Virtualized Data Centers Research Articles

New Experimental Spectra and Quantitative Modeling of the Bending Dyad of Silane in the 900 cm-1 Region for Its 3 Isotopologues.

The silane (SiH4) molecule is of importance for a wide range of fundamental and applied problems of physics, chemistry, astrophysics, and industry. We present here the newest and clearest complete quantitative analysis and modeling of line positions and intensities in the strongly absorbing ν2/ν4 bending dyad in the 830-1150 cm-1 spectral region. A database of calculated silane lines, SiCaSDa, is made available online through the Virtual Atomic and Molecular Data Centre (VAMDC).

Energy-Efficient Per-Core DVFS for Virtual Machine Management in Cloud Data Centers

Energy efficiency and thermal management are critical challenges in virtualized cloud data centers, particularly for optimizing parallel workloads. Dynamic Voltage and Frequency Scaling (DVFS) is widely used to balance power consumption and computational performance. This study proposes an Adaptive Threshold Per-Core DVFS Governor that dynamically adjusts CPU core frequencies based on per-core utilization, improving energy efficiency and workload performance. The proposed algorithm is evaluated using Charm++ parallel workloads and is benchmarked against existing Linux governors, including the Conservative, OnDemand, and Performance governors. Experimental results demonstrate that the proposed approach achieves superior energy efficiency per Giga-instructions compared to the Conservative and OnDemand governors while maintaining performance levels comparable to the Performance governor. Furthermore, the proposed method reduces average CPU temperature by approximately 5% (2.5◦C lower) compared to the Performance governor, contributing to enhanced thermal management in cloud computing environments. These findings highlight the potential of the adaptive per-core DVFS mechanism for improving energy efficiency and performance in virtualized data centers.

A New Approach to Cloud Resource Scheduling Using Genetic Reinforcement Kernel Optimization and Machine Learning Model

ABSTRACTTwo of the most essential elements of cloud resource management systems are resource management as well as scheduling. Due to the heterogeneity of resources, their interdependencies, and the unpredictable nature of load in a cloud environment, cloud Resource Scheduling (RS) is the most important issue to handle effectively. One of the most challenging tasks in cloud computing is RS, where resources must be assigned to the necessary tasks or jobs in accordance with the necessary Quality of Service (QoS) of the cloud applications. This study suggests a unique method for scheduling cloud resources based on a virtual data center and machine learning model. The genetic reinforcement kernel swarm optimization methodology and cloud data centers are deployed here. The suggested network analysis aims to balance energy usage and SLA. The suggested framework is assessed by doing experiments on the Google Cluster dataset, Planet Lab, and Bitbrains VM traces, as well as three real‐world workload datasets. Execution cost, Execution time, Makespan, Energy consumption, Resource utilization, and Scalability are factors that were examined here. The proposed framework is superior to several performance indicators compared to state‐of‐the‐art techniques. The project's methodology addresses the issues of load imbalance and excessive migration expenses.

Improving the efficiency of using the resources of virtual data centers with a heterogeneous structure by repositioning virtual machines

The article presents an approach to managing virtualized data centers (VSDDC), which are based on virtual machine hypervisors – software management modules that allow multiple virtual machines to use the resources of a single server platform. The aim of the work is to increase the efficiency of using VSDDC resources with a heterogeneous structure through the development of mathematical and software for the relocation of virtual machines. As a result, a model of multidimensional representation of virtualized resources has been developed, taking into account the normalized value of their use by live migration algorithms and providing the possibility of calculating their imbalance, which determines the need to perform the process of repositioning virtual machines; an algorithm for repositioning virtual machines has been created based on a reasonably chosen method of solving the problem of multidimensional combinatorial optimization; an architecture of a software-implemented support system for repositioning virtual machines in VSDDC has been proposed with a heterogeneous structure; An experimental study was conducted to evaluate the efficiency of using VSDDC resources based on the proposed algorithm for solving the problem of reallocation of virtual machines for various variants of the VSDDC structure.

