Scheduling refers to allocating computing resources like processor time and memory to processes. In cloud computing, scheduling maps jobs to virtual machines. There are two levels of scheduling - at the host level to distribute VMs, and at the VM level to distribute tasks. Common scheduling algorithms include first-come first-served (FCFS), shortest job first (SJF), round robin, and max-min. FCFS prioritizes older jobs but has high wait times. SJF prioritizes shorter jobs but can starve longer ones. Max-min prioritizes longer jobs to optimize resource use. The choice depends on goals like throughput, latency, and fairness.
This Presentation provides a detailed insight about Collaborating Using Cloud Services Email Communication over the Cloud - CRM Management – Project Management-Event
Management - Task Management – Calendar - Schedules - Word Processing –
Presentation – Spreadsheet - Databases – Desktop - Social Networks and Groupware.
Need for Virtualization – Pros and cons of Virtualization – Types of Virtualization –System VM, Process VM, Virtual Machine monitor – Virtual machine properties - Interpretation and binary translation, HLL VM - supervisors – Xen, KVM, VMware, Virtual Box, Hyper-V.
This document contains information about an exam for the position of Assistant Manager (Technical) at Bangladesh Telecommunication Company Limited (BTCL). It includes 10 multiple choice questions covering topics like protocols, fiber optic transmission, and signal processing. It also contains information about a previous exam for the position of Assistant Engineer (CSE) at BTCL from 2017, including 18 questions on topics such as data structures, SQL queries, pipelining, and IP addressing.
Automatic gender and age classification has become quite relevant in the rise of social media platforms. However, the existing methods have not been completely successful in achieving this. Through this project, an attempt has been made to determine the gender and age based on a frame of the person. This is done by using deep learning, OpenCV which is capable of processing the real-time frames. This frame is given as input and the predicted gender and age are given as output. It is difficult to predict the exact age of a person using one frame due the facial expressions, lighting, makeup and so on so for this purpose various age ranges are taken, and the predicted age falls in one of them. The Adience dataset is used as it is a benchmark for face photos and includes various real-world imaging conditions like noise, lighting etc.
1. A string is a one-dimensional array of characters terminated by a null character. Strings can be initialized during compilation or at runtime.
2. Common string functions like scanf(), gets(), getchar() are used to input strings while printf(), puts(), putchar() are used to output strings.
3. Library functions like strcpy(), strcat(), strcmp(), strlen() allow manipulation of strings like copying, concatenation, comparison and finding length.
Binary addition, Binary subtraction, Negative number representation, Subtraction using 1’s complement and 2’s complement, Binary multiplication and division, Arithmetic in octal, hexadecimal number system, BCD and Excess – 3 arithmetic
Cloud computing has several key characteristics that provide benefits to both consumers and providers of cloud services. These characteristics include on-demand access to resources, no upfront commitments, simplified scalability, efficient allocation of resources, and energy efficiency. The essential characteristics of cloud computing that define its nature include on-demand self-service, broad network access, resource pooling, rapid elasticity, and measured services.
Parallel and distributed computing allows problems to be broken into discrete parts that can be solved simultaneously. This approach utilizes multiple processors that work concurrently on different parts of the problem. There are several types of parallel architectures depending on how instructions and data are distributed across processors. Shared memory systems give all processors access to a common memory space while distributed memory assigns private memory to each processor requiring explicit data transfer. Large-scale systems may combine these approaches into hybrid designs. Distributed systems extend parallelism across a network and provide users with a single, integrated view of geographically dispersed resources and computers. Key challenges for distributed systems include transparency, scalability, fault tolerance and concurrency.
Cloud Computing offers an on-demand and scalable access to a shared pool of resources hosted in a data center at providers’ site. It reduces the overheads of up-front investments and financial risks for the end-user. Regardless of the fact that cloud computing offers great advantages to the end users, there are several challenging issues that are mandatory to be addressed.
