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About 10,000 papers for “cloud infrastructure”

Cloud infrastructure.

Richard Bean (3981452), Stephen Snow (9105590), Mashhuda Glencross (7168703) et al. · Figshare · 2020

Cited by 0Open access

Cloud Infrastructure

Yushi Shen, Yale Li, Ling Wu et al. · Advances in systems analysis, software engineering, and high performance computing book series · 2013

This chapter focuses on the different aspects of cloud computing virtualization. It introduces the fundamental concepts of computer virtualization, storage virtualization, network virtualization, and application virtualization. Virtualization techniques, infrastructure, components, and implementation are described in detail.

Cited by 0

Cloud Computing Infrastructure

Ronnie B. Santelicesa, Bartolome T. Tanguilig Iii B · 2016

Higher Education Institutions (HEIs) are required to submit documents to the Commission on Higher Education (CHED) including faculty members ’ data when applying for a new program offering. Based on the documents submitted, problems were encountered by CHED as some academic institutions submit documents of faculty members ’ who are not connected with them, or faculty members ’ who are connected but associated with other institutions. Proper and automated validation processes may be utilized to improve the commission’s regulation procedures on validation processes of the documents. The study proposed the CHED Faculty Information System (CHED-FIS) utilizing Cloud Computing Infrastructure. Relevant information where gathered through CHED’s Memorandum Orders and by interviewing CHED personnel as the bases in developing the system. The study made use of descriptive and developmental methods of research. The software development process applied is prototyping. The study likewise utilized the Hierarchical Input Process Output (HIPO) chart to describe the various components of the system and their relationships to one another during implementation. A structured analysis technique known as data flow diagram (DFDs) was used and presents a graphical representation of data processes in the organization. The framework for the information systems architecture was structured using a 3 –Tier architectural model which consists of presentation, logic and data tier. For the evaluation of the system, five-point rating scale questionnaire was used, with CHED Central Office and CHED Regional Office personnel as respondents, to determine the system’s functionality, efficiency,

Cited by 0

JINR Cloud Infrastructure

V. Korenkov, Nikolay Kutovskiy, N. Balashov et al. · Procedia Computer Science · 2015

Cloud technologies are already wide spread among IT industry and start to gain popularity in academic field. To provide a modern computing facility for JINR users participating in different national and international scientific projects as well as to satisfy the needs of developers (development, testing and debugging various apps in various environments) and system administrators (testing and studying specifics of installation and operation of new apps or verifying updates) a cloud infrastructure was deployed at the Laboratory of Information Technologies of the Joint Institute for Nuclear Research (LIT JINR). Initially having simple setup with single front-end cloud node and few cluster nodes only it is now transformed into robust powerful cloud platform with front-end core services in high availability configuration distributed over two servers including MySQL data base replicas, and cloud data store based on distributed network file system. Users authentication in cloud web GUI via Kerberos, a custom driver for OpenVZ virtualization support as well as a driver for integration with other private clouds on infrastructure level and visualization of statistics on cloud resources usage have been developed in-house for our own needs. The JINR cloud is used not only by JINR users, developers and system administrators to fulfill JINR commitments in different national and international projects but also as a computing facility in BES-III experiment.

Cited by 4Open access

Cloud Infrastructure Security

Mohammad GhasemiGol · 2019

Cloud infrastructure consists of different components such as servers, storage, network, management and deployment software, and platform virtualization. Therefore, the cloud infrastructure security is the most important part in cloud security and any attacks to the cloud infrastructure will cause a large amount of service disruption. In this chapter, we investigate Cloud infrastructure security issues as one of the most important part of cloud security, analyze the infrastructure security in several existing Cloud platforms, and discusses some countermeasure to protect cloud infrastructure against various threats and vulnerabilities.

Cited by 1

eScience Cloud Infrastructure

Matthias Keller, Dirk Meister, André Brinkmann et al. · 2011

Grid computing enables access to high performance computing resources by offering unified interfaces to compute facilities of distributed compute centers. These compute centers are limited in personal capacity and in support capabilities for different communities/VOs. This work presents a solution to this management problem by facilitating the natural interface introduced by virtualization to separate hardware and application provisioning. Any eScience community may provide preconfigured applications within virtual machine images and compute centers run these without having to maintain applications. This is similar to the Infrastructure as a Service and Software as a Service known from cloud computing. Additionally, in contrast to the state of the art in grid computing, we propose a scalable process to maintain compute resources for scientific users, including the definition of a chain of trust between users and compute centers, which simplifies the addition of communities and resources. As a result, this paper lays the foundation for a next-generation eScience Cloud improving the accessibility of compute resources for research and industry.

