and virtual machines (VMs) while being easy to configure, highly available, and energy efficient. For scalability, Snooze performs distributed VM management based on a hierarchical architecture. To support ease of configuration and high availability Snooze implements self-configuring and self-healing features. Finally, for energy efficiency, Snooze integrates a holistic energy management approach via VM resource (i.e. CPU, memory, network) utilization monitoring, underload/overload detection and mitigation, VM consolidation (by implementing a modified version of the Sercon algorithm), and power management to transition idle servers into a power saving mode. A highly modular Snooze prototype was developed and extensively evaluated on the Grid'5000 testbed using realistic applications. Results show that: (i) distributed VM management does not impact submission time; (ii) fault tolerance mechanisms do not impact application performance and (iii) the system scales well with an increasing number of resources thus making it suitable for managing large-scale data centers. We also show that the system is able to dynamically scale the data center energy consumption with its utilization thus allowing it to conserve substantial power amounts with only limited impact on application performance. Snooze is an open-source software under the GPLv2 license. The second contribution is a novel VM placement algorithm based on the Ant Colony Optimization (ACO) meta-heuristic. ACO is interesting for VM placement due to its polynomial worst-case time complexity, close to optimal solutions and ease of parallelization. Simulation results show that while the scalability of the current algorithm implementation is limited to a smaller number of servers and VMs, the algorithm outperforms the evaluated First-Fit Decreasing greedy approach in terms of the number of required servers and computes close to optimal solutions. In order to enable scalable VM consolidation, this thesis makes two further contributions: (i) an ACO-based consolidation algorithm; (ii) a fully decentralized consolidation system based on an unstructured peer-to-peer network. The key idea is to apply consolidation only in small, randomly formed neighbourhoods of servers. We evaluated our approach by emulation on the Grid'5000 testbed using two state-of-the-art consolidation algorithms (i.e. Sercon and V-MAN) and our ACO-based consolidation algorithm. Results show our system to be scalable as well as to achieve a data center utilization close to the one obtained by executing a centralized consolidation algorithm.
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Feller, Eugen. "Automatic and energy-efficient management of large scale virtualized data centers." Rennes 1, 2012. http://www.theses.fr/2012REN1S136.

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Cette thèse propose Snooze, un système autonome et économique en énergie pour des clouds "Infrastructure-as-a-Service" (IaaS). Pour le passage à l’échelle, la facilité d’administration et la haute disponibilité, Snooze repose sur une architecture hiérarchique auto-configurable et auto-réparante. Pour la gestion de l’énergie, Snooze intègre la surveillance des ressources utilisées par les machines virtuelles (VM), la résolution des situations de sous-charge et de surcharge des serveurs, la gestion de leur alimentation électrique et le regroupement de VMs. Un prototype robuste du système Snooze a été développé et évalué avec des applications réalistes sur la plate-forme Grid’5000. Pour favoriser les périodes d’inactivité des serveurs dans un cloud IaaS, il faut placer les VMs judicieusement et les regrouper. Cette thèse propose un algorithme de placement de VMs fondé sur la méta-heuristique d’optimisation par colonies de fourmis (ACO). Des simulations ont montré que cet algorithme calcule des solutions proches de l’optimal, meilleures que celles de l’algorithme "First-Fit-Decreasing" au prix d’un moins bon passage à l’échelle. Pour le passage à l’échelle du regroupement de VMs, cette thèse apporte deux autres contributions : un algorithme de regroupement de VMs fondé sur l'ACO et un système de regroupement de VMs complètement décentralisé fondé sur un réseau pair-à-pair non structuré de serveurs. Les résultats d’émulation ont montré que notre système passe à l’échelle et qu’il permet d’atteindre un taux d’utilisation du centre de données proche de celui obtenu avec un système centralisé
Large-scale virtualized data centers now require cloud providers to implement scalable, autonomic, and energy-efficient cloud management systems. To address these challenges this thesis proposes Snooze, a novel highly available, easy to configure, and energy-efficient Infrastructure-as-a-Service (IaaS) cloud management system. For scalability and high availability Snooze integrates a self-configuring and healing hierarchical architecture. To achieve energy efficiency Snooze integrates a holistic energy management approach via virtual machine (VM) resource utilization monitoring, server underload/overload mitigation, VM consolidation, and power management. A robust Snooze prototype was developed and extensively evaluated on the Grid'5000 testbed using realistic applications. The experiments have proven Snooze to be scalable, highly available and energy-efficient. One way to favor servers idle times in IaaS clouds is to perform energy-efficient VM placement and consolidation. This thesis proposes a novel VM placement algorithm based on the Ant Colony Optimization (ACO) meta-heuristic. Simulation results have shown that the proposed algorithm computes close to optimal solutions and outperforms the evaluated First-Fit Decreasing algorithm at the cost of decreased scalability. To enable scalable VM consolidation, this thesis makes two further contributions: (i) an ACO-based VM consolidation algorithm; (ii) a fully decentralized VM consolidation system based on an unstructured peer-to-peer network of servers. Emulation conducted on the Grid'5000 testbed has proven our system to be scalable as well as to achieve data center utilization close to the one of a centralized system
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Tesfatsion, Kostentinos Selome. "A Combined Frequency Scaling and Application Elasticity Approach for Energy-Efficient Virtualized Data Centers." Thesis, Umeå universitet, Institutionen för datavetenskap, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-85211.