A METHOD FOR REDISTRIBUTING VIRTUAL MACHINES OF HETEROGENEOUS DATA CENTRES

Ant colony algorithms are efficient due to their ability to avoid local minima and find global optima through parallel exploration of multiple solutions. This is achieved through a combination of deterministic and stochastic elements. Deterministic elements include selection rules based on pheromone traces and heuristic information. Stochastic elements introduce an element of randomness and variability. This ensures exploration of new paths. Such a flexible structure makes ant colony algorithms extremely popular in complex and dynamically changing problems, such as the traveling salesman problem and the task of redistributing virtual machines. The subject of study in the article is methods of optimizing the placement of virtual machines of heterogeneous data centers. The purpose of the article is to improve the efficiency of resource use in heterogeneous virtualized data centers by redistributing virtual machines. The following results were obtained. The article presents the developed algorithm for redistributing virtual machines, based on the ant colony metaheuristics, which provides obtaining a migration matrix of virtual machines, differing from known algorithms by taking into account the heterogeneous structure of data centers and additional resources, which represent overhead costs required by the algorithms of virtual machines Live Migration, when calculating it. The developed support system provides flexibility, scalability and a high degree of adaptation to the conditions of modern heterogeneous data centers. It provides the ability to centralize management and monitoring, while supporting the requirements of cross-platform and integration with existing monitoring solutions, which makes it an important tool for ensuring the reliability and efficiency of data centers. Conclusion. The redistributing virtual machines support system not only simplifies the tasks of administrators, but also promotes more rational use of computing power, which is especially important in the context of today's dynamic development of IT infrastructure.

A new model-based approach for estimating rural hospital markets.

To provide a new approach for defining rural hospital markets. First, we estimated models of hospital choice. We defined hospitals in the choice set using nationwide hospital data from the Healthcare Cost Report Information System (HCRIS). We modeled hospital choice using conditional logit regression and 2019 Medicare Fee-for-Service (FFS) claims data from the Centers for Medicare & Medicaid Services (CMS) Virtual Research Data Center. Next, we calculated estimated inpatient and emergency department utilization by patient ZIP code. We then estimated the total Medicare FFS volume for each hospital as well as the percent of each hospital's volume attributable to each ZIP code. We sorted ZIP codes by the patient volume attributable to the given hospital (from most volume to least volume) and then added ZIP codes to the market until at least 50% of the hospital's total patient volume was represented. The average rural hospital market included three ZIP codes, an estimated population total of 37,221, and an estimated 5385 Medicare FFS beneficiaries. Furthermore, the average rural hospital had an estimated market share of 29%. A lower estimated market population was found for Critical Access Hospitals, hospitals unaffiliated with a system, hospitals with a smaller number of acute beds, and hospitals with fewer staff. We developed a new approach for defining rural hospital markets. This approach can be used to inform health services researchers, policymakers, and communities about key market predictors of rural hospital financial distress, populations adversely affected by rural hospital closure, and more.

Data Center Virtualization: Challenges and Innovations in Data Protection

With the rapid development of information technology, data center virtualization has become a key technology to improve resource utilization and reduce operational costs. However, the complexity and dynamism of virtualized environments bring new challenges to data protection. This paper aims to explore the application of data center virtualization technology and deeply analyze the strategies and technologies for data protection in virtualized environments. The article first reviews the development history of data center virtualization technology and the theoretical basis of data protection, then discusses in detail the application of virtualization technology in actual data centers, including virtualization architecture, implementation steps, and optimization strategies. Subsequently, the paper focuses on analyzing key data protection technologies such as data backup and recovery, data encryption, and the assurance of data integrity and availability, and discusses the practical application of these technologies in virtualized environments. In addition, the article identifies the challenges faced by data protection in virtualized environments and proposes corresponding countermeasures. Finally, the paper summarizes the research findings and offers suggestions for future research directions. Through in-depth research on data center virtualization and data protection, this paper provides theoretical guidance and practical references for data center managers to ensure the security and reliability of data in virtualized environments.