This document provides an overview of cluster computing. It defines a cluster as a group of loosely coupled computers that work together closely to function as a single computer. Clusters improve speed and reliability over a single computer and are more cost-effective. Each node has its own operating system, memory, and sometimes file system. Programs use message passing to transfer data and execution between nodes. Clusters can provide low-cost parallel processing for applications that can be distributed. The document discusses cluster architecture, components, applications, and compares clusters to grids and cloud computing.
Memory virtualization uses a portion of a disk drive as an extension of main memory. It divides both main memory and virtual memory into pages of equal size. Only needed pages reside in memory at a time, while unnecessary pages are stored on disk. When memory runs low, pages are written to the disk swap file as virtual memory. This allows larger programs to run in less physical RAM by swapping pages between disk and memory as needed.
The document discusses different types of virtualization including hardware, network, storage, memory, software, data, and desktop virtualization. Hardware virtualization includes full, para, and partial virtualization. Network virtualization includes internal and external virtualization. Storage virtualization includes block and file virtualization. Memory virtualization enhances performance through shared, distributed, or networked memory that acts as an extension of main memory. Software virtualization allows guest operating systems to run virtually. Data virtualization manipulates data without technical details. Desktop virtualization provides remote access to work from any location for flexibility and data security.
4.1Introduction
- Potential Threats and Attacks on Computer System
- Confinement Problems
- Design Issues in Building Secure Distributed Systems
4.2 Cryptography
- Symmetric Cryptosystem Algorithm: DES
- Asymmetric Cryptosystem
4.3 Secure Channels
- Authentication
- Message Integrity and Confidentiality
- Secure Group Communication
4.4 Access Control
- General Issues
- Firewalls
- Secure Mobile Code
4.5 Security Management
- Key Management
- Issues in Key Distribution
- Secure Group Management
- Authorization Management
This document discusses deploying infrastructure as a service (IaaS) using Eucalyptus. Eucalyptus is an open-source software platform that provides IaaS and enables on-premise private clouds. It uses existing infrastructure to create a scalable, secure web services layer for compute, network and storage. The architecture of Eucalyptus includes a Cloud Controller, Cluster Controllers, Storage Controller, and Node Controllers that manage VM execution and network scheduling. Eucalyptus can dynamically scale resources based on application workloads. The document discusses using Ubuntu 12.04 on the Eucalyptus front-end and Xen as the underlying hypervisor on backend nodes.
Provides a simple and unambiguous taxonomy of three service models
- Software as a service (SaaS)
- Platform as a service (PaaS)
- Infrastructure as a service (IaaS)
(Private cloud, Community cloud, Public cloud, and Hybrid cloud)
One can Study the key concept of Virtualization, its types, why Virtualization and what are the use cases and Benefits of Virtualization and example of Virtualization.
On-demand computing refers to a delivery model where computing resources are made available to users as needed. These resources can be maintained within a user's enterprise or provided by a cloud service provider, in which case it is referred to as cloud computing. Effective use of cloud computing requires properly provisioning resources to avoid over-provisioning, which wastes money, and under-provisioning, which hurts performance. Efficient resource provisioning in the cloud is challenging due to the variety of VM types, pricing models, demand and cost uncertainties, and the need to balance multiple objectives like cost and quality of service.
There are 5 levels of virtualization implementation:
1. Instruction Set Architecture Level which uses emulation to run inherited code on different hardware.
2. Hardware Abstraction Level which uses a hypervisor to virtualize hardware components and allow multiple users to use the same hardware simultaneously.
3. Operating System Level which creates an isolated container on the physical server that functions like a virtual server.
4. Library Level which uses API hooks to control communication between applications and the system.
5. Application Level which virtualizes only a single application rather than an entire platform.
- Substitution techniques involve replacing the letters of plaintext with other letters, numbers or symbols. The main substitution techniques are Caesar cipher, monoalphabetic cipher, Playfair cipher and Hill cipher.