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At present, large-scale data centers are typically over-provisioned in order to handle peak load requirements. The resulting low utilization of resources contribute to a huge amounts of power consumption in data centers. The effects of high power consumption manifest in a high operational cost in data centers and carbon footprints to the environment. Therefore, the management solutions for large-scale data centers must be designed to effectively take power consumption into account. In this work, we combine three management techniques that can be used to control systems in an energy-efficient manner: changing the number of virtual machines, changing the number of cores, and scaling the CPU frequencies. The proposed system consists of a controller that combines feedback and feedforward information to determine a configuration that minimizes power consumption while meeting the performance target. The controller can also be configured to accomplish power minimization in a stable manner, without causing large oscillations in the resource allocations. Our experimental evaluation based on the Sysbench benchmark combined with workload traces from production systems shows that our approach achieves the lowest energy consumption among the compared three approaches while meeting the performance target.
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Spinner, Simon [Verfasser], Samuel [Gutachter] Kounev, and Kurt [Gutachter] Geihs. "Self-Aware Resource Management in Virtualized Data Centers / Simon Spinner ; Gutachter: Samuel Kounev, Kurt Geihs." Würzburg : Universität Würzburg, 2017. http://d-nb.info/1141576945/34.

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Božić, Nikola. "Blockchain technologies and their application to secure virtualized infrastructure control." Electronic Thesis or Diss., Sorbonne université, 2019. http://www.theses.fr/2019SORUS596.