Virtualization and energy management optimization of high speed computer network data centers based on optical switching and network technology

Virtualization and energy management optimization of high speed computer network data centers based on optical switching and network technology

BASECOL2023 scientific content

Context. The global context of making numerous data produced by researchers available requires collecting and organising the data, assigning meaningful metadata, and presenting the data in a meaningful and homogeneous way. The BASECOL database, which collects inelastic rate coefficients for application to the interstellar medium and to circumstellar and cometary atmospheres, meets those requirements. Aims. We aim to present the scientific content of the BASECOL2023 edition. Methods. While the previous versions relied on finding rate coefficients in the literature, the current version is populated with published results sent by the producers of data. The paper presents the database, the type of data that can be found, the type of metadata that are used, and the Virtual Atomic and Molecular Data Centre (VAMDC) standards that are used for the metadata. Finally, we present the different datasets species by species. Results. As the BASECOL database, interconnected with the VAMDC e-infrastructure, uses the VAMDC standards, the collisional data can be extracted with tools using VAMDC standards and can be associated with spectroscopic data extracted from other VAMDC connected databases such as the Cologne database for molecular spectroscopy (CDMS), the jet propulsion laboratory molecular spectroscopy database (JPL), and the high-resolution transmission molecular absorption database (HITRAN).

Remote DasaLAB: datacenter as a laboratory for remote learning

ABSTRACT The pandemic situation banned the presence of teachers and students in the classrooms disrupting the typical teaching process. Videoconferencing services have been used successfully for lectures, but they are insufficient for hands-on laboratories where the physical presence is a requirement (i.e. to access specific hardware). Enabling remote access to the equipment allows to overcome this issue, but the students must share resources (temporarily or physically) and lack full control on the equipment. This is not optimal for some subjects, such as the practical labs on datacenter management, which are increasingly being added into the IT higher education curriculum. In this paper, we present the design and implementation of a distributed laboratory environment, so-called Remote DasaLAB, to create and deploy virtual datacenters using the student's owned resources to support the practical training of students in remote (or hybrid) mode. This environment is flexible, cheap, easy to implement with available commodity resources (the students' computers) and provides full control over the platform. We also present a specific use case on leveraging Remote DasaLAB for the practical assignments of an Operating Systems subject, in which the students build a virtual datacenter composed of multiple nodes and can properly run a containerized application distributed in these nodes.

Real-time power management in virtualized data centers using predictive analytics

With the growing demand for cloud services and the proliferation of data-intensive applications, power management in virtualized data centers has become increasingly critical. Efficient power management not only reduces operational costs but also minimizes the environmental impact of data center operations. This paper explores the implementation of real-time power management in virtualized data centers using predictive analytics. By leveraging machine learning algorithms to predict power consumption patterns, we can optimize resource allocation, enhance energy efficiency, and maintain performance. This study outlines a framework for integrating predictive analytics into power management systems, evaluates its potential benefits, and discusses the challenges involved.

Energy-efficient resource allocation in cloud infrastructure using L3F-MGA and E-ANFIS

Energy-efficient resource allocation in cloud infrastructure using L3F-MGA and E-ANFIS

Measuring the impact of SR-IOV and virtualization on packet round-trip time

Measuring the impact of SR-IOV and virtualization on packet round-trip time

ABLA: Application-Based Load-Balanced Approach for Adaptive Mapping of Datacenter Networks

Cloud-based services are growing more rapidly than ever, and so does the management challenge on their providers’ side. Cloud-based datacenter networks are built with nodes of huge processing power, connected by high bandwidth capacities to carry their interior traffic requirements. However, such cloud networks still have limits that are imposed not necessarily by their physical components, but by the schemes of resource management being deployed. Traditionally, for an institute to provide services, it needs to have its own datacenter facility that interconnects its servers through a topology that matches its desired administrative policies and scaling objectives. With the theme of cloud-based IaaS, such datacenter topologies can be created virtually over the cloud. Nowadays, a significant part of those institutes who provide us with our daily services have their infrastructures hosted over cloud ones. Therefore, resources of such cloud networks need to be efficiently utilized, in order to keep their performance and hosting prices competitive. A typical datacenter network mainly consists of server nodes and network links. Besides the resources of the server nodes, the network bandwidth resources are considered a crucial key determinant for the whole datacenter performance. Indeed, a server without sufficient bandwidth capacities is almost useless. Proposals in the literature present schemes for resource utilization on either side of the problem at a time: the nodes or the links. Working in isolation can never deliver efficient mapping solutions. ABLA is an Application-Based, and Load balancing Approach for adaptive mapping proposal. ABLA’s methodology tackles both sides of the datacenter, the nodes and links. It starts by (1) breaking down the node’s resource requirement for the requested applications to be hosted over the virtual server machines besides (2) reading the topological connectivity and bandwidth requirements for each virtual node to all other nodes in the virtual datacenter topology. Compared to other models in the literature, the simulation results show that our proposed ABLA model provides for complete mapping services via load-balanced hosting networks. This allows for competitive hosting prices, with higher performance and service satisfaction rates.