Cited by 8

JINR cloud infrastructure evolution

A. V. Baranov, N. Balashov, Nikolay Kutovskiy et al. · Physics of Particles and Nuclei Letters · 2016

To fulfil JINR commitments in different national and international projects related to the use of modern information technologies such as cloud and grid computing as well as to provide a modern tool for JINR users for their scientific research a cloud infrastructure was deployed at Laboratory of Information Technologies of Joint Institute for Nuclear Research. OpenNebula software was chosen as a cloud platform. Initially it was set up in simple configuration with single front-end host and a few cloud nodes. Some custom development was done to tune JINR cloud installation to fit local needs: web form in the cloud web-interface for resources request, a menu item with cloud utilization statistics, user authentication via Kerberos, custom driver for OpenVZ containers. Because of high demand in that cloud service and its resources over-utilization it was re-designed to cover increasing users’ needs in capacity, availability and reliability. Recently a new cloud instance has been deployed in high-availability configuration with distributed network file system and additional computing power.

Cited by 36

Software-Defined Cloud Infrastructure

R. Mohanasundaram, A. Jayanthiladevi, G Keerthana · IGI Global eBooks · 2021

Cloud computing suggests that the applications conveyed as services over the internet and frameworks programming in the server that give various services and offers in “pay as you go” trend which means pay only for what you use. The information and services are managed as software as a service (SaaS). Some sellers utilize terms, for example, IaaS (infrastructure as a service) and PaaS (platform as a service). The purpose of cloud computing is quickly expanding in everyday life. Today the use of cloud computing is widespread to the point that it is being utilized even in the medicinal services industry. As the development of cloud computing in healthcare is happening at a fast rate, we can expect a noteworthy piece of the healthcare administrations to move onto the Cloud and along these lines more focus is laid on giving cost-effective and efficient services to the general population all around the world. Cloud these days are turning into the new building pieces of significant organizations spread the world over. They offer assistance in servicing to offer different frameworks. Cloud computing has enhanced its technique and technologies in a better way to provide better services. Existing e-healthcare has many difficulties from advancement to usage. In this chapter, the authors discuss how cloud computing is utilized and the services provided by the Cloud and their models and its infrastructure.

Cited by 1

Safe cloud infrastructure design

Marie Hanzlová · Digital Repository (National Repository of Grey Literature) · 2013

This diploma thesis is focused on the security of cloud computing. Theoretical part of this thesis identifies options which generally lead to higher safety and availability of applications, regardless of the solution. A package of cloud services (called Productivity Suite) was defined, based on the customers' requirements, which is built on Microsoft platform and combined of the following products: Microsoft Exchange, Microsoft SharePoint, Microsoft Lync and is intended to be used by end customers. Specification of the service package, identified opportunities for strengthening the level of security and requirements of potential customers are the primary inputs for designing safe cloud infrastructure, which is the main contribution of this thesis. First step of designing infrastructure is to choose the service provider of data center, who will operate the solution. A decision must be made to select leased solution or owned components. The result of this part is a calculation, which contains all HW components (servers, firewalls, switches, tape library backups, disk arrays) and SW components considering the licensing policy, SSL certificate, domain, backup solution and other operating costs. The solution is limited by financial resources. The priority is safety, security and quality of services.