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Blockchain est une technologie qui fait du concept de registre partagé à partir de systèmes distribués une réalité pour un certain nombre de domaines d’application, du crypto-monnaie à potentiellement tout système industriel nécessitant une prise de décision décentralisée, robuste, fiable et automatisée dans une situation à plusieurs parties prenantes. Néanmoins, les avantages réels de l’utilisation de la blockchain au lieu de toute autre solution traditionnelle (telle que des bases de données centralisées) ne sont pas complètement compris à ce jour, ni quel type de blockchain répond le mieux aux exigences du cas d'utilisation et à son utilisation. Au début, notre objectif est de fournir une sorte de « vademecum » à la communauté, tout en donnant une présentation générale de la blockchain qui dépasse son cas d'utilisation en des crypto monnaies telle que Bitcoin, et en passant en revue une sélection de la vaste littérature qui est apparue au cours des dernières années. Nous décrivons les exigences clés et leur évolution lorsque nous passons des blockchains publics à priver, en présentant les différences entre les mécanismes de consensus proposés et expérimentés, et en décrivant les plateformes de blockchain existantes. De plus, nous présentons la blockchain B-VMOA pour sécuriser les opérations d’orchestration de machines virtuelles pour les systèmes de cloud computing et de virtualisation des fonctions réseau en appliquant la logique de vademecum proposée. À l'aide d'exemples de didacticiels, nous décrivons nos choix de conception et élaborons des plans de mise en œuvre. Nous développons plus avant la logique de vademecum appliquée à l'orchestration dans le cloud et comment elle peut conduire à des spécifications de plateforme précises. Nous capturons les opérations du système clés et les interactions complexes entre elles. Nous nous concentrons sur la dernière version de la plateforme Hyperledger Fabric en tant que moyen de développer le système B-VMOA. De plus, Hyperledger Fabric optimise les performances, la sécurité et l’évolutivité conçues pour le réseau B-VMOA en séparant la charge de travail entre (i) les homologues d’exécution et de validation de transaction et (ii) les nœuds qui sont charges pour l'ordre des transactions. Nous étudions et utilisons une architecture <> qui différencie notre système B-VMOA conçu des systèmes distribués hérités qui suivent une architecture de réplication d'état de machine traditionnelle. Nous paramétrons et validons notre modèle avec les données recueillies sur un banc d'essai réaliste, en présentant une étude empirique pour caractériser les performances du système et identifier les goulots d'étranglement potentiels. En outre, nous présentons les outils que nous avons utilisés, la configuration du réseau et la discussion sur les observations empiriques issues de la collecte de données. Nous examinons l'impact de divers paramètres configurables pour mener une étude approfondie des composants principaux et des performances de référence pour les modèles d'utilisation courants. À savoir, B-VMOA est destiné à être exécuté dans un centre de données. Différentes topologies d'interconnexion de centres de données évoluent différemment en raison des protocoles de communication. Il semble difficile de concevoir efficacement les interconnexions réseau de manière à rentabiliser le déploiement et la maintenance de l’infrastructure. Nous analysons les propriétés structurelles de plusieurs topologies DCN et présentons également une comparaison entre ces architectures de réseau dans le but de réduire les coûts indirects de la technologie B-VMOA. D'après notre analyse, nous recommandons l'hypercube topologie comme solution pour remédier au goulot d'étranglement des performances dans le plan de contrôle B-VMOA provoqué par gossip, le protocole de diffusion, ainsi qu'une estimation de l'amélioration des performances
Blockchain is a technology making the shared registry concept from distributed systems a reality for a number of application domains, from the cryptocurrency one to potentially any industrial system requiring decentralized, robust, trusted and automated decision making in a multi-stakeholder situation. Nevertheless, the actual advantages in using blockchain instead of any other traditional solution (such as centralized databases) are not completely understood to date, or at least there is a strong need for a vademecum guiding designers toward the right decision about when to adopt blockchain or not, which kind of blockchain better meets use-case requirements, and how to use it. At first, we aim at providing the community with such a vademecum, while giving a general presentation of blockchain that goes beyond its usage in Bitcoin and surveying a selection of the vast literature that emerged in the last few years. We draw the key requirements and their evolution when passing from permissionless to permissioned blockchains, presenting the differences between proposed and experimented consensus mechanisms, and describing existing blockchain platforms. Furthermore, we present the B-VMOA blockchain to secure virtual machine orchestration operations for cloud computing and network functions virtualization systems applying the proposed vademecum logic. Using tutorial examples, we describe our design choices and draw implementation plans. We further develop the vademecum logic applied to cloud orchestration and how it can lead to precise platform specifications. We capture the key system operations and complex interactions between them. We focus on the last release of Hyperledger Fabric platform as a way to develop B-VMOA system. Besides, Hyperledger Fabric optimizes conceived B-VMOA network performance, security, and scalability by way of workload separation across: (i) transaction execution and validation peers, and (ii) transaction ordering nodes. We study and use a distributed execute-order-validate architecture which differentiates our conceived B-VMOA system from legacy distributed systems that follow a traditional state-machine replication architecture. We parameterize and validate our model with data collected from a realistic testbed, presenting an empirical study to characterize system performance and identify potential performance bottlenecks. Furthermore, we present the tools we used, the network setup and the discussion on empirical observations from the data collection. We examine the impact of various configurable parameters to conduct an in-dept study of core components and benchmark performance for common usage patterns. Namely, B-VMOA is meant to be run within data center. Different data center interconnection topologies scale differently due to communication protocols. Enormous challenges appear to efficiently design the network interconnections so that the deployment and maintenance of the infrastructure is cost-effective. We analyze the structural properties of several DCN topologies and also present some comparison among these network architectures with the aim to reduce B-VMOA overhead costs. From our analysis, we recommend the hypercube topology as a solution to address the performance bottleneck in the B-VMOA control plane caused by gossip dissemination protocol along with an estimate of performance improvement
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9

Le, Louët Guillaume. "Maîtrise énergétique des centres de données virtualisés : D'un scénario de charge à l'optimisation du placement des calculs." Phd thesis, Ecole des Mines de Nantes, 2014. http://tel.archives-ouvertes.fr/tel-01044650.