Progressive-fidelity computation of the genetic algorithm for energy-efficient virtual machine placement in cloud data centers

Progressive-fidelity computation of the genetic algorithm for energy-efficient virtual machine placement in cloud data centers

IaaS Cloud Architecture Distributed Cloud Infrastructures and Virtualized Data centers

In data centers, expensive, rigid mainframe-based systems have replaced flexible distributed architectures built on commodity technology. These architectures may be dynamically divided, molded, and modified to accommodate many business procedures and shifting service requirements. Virtualization is crucial in facilitating data center deployment as it separates the system and network from the fundamental physical components and storage management systems. By leveraging virtualized infrastructures, organizations can consolidate servers and provision resources on-demand, leading to heightened rates of server use and significant expenses as well as energy savings. To ensure optimal data center operations, efficiency, and security, it is crucial to control these virtual networks in a maintainable manner. The cloud network manager is crucial at this point in the data center architecture. Delivering infrastructure as a service, which converts conventional data centers into cloud-like designs, is its primary duty. Data centers of the future will resemble personal Internet as a Service platform in terms of being able to execute virtualized services in a flexible and agile manner. The virtual infrastructure manager coordinates the digital deployment of resources, sometimes referred to as the cloud operating system in this context, which also oversees the monitoring and management network for natural and virtual services. By managing the data center as a cloud, it is also feasible to add distant services from other federated data centers or industrial clouds to the local infrastructure.

Assessment of the FAIRness of the Virtual Atomic and Molecular Data Centre following the Research Data Alliance evaluation framework

Assessment of the FAIRness of the Virtual Atomic and Molecular Data Centre following the Research Data Alliance evaluation framework

A Virtual Data Center Comparison Of Different Firewalls' Performance

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.

Comparison Of Different Firewalls Performance In A Virtual For Cloud Data Center

Every data centre, whether virtual or physical, relies on its network, and the firewall is an essential part of that network for safe communication. Data centre connection can be protected by a variety of firewall types, including software firewalls, physical firewalls, virtual appliance firewalls, and kernel-integrated firewalls. There are several factors to consider when selecting a firewall, especially in a virtualized data centre, where each firewall works differently in different situations. Virtualized data centres are intended to yield lower budgets, efficient management extensibility, better utilization of available resources, scalability, and energy resilience, among several other advantages. Virtualized data centres are the topic of this study, which examines the application of firewalls. 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. With its distributed firewall functionality, virtual machines can travel across hypervisors with no disruption to their security settings, if their policies remain the same. A kernel-based, distributed firewall is the best way to protect against viruses.

Critical Analysis on Detection and Mitigation of Security Vulnerabilities in Virtualization Data Centers

There is an increasing demand for IT resources in growing business enterprises. Data center virtualization helps to meet this increasing demand by driving higher server utilization and utilizing un-used CPU cycles without causes much increase in new servers. Reduction in infrastructure complexities, Optimization of cost of IT system management, power and cooling are some of the additional benefits of virtualization. Virtualization also brings various security vulnerabilities. They are prone to attacks like hyperjacking, intrusion, data thefts, denial of service attacks on virtualized servers and web facing applications etc. This works identifies the security challenges in virtualization. A critical analysis on existing state of art works on detection and mitigation of various vulnerabilities is presented. The aim is to identify the open issues and propose prospective solutions in brief for these open issues.