Cited by 0

PRACTICAL CLOUD COMPUTING INFRASTRUCTURE

James Lembke · Figshare · 2021

Cloud and parallel computing are fundamental components in the processing of large data sets. Deployments of distributed computers require network infrastructure that is fast, efficient, and secure. Software Defined Networking (SDN) separates the forwarding of network data by switches (data plane) from the setting and managing of network policies (control plane). While this separation provides flexibility for setting network policies affecting the establishment of network flows in the data plane, it provides little to no fault tolerance for failures, either benign or caused by corrupted/malicious applications. Such failures can cause network flows to be incorrectly routed through the network or stop such flows altogether. Without protection against faults, cloud network providers using SDN run the risk of inefficient allocation of network resources or even data loss. Furthermore, the asynchronous nature existing protocols for SDN does not provide a mechanism for consistency in network policy updates across multiple switches.In addition, cloud and parallel applications require an efficient means for accessing local system data (input data sets, temporary storage locations, etc.). While in many cases it may be possible for a process to access this data by making calls directly to a file system (FS) kernel driver, this is not always possible (e.g. when using experimental distributed FSs where the needed libraries for accessing the FS only exist in user space).This dissertation provides a design for fault tolerance of SDN and infrastructure for advancing the performance of user space FSs. It is divided into three main parts. The first part describes a fault tolerant, distributed SDN control plane framework. The second part expands upon the fault tolerant approach to SDN control plane by providing a practical means for dynamic control plane membership as well as providing a simple mechanism for controller authentication through threshold signatures. The third part describes an efficient framework for user space FS access.This research makes three contributions. First, the design, specification, implementation, and evaluation of a method for fault tolerant SDN control plane that is inter-operable with existing control plane applications involving minimal instrumentation of the data plane runtime. Second, the design, specification, implementation and evaluation of a mechanism for dynamic SDN control plane membership that all ensure consistency of network policy updates and minimizes switch overhead through the use of distributed key generation and threshold signatures. Third, the design, specification, implementation, and evaluation of a user space FS access framework that is correct to the Portable Operating System Interface (POSIX) specification with significantly better performance over existing user space access methods, while requiring no implementation changes for application programmers.

Cited by 0Open access

Cloud Infrastructure for Robotics

C. Harinakshi, A. Masooda, G. Suchetha · Advances in computational intelligence and robotics book series · 2024

The integration of cloud infrastructure with robotics transforms the field by providing a cost-effective platform for developing, testing, and deploying robotic applications. Cloud's on-demand computing resources accelerate innovation, allowing developers to experiment with new algorithms efficiently. This global collaboration enables remote control and testing of robots worldwide, overcoming geographical constraints. Cloud infrastructure enhances deployment by offloading intensive tasks, reducing hardware requirements, and promoting cost-effectiveness. Centralized fleet management streamlines operations, ensuring uniform updates and security patches for system stability. Robust security measures, including encryption and authentication, address privacy concerns. Cloud robotics implement edge computing for local data processing, minimizing the risk of breaches. Scalability accommodates growing demands, enabling businesses to adapt without significant investments.

Cited by 1

PRACTICAL CLOUD COMPUTING INFRASTRUCTURE

Lembke, James A · Purdue · 2021

Cloud and parallel computing are fundamental components in the processing of large data sets. Deployments of distributed computers require network infrastructure that is fast, efficient, and secure. Software Defined Networking (SDN) separates the forwarding of network data by switches (data plane) from the setting and managing of network policies (control plane). While this separation provides flexibility for setting network policies affecting the establishment of network flows in the data plane, it provides little to no fault tolerance for failures, either benign or caused by corrupted/malicious applications. Such failures can cause network flows to be incorrectly routed through the network or stop such flows altogether. Without protection against faults, cloud network providers using SDN run the risk of inefficient allocation of network resources or even data loss. Furthermore, the asynchronous nature existing protocols for SDN does not provide a mechanism for consistency in network policy updates across multiple switches.In addition, cloud and parallel applications require an efficient means for accessing local system data (input data sets, temporary storage locations, etc.). While in many cases it may be possible for a process to access this data by making calls directly to a file system (FS) kernel driver, this is not always possible (e.g. when using experimental distributed FSs where the needed libraries for accessing the FS only exist in user space).This dissertation provides a design for fault tolerance of SDN and infrastructure for advancing the performance of user space FSs. It is divided into three main parts. The first part describes a fault tolerant, distributed SDN control plane framework. The second part expands upon the fault tolerant approach to SDN control plane by providing a practical means for dynamic control plane membership as well as providing a simple mechanism for controller authentication through threshold signatures. The third part describes an efficient framework for user space FS access.This research makes three contributions. First, the design, specification, implementation, and evaluation of a method for fault tolerant SDN control plane that is inter-operable with existing control plane applications involving minimal instrumentation of the data plane runtime. Second, the design, specification, implementation and evaluation of a mechanism for dynamic SDN control plane membership that all ensure consistency of network policy updates and minimizes switch overhead through the use of distributed key generation and threshold signatures. Third, the design, specification, implementation, and evaluation of a user space FS access framework that is correct to the Portable Operating System Interface (POSIX) specification with significantly better performance over existing user space access methods, while requiring no implementation changes for application programmers.