- The Caesar cipher replaces each letter with the letter three positions down the alphabet. The monoalphabetic cipher uses a single alphabetic key for the entire message. The Playfair cipher encrypts pairs of letters based on a 5x5 grid generated from a keyword. The Hill cipher encrypts blocks of letters as numerical values using a matrix-based approach.
This document provides an overview of virtual machines. It defines a virtual machine as a software implementation of a machine that executes programs like physical hardware. There are two main types: system virtual machines which provide a complete OS environment, and process virtual machines which provide a platform-independent programming environment. Popular virtual machine software discussed includes VMware Workstation, Xen, VirtualBox, and Citrix. VMware Workstation allows multiple operating systems to run simultaneously on a single PC without restarting. Xen is an open-source virtual machine monitor that allows multiple guest operating systems to run concurrently on the same hardware. It has a three-layer architecture consisting of a virtual machine layer, hypervisor layer, and hardware/physical layer.
Cloud computing allows users to access virtual hardware, software, platforms, and services on an as-needed basis without large upfront costs or commitments. This transforms computing into a utility that can be easily provisioned and composed. The long-term vision is for an open global marketplace where IT services are freely traded like utilities, lowering barriers and allowing flexible access to resources and software for all users.
Cloud computing is the emerging trend in todays world. Cloud computing is not a separate technology, it is platform which provides platform as a service, Infrastructure as a service and Software as a service. The most important thing with cloud is that we hire everything from a third party or store our important datas in a third parties place .Here comes the major issue of how our datas are secured. In this paper, we discuss about how to protect our datas in the cloud with various cryptographic techniques. Padmapriya I | Ragini H "Cloud Cryptography" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-2 , February 2019, URL: https://www.ijtsrd.com/papers/ijtsrd21547.pdf
Paper URL: https://www.ijtsrd.com/computer-science/computer-network/21547/cloud-cryptography/padmapriya-i
Symmetric encryption uses a shared secret key between the sender and receiver to encrypt and decrypt messages. It is faster than asymmetric encryption but requires secure key exchange. Asymmetric encryption uses separate public and private keys, where the public key is used to encrypt and the private key decrypts, allowing secure communication without pre-shared keys. Common symmetric algorithms are AES and DES, while asymmetric algorithms include RSA, Diffie-Hellman, and ECDSA.
OpenNebulaConf2017EU: IPP Cloud by Jimmy Goffaux, IPPONOpenNebula Project
This document summarizes a demo of using Terraform to provision resources on an OpenNebula infrastructure. It describes the OpenNebula architecture which includes 400 VM instances across 7 nodes with 3TB of RAM, 250 cores, and a CephFS datastore. It also provides links to two Git repositories - one for an OpenNebula API and one for a Terraform provider that uses the API - that can be used to try provisioning VMs, templates, networks and more via Terraform.
Cloud Computing Architecture with Open Nebula - HPC Cloud Use Cases - NASA A...Ignacio M. Llorente
OpenNebula is a fully open-source cloud management platform, with excellent performance and scalability to manage tens of thousands of virtual machines, and with the most advanced functionality for building virtualized enterprise data centers and private cloud infrastructures. OpenNebula is the result of many years of research and development in efficient and scalable management of virtual machines on large-scale distributed infrastructures. Its innovative features have been developed to address the requirements of business use cases from leading companies in the context of flagship international projects in cloud computing. OpenNebula is being used by many supercomputing and leading research centers to build HPC and science clouds for hosting virtualized computational environments, such as batch farms and computing clusters, or for providing users with new "HPC as a service" resource provisioning models. The talk describes how to design a cloud architecture with OpenNebula and its innovative features to enable the execution of flexible and elastic cluster and high performance computing services on demand while reducing the associated cost of building the datacenter infrastructure.