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Cette thèse se place dans le contexte de l'hébergement de services informatiques virtualisés et apporte deux contributions. Elle propose premièrement un système d'aide à la gestion modulaire, déplaçant les machines virtuelles du centre pour le maintenir dans un état satisfaisant. Ce système permet en particulier d'intégrer la notion de consommation électrique des serveurs ainsi que des règles propres à cette consommation. Sa modularité permet de plus l'adaptation de ses composants à des problèmes de grande taille. Cette thèse propose de plus un outil pour comparer différents gestionnaires de centres virtualisés. Cet outil injecte un scénario de montée en charge reproductible dans une infrastructure virtualisée. L'injection d'un tel scénario permet d'évaluer les performances du système de gestion du centre grâce à des sondes spécifiques. Le langage utilisé pour cette injection est extensible et permet l'utilisation de scénarios paramétrés.
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Wolke, Andreas [Verfasser], Martin [Akademischer Betreuer] Bichler, and Georg [Akademischer Betreuer] Carle. "Energy efficient capacity management in virtualized data centers / Andreas Wolke. Gutachter: Georg Carle ; Martin Bichler. Betreuer: Martin Bichler." München : Universitätsbibliothek der TU München, 2015. http://d-nb.info/1070372390/34.

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Books on the topic "Virtualized Data Center"

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Malcolm, Orr, and Page Greg, eds. Cloud computing: Automating the virtualized data center. Indianapolis, IN: Cisco Press, 2012.

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Tsai, Linjiun, and Wanjiun Liao. Virtualized Cloud Data Center Networks: Issues in Resource Management. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-32632-0.

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International Business Machines Corporation. International Technical Support Organization, ed. Managing security and compliance in cloud or virtualized data centers. [Poughkeepsie, NY: IBM Corp., International Technical Support Organization], 2013.

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K, Kokula Krishna Hari, ed. An Efficient Load Balancing Algorithm for virtualized Cloud Data Centers: ICCCEG 2014. Vietnam: Association of Scientists, Developers and Faculties, 2014.

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Tsai, Linjiun, and Wanjiun Liao. Virtualized Cloud Data Center Networks: Issues in Resource Management. Springer London, Limited, 2016.

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Tsai, Linjiun, and Wanjiun Liao. Virtualized Cloud Data Center Networks: Issues in Resource Management. Springer, 2016.

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Vachon, Pierre, Sukento Sukirya, Pete Gore, and Brian Clay. Data Center Virtualization: A practical guide to successful deployments of a Virtualized Data Center Infrastructure. Pearson Education, Limited, 2010.

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Iqbal, Mickey, Chris Molloy, Jim Rymarczyk, and Mithkal Smadi. IT Virtualization Best Practices: A Lean, Green Virtualized Data Center Approach. MC Press Online, LLC, 2011.

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It Virtualization Best Practices A Lean Green Virtualized Data Center Approach. MC Press, 2011.

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Iqbal, Mickey, Chris Molloy, Jim Rymarczyk, and Mithkal Smadi. IT Virtualization Best Practices: A Lean, Green Virtualized Data Center Approach. MC Press, LLC, 2011.

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Book chapters on the topic "Virtualized Data Center"

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Tsai, Linjiun, and Wanjiun Liao. "Transformation of Data Center Networks." In Virtualized Cloud Data Center Networks: Issues in Resource Management., 15–27. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-32632-0_3.

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Tsai, Linjiun, and Wanjiun Liao. "Introduction." In Virtualized Cloud Data Center Networks: Issues in Resource Management., 1–7. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-32632-0_1.

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Tsai, Linjiun, and Wanjiun Liao. "Allocation of Virtual Machines." In Virtualized Cloud Data Center Networks: Issues in Resource Management., 9–13. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-32632-0_2.

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Tsai, Linjiun, and Wanjiun Liao. "Allocation of Servers." In Virtualized Cloud Data Center Networks: Issues in Resource Management., 29–39. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-32632-0_4.

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Tsai, Linjiun, and Wanjiun Liao. "Performance Evaluation." In Virtualized Cloud Data Center Networks: Issues in Resource Management., 41–49. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-32632-0_5.

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Tsai, Linjiun, and Wanjiun Liao. "Conclusion." In Virtualized Cloud Data Center Networks: Issues in Resource Management., 51. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-32632-0_6.

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Wu, Jie, Binzhang Fu, and Mingyu Chen. "Stem: A Table-Based Congestion Control Framework for Virtualized Data Center Networks." In Lecture Notes in Computer Science, 122–26. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-68210-5_12.