Cited by 0Open access

Integrated Cloud Infrastructure Offerings

2018

This chapter presents information on the Understanding Cloud Fundamentals 210-451 CLDFND exam that expects the candidate to understand and describe the various integrated offerings available as well as the underlying concepts. A pool of devices (POD) can be described as a grouping of common infrastructure such as network, computing, storage, and application components that deliver a network service or application. The POD is a homogenous structure, making it easy to repeat and scale because its components are known and can be easily replicated. FlexPod, from Cisco and Network Appliance, is the first integrated solution. FlexPod is a single-rack solution that integrates all the required equipment needed for a specific application. Some of the FlexPod applications include the VMware virtualization POD, XenDesktop for virtualized desktop, a private cloud, Oracle Real Application Cluster (RAC), ACI, and Docker containers.

Cited by 0

D2.2 Cloud-native infrastructure

Apostolakis, Konstantinos · Zenodo (CERN European Organization for Nuclear Research) · 2023

This deliverable reports on the final list of technical requirements; component specifications; and overall platform architecture driving the design of the 5G-EPICENTRE integrated solution. It corresponds to the second and final version of deliverable D1.3 “Experimentation requirements and architecture specification preliminary version”. The deliverable does not replace the precursor document, but rather complements it with information that corresponds to the progress made in Tasks T1.2 and T1.3 since the delivery of D1.3. Wherever specified however, the contents in this document shall take precedence over those in D1.3, thus reflecting the project’s evolutionary approach, and capacity of the Consortium to align to evolving needs and developments outside its control.The intention of this document is to provide a comprehensive overview of the facility technical specifications, along with a functional viewpoint of the architectural building blocks that will comprise the final platform to be delivered. Therefore, a high-level overview of the envisioned roles, responsibilities and interrelationships among platform components will be documented, to be used as guidelines for the final development of the individual technological components in the context of Work Packages 2-4.This document provides a thorough description of the methodology and tools used to verify and validate the platform stakeholders’ requirements, which have been previously analysed and classified into a comprehensive set of high-level functional and non-functional requirements in D1.3. New platform stakeholders (i.e., experimenters expected to utilise the platform for the purpose of experimenting with their solutions) have been consulted to inform the 5G-EPICENTRE platform design based on their needs and expectations regarding the elicited capabilities that the system should expose for 5G experimentation. In addition, the list of technical requirements has been verified, validated and re-prioritized, based on those stakeholders’ feedback. This insight has been utilised in order to re-imagine (wherever necessary) the original architectural model, to meet stakeholder intent.The document then presents the methodology to refine this architectural model, namely the various stages of the architecture re-design approach. These constitute a technology exploration step, informed further by the joint activities of the 5G-PPP ICT-41 projects with respect to the joint definition of the Network Applications ecosystem. This step was followed by a top-down re-design of the platform architecture, identifying both new and obsolete building blocks and functionalities, as well as tools and solutions for crucial system “must-have” features, that have evolved in parallel with project activities (e.g., mature Karmada management system for cross-orchestration of Kubernetes cluster resources becoming available in July 2021 – M7). The process was finally complemented by a bottom-up re-specification of both past and present functional blocks.Finally, four architectural viewpoints are defined, namely the functional view; information view; deployment view; and security view. The functional view specifies the roles and capabilities provided by the various functional blocks identified in the re-design process. The information view defines how information flows through the integrated system during common usage scenarios of the platform component stack. The deployment view provides insight on deployment of the hardware and software artefacts across available virtualised and bare-metal infrastructure. Finally, the security view incorporates a security perspective in terms of how the larger attack surface created by embracing a Kubernetes deployment environment can be addressed by design; as well as via dedicated Network Application solutions offered by the platform itself.The deliverable represents the final output of Task T1.2 and T1.3 of the 5G-EPICENTRE Work Package 1.

Cited by 0Open access