Cloud computing has several key characteristics that provide benefits to both consumers and providers of cloud services. These characteristics include on-demand access to resources, no upfront commitments, simplified scalability, efficient allocation of resources, and energy efficiency. The essential characteristics of cloud computing that define its nature include on-demand self-service, broad network access, resource pooling, rapid elasticity, and measured services.
Parallel and distributed computing allows problems to be broken into discrete parts that can be solved simultaneously. This approach utilizes multiple processors that work concurrently on different parts of the problem. There are several types of parallel architectures depending on how instructions and data are distributed across processors. Shared memory systems give all processors access to a common memory space while distributed memory assigns private memory to each processor requiring explicit data transfer. Large-scale systems may combine these approaches into hybrid designs. Distributed systems extend parallelism across a network and provide users with a single, integrated view of geographically dispersed resources and computers. Key challenges for distributed systems include transparency, scalability, fault tolerance and concurrency.
Cloud Computing offers an on-demand and scalable access to a shared pool of resources hosted in a data center at providers’ site. It reduces the overheads of up-front investments and financial risks for the end-user. Regardless of the fact that cloud computing offers great advantages to the end users, there are several challenging issues that are mandatory to be addressed.
This document provides an overview of cluster computing. It defines a cluster as a group of loosely coupled computers that work together closely to function as a single computer. Clusters improve speed and reliability over a single computer and are more cost-effective. Each node has its own operating system, memory, and sometimes file system. Programs use message passing to transfer data and execution between nodes. Clusters can provide low-cost parallel processing for applications that can be distributed. The document discusses cluster architecture, components, applications, and compares clusters to grids and cloud computing.
Memory virtualization uses a portion of a disk drive as an extension of main memory. It divides both main memory and virtual memory into pages of equal size. Only needed pages reside in memory at a time, while unnecessary pages are stored on disk. When memory runs low, pages are written to the disk swap file as virtual memory. This allows larger programs to run in less physical RAM by swapping pages between disk and memory as needed.
The document discusses different types of virtualization including hardware, network, storage, memory, software, data, and desktop virtualization. Hardware virtualization includes full, para, and partial virtualization. Network virtualization includes internal and external virtualization. Storage virtualization includes block and file virtualization. Memory virtualization enhances performance through shared, distributed, or networked memory that acts as an extension of main memory. Software virtualization allows guest operating systems to run virtually. Data virtualization manipulates data without technical details. Desktop virtualization provides remote access to work from any location for flexibility and data security.
4.1Introduction
- Potential Threats and Attacks on Computer System
- Confinement Problems
- Design Issues in Building Secure Distributed Systems
4.2 Cryptography
- Symmetric Cryptosystem Algorithm: DES
- Asymmetric Cryptosystem
4.3 Secure Channels
- Authentication
- Message Integrity and Confidentiality
- Secure Group Communication
4.4 Access Control
- General Issues
- Firewalls
- Secure Mobile Code
4.5 Security Management
- Key Management
- Issues in Key Distribution
- Secure Group Management
- Authorization Management
This document discusses deploying infrastructure as a service (IaaS) using Eucalyptus. Eucalyptus is an open-source software platform that provides IaaS and enables on-premise private clouds. It uses existing infrastructure to create a scalable, secure web services layer for compute, network and storage. The architecture of Eucalyptus includes a Cloud Controller, Cluster Controllers, Storage Controller, and Node Controllers that manage VM execution and network scheduling. Eucalyptus can dynamically scale resources based on application workloads. The document discusses using Ubuntu 12.04 on the Eucalyptus front-end and Xen as the underlying hypervisor on backend nodes.
Provides a simple and unambiguous taxonomy of three service models
- Software as a service (SaaS)
- Platform as a service (PaaS)
- Infrastructure as a service (IaaS)
(Private cloud, Community cloud, Public cloud, and Hybrid cloud)
One can Study the key concept of Virtualization, its types, why Virtualization and what are the use cases and Benefits of Virtualization and example of Virtualization.