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Oeldemann, Andreas, Thomas Wild, and Andreas Herkersdorf. "Reducing Data Center Resource Over-Provisioning Through Dynamic Load Management for Virtualized Network Functions." In Architecture of Computing Systems - ARCS 2017, 234–47. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-54999-6_18.

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Quang-Hung, Nguyen, Nam Thoai, Nguyen Thanh Son, and Duy-Khanh Le. "Energy-Aware Lease Scheduling in Virtualized Data Centers." In Modeling, Simulation and Optimization of Complex Processes - HPSC 2012, 195–205. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-09063-4_16.

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Karras, Kimon, Orthodoxos Kipouridis, Nick Zotos, Evangelos Markakis, and George Bogdos. "Enabling Virtualized Programmable Logic Resources at the Edge and the Cloud." In Hardware Accelerators in Data Centers, 149–62. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-92792-3_8.

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Conference papers on the topic "Virtualized Data Center"

1

Erickson, David, Mendel Rosenblum, Brandon Heller, Shuang Yang, Jonathan Chu, Jonathan Ellithorpe, Scott Whyte, Stephen Stuart, Nick McKeown, and Guru Parulkar. "Optimizing a virtualized data center." In the ACM SIGCOMM 2011 conference. New York, New York, USA: ACM Press, 2011. http://dx.doi.org/10.1145/2018436.2018530.

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Kant, K. "Towards a virtualized data center transport protocol." In IEEE INFOCOM 2008 - IEEE Conference on Computer Communications Workshops. IEEE, 2008. http://dx.doi.org/10.1109/infocom.2008.4544645.

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Klymash, Mykhailo, Olga Shpur, Orest Lavriv, and Nazar Peleh. "Information Security in Virtualized Data Center Network." In 2019 3rd International Conference on Advanced Information and Communications Technologies (AICT). IEEE, 2019. http://dx.doi.org/10.1109/aiact.2019.8847764.

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Machida, Fumio, Jianwen Xiang, Kumiko Tadano, and Yoshiharu Maeno. "Combined Server Rejuvenation in a Virtualized Data Center." In 2012 IEEE 9th Int'l Conference on Ubiquitous Intelligence & Computing / 9th Int'l Conference on Autonomic & Trusted Computing (UIC/ATC). IEEE, 2012. http://dx.doi.org/10.1109/uic-atc.2012.52.

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Zhang, Wei, Hangwei Qian, Craig E. Wills, and Michael Rabinovich. "Agile resource management in a virtualized data center." In the first joint WOSP/SIPEW international conference. New York, New York, USA: ACM Press, 2010. http://dx.doi.org/10.1145/1712605.1712626.

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Wo, Tianyu, Qian Sun, Bo Li, and Chunming Hu. "Overbooking-Based Resource Allocation in Virtualized Data Center." In 2012 IEEE 15th International Symposium on Object/Component/Service-Oriented Real-Time Distributed Computing Workshops (ISORCW). IEEE, 2012. http://dx.doi.org/10.1109/isorcw.2012.34.

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ElBouanani, Houssam, Chadi Barakat, Guillaume Urvoy-Keller, and Dino Lopez-Pacheco. "Collaborative Traffic Measurement in Virtualized Data Center Networks." In 2019 IEEE 8th International Conference on Cloud Networking (CloudNet). IEEE, 2019. http://dx.doi.org/10.1109/cloudnet47604.2019.9064127.

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Zhengmin Li, Chunge Zhu, Xinran Liu, and Xiufeng Sui. "Anomaly detection for virtualized data center via outlier analysis." In 2017 IEEE 14th International Conference on Networking, Sensing and Control (ICNSC). IEEE, 2017. http://dx.doi.org/10.1109/icnsc.2017.8000085.

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Tarafdar, Naif, Thomas Lin, Nariman Eskandari, David Lion, Alberto Leon-Garcia, and Paul Chow. "Heterogeneous virtualized network function framework for the data center." In 2017 27th International Conference on Field Programmable Logic and Applications (FPL). IEEE, 2017. http://dx.doi.org/10.23919/fpl.2017.8056790.

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Torquato, Matheus, Erico Guedes, Paulo Maciel, and Marco Vieira. "A Hierarchical Model for Virtualized Data Center Availability Evaluation." In 2019 15th European Dependable Computing Conference (EDCC). IEEE, 2019. http://dx.doi.org/10.1109/edcc.2019.00029.

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