On-demand computing refers to a delivery model where computing resources are made available to users as needed. These resources can be maintained within a user's enterprise or provided by a cloud service provider, in which case it is referred to as cloud computing. Effective use of cloud computing requires properly provisioning resources to avoid over-provisioning, which wastes money, and under-provisioning, which hurts performance. Efficient resource provisioning in the cloud is challenging due to the variety of VM types, pricing models, demand and cost uncertainties, and the need to balance multiple objectives like cost and quality of service.
There are 5 levels of virtualization implementation:
1. Instruction Set Architecture Level which uses emulation to run inherited code on different hardware.
2. Hardware Abstraction Level which uses a hypervisor to virtualize hardware components and allow multiple users to use the same hardware simultaneously.
3. Operating System Level which creates an isolated container on the physical server that functions like a virtual server.
4. Library Level which uses API hooks to control communication between applications and the system.
5. Application Level which virtualizes only a single application rather than an entire platform.
- Substitution techniques involve replacing the letters of plaintext with other letters, numbers or symbols. The main substitution techniques are Caesar cipher, monoalphabetic cipher, Playfair cipher and Hill cipher.
- The Caesar cipher replaces each letter with the letter three positions down the alphabet. The monoalphabetic cipher uses a single alphabetic key for the entire message. The Playfair cipher encrypts pairs of letters based on a 5x5 grid generated from a keyword. The Hill cipher encrypts blocks of letters as numerical values using a matrix-based approach.
This document provides an overview of virtual machines. It defines a virtual machine as a software implementation of a machine that executes programs like physical hardware. There are two main types: system virtual machines which provide a complete OS environment, and process virtual machines which provide a platform-independent programming environment. Popular virtual machine software discussed includes VMware Workstation, Xen, VirtualBox, and Citrix. VMware Workstation allows multiple operating systems to run simultaneously on a single PC without restarting. Xen is an open-source virtual machine monitor that allows multiple guest operating systems to run concurrently on the same hardware. It has a three-layer architecture consisting of a virtual machine layer, hypervisor layer, and hardware/physical layer.
Cloud computing allows users to access virtual hardware, software, platforms, and services on an as-needed basis without large upfront costs or commitments. This transforms computing into a utility that can be easily provisioned and composed. The long-term vision is for an open global marketplace where IT services are freely traded like utilities, lowering barriers and allowing flexible access to resources and software for all users.
Cloud computing is the emerging trend in todays world. Cloud computing is not a separate technology, it is platform which provides platform as a service, Infrastructure as a service and Software as a service. The most important thing with cloud is that we hire everything from a third party or store our important datas in a third parties place .Here comes the major issue of how our datas are secured. In this paper, we discuss about how to protect our datas in the cloud with various cryptographic techniques. Padmapriya I | Ragini H "Cloud Cryptography" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-2 , February 2019, URL: https://www.ijtsrd.com/papers/ijtsrd21547.pdf
Paper URL: https://www.ijtsrd.com/computer-science/computer-network/21547/cloud-cryptography/padmapriya-i
Symmetric encryption uses a shared secret key between the sender and receiver to encrypt and decrypt messages. It is faster than asymmetric encryption but requires secure key exchange. Asymmetric encryption uses separate public and private keys, where the public key is used to encrypt and the private key decrypts, allowing secure communication without pre-shared keys. Common symmetric algorithms are AES and DES, while asymmetric algorithms include RSA, Diffie-Hellman, and ECDSA.
OpenNebulaConf2017EU: IPP Cloud by Jimmy Goffaux, IPPONOpenNebula Project
This document summarizes a demo of using Terraform to provision resources on an OpenNebula infrastructure. It describes the OpenNebula architecture which includes 400 VM instances across 7 nodes with 3TB of RAM, 250 cores, and a CephFS datastore. It also provides links to two Git repositories - one for an OpenNebula API and one for a Terraform provider that uses the API - that can be used to try provisioning VMs, templates, networks and more via Terraform.
Cloud Computing Architecture with Open Nebula - HPC Cloud Use Cases - NASA A...Ignacio M. Llorente
OpenNebula is a fully open-source cloud management platform, with excellent performance and scalability to manage tens of thousands of virtual machines, and with the most advanced functionality for building virtualized enterprise data centers and private cloud infrastructures. OpenNebula is the result of many years of research and development in efficient and scalable management of virtual machines on large-scale distributed infrastructures. Its innovative features have been developed to address the requirements of business use cases from leading companies in the context of flagship international projects in cloud computing. OpenNebula is being used by many supercomputing and leading research centers to build HPC and science clouds for hosting virtualized computational environments, such as batch farms and computing clusters, or for providing users with new "HPC as a service" resource provisioning models. The talk describes how to design a cloud architecture with OpenNebula and its innovative features to enable the execution of flexible and elastic cluster and high performance computing services on demand while reducing the associated cost of building the datacenter infrastructure.
OpenNebulaConf2017EU: Alternative Context for Windows by Paul Batchelor, Blac...OpenNebula Project
This document discusses alternative approaches to contextualization for Windows virtual machines. It notes issues with the current approach using context.ps1, which requires reboots and has no mechanism for automatic Active Directory domain joining. The document proposes using Unattend.xml, which allows Windows to be configured during initial setup without reboots. It describes a method to dynamically generate Unattend.xml by calling a script via the OpenNebula FILES attribute, replacing VM parameters. Testing showed the Unattend.xml approach boosted a Windows VM from a 7 minute boot time to 3 minutes and 30 seconds without additional reboots.
OpenNebula is an open-source cloud computing tool for managing virtualized infrastructure in a data center. It allows for both private and hybrid cloud deployments. The presentation provided an overview of OpenNebula's architecture and components, how to develop drivers to integrate different technologies, and ways to interact programmatically through APIs and scripting. It also discussed how OpenNebula is used by hosting companies, technology providers, and research organizations to deploy cloud services.
O documento descreve os métodos e procedimentos para instalação e configuração do OpenNebula, incluindo a instalação nos nós front-end e de hospedagem, compartilhamento de armazenamento, configuração de serviços e criação de máquinas virtuais.
Rudder manages the configuration of all systems continuously every 5 minutes. To interface OpenNebula VMs with Rudder, install the Rudder agent on the VMs and add a configuration file to enable communication between the VM agents and Rudder server. Rudder then takes over configuration of the new VMs.
This document provides an overview of installing and using OpenNebula. It describes setting up a typical OpenNebula environment with multiple backends and a hypervisor. It then walks through installing OpenNebula on two nodes, configuring passwordless SSH, adding hosts, images, networks, templates, and instantiating VMs. It also covers basic VM actions, contextualization, permissions, groups, and the different views in OpenNebula. Finally, it introduces OneFlow for managing multi-tier applications and services, including templates, deployment strategies, scaling, and auto-scaling based on metrics and schedules.
This document provides an overview of cloud computing and the Eucalyptus platform. It defines cloud computing as a large-scale distributed computing paradigm that delivers dynamically scalable computing resources as a service over the Internet. It then describes Eucalyptus as an open-source software that implements cloud computing on computer clusters and is compatible with Amazon EC2. The document outlines the Eucalyptus cloud architecture including components like the Cloud Controller, Cluster Controller, Node Controller, Storage Controller, and Walrus storage. It provides examples of deploying data mining applications on Eucalyptus and Amazon EC2 clouds.
The life cycle of a virtual machine (VM) provisioning processHitesh Mohapatra
The life cycle of a virtual machine (VM) provisioning process includes the following stages:
Creation: The VM is created
Configuration: The VM is configured in a development environment
Allocation: Virtual resources are allocated
Exploitation and monitoring: The VM is used and its status is monitored
Elimination: The VM is eliminated
The document describes a survey of open source cloud architectures including Eucalyptus, OpenStack, CloudStack, and OpenNebula. It discusses installing each one and attempting to evaluate their performance. However, issues were encountered when trying to log into the virtual machine instances that prevented benchmarking. Specifically, incorrect passwords were used across all architectures despite trying standard passwords and different image files. The one exception was OpenNebula where checking a one_auth file resolved the issue.
This document discusses cloud computing concepts including cloud characteristics, architectural layers, infrastructure models, and virtualization. It focuses on the cloud ecosystem including cloud consumers, management, virtual infrastructure management using tools like OpenNebula, and virtual machine managers like Xen and KVM. OpenNebula is described as providing a unified view of virtual resources across platforms and managing VM lifecycles through orchestrating image, network, and hypervisor management.
comparative study of Cloud computing tools Aditya Trivedi
The document provides information on Nimbus, an open-source toolkit that focuses on providing Infrastructure-as-a-Service capabilities to the scientific community. It enables resource providers to build private and community IaaS clouds, and users to use IaaS clouds. It also enables developers to extend, experiment, and customize IaaS. The document then discusses OpenNebula, an open-source project aimed at building the industry standard open source cloud computing tool to manage the complexity and heterogeneity of distributed data center infrastructures. It was designed with principles of openness, adaptability, interoperability, stability, and to prevent vendor lock-in.
Virtualization, A Concept Implementation of CloudNishant Munjal
This presentation will guide through deploying virtualization in linux environment and get its access to another machine followed by virtualization concept.
Get superior performance with auto scalable e nlight managed cloudmanoharparakh
In the world of indefinite possibilities, we understand every computing need, each automation move and every single technology update. Every business is unique in its own way, so must be the Cloud Solution. Hence, we specially engineered an intelligent cloud computing architecture for your business. eNlight gives you the right cloud infrastructure, perfectly pooled resources and forever technical support to run your business enterprise dynamically.
This document provides an introduction to cloud computing. It defines cloud computing and discusses its key characteristics including elasticity, multi-tenancy, and utility computing. The document outlines the different types of cloud services including Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). It also discusses the technologies that enable cloud computing such as virtualization and containerization. The document uses examples like Amazon Web Services, Google Cloud, and OpenStack to illustrate cloud concepts.
Virtualization allows multiple operating systems and applications to run simultaneously on a single physical machine. It provides benefits such as running different operating systems, easier software installation through virtual appliances, testing and disaster recovery using snapshots, and infrastructure consolidation to reduce hardware costs. Virtualization works by allocating resources like memory, processing power, and storage to virtual machines through a hypervisor. Early virtualization technologies date back to the 1960s but it became widely adopted in the 2000s with advances in hypervisor software.
Virtual machine provisioning automates the process of deploying new virtual machines on physical servers in minutes rather than the days it previously took. It allocates computing resources to support the virtual machine. Virtual machine migration allows maintenance tasks to be completed in milliseconds rather than the lengthy downtime previously required. Together, provisioning and migration improve efficiency and flexibility while maintaining service availability and meeting service level agreements.
Virtual machine provisioning automates the process of deploying new virtual machines on physical servers in minutes rather than the days it previously took. It allocates computing resources to support the virtual machine. Virtual machine migration allows maintenance tasks to be completed in milliseconds rather than hours by live migrating virtual machines between physical servers. Together, provisioning and migration improve efficiency and flexibility while maintaining service availability and meeting service level agreements.
The document provides recommendations for books on cloud computing concepts and technologies. It then discusses the history and drivers of the Fourth Industrial Revolution powered by cloud, social, mobile, IoT, and AI technologies. The document defines cloud computing and discusses characteristics such as on-demand access to computing resources, utility computing models, and service delivery of infrastructure, platforms, and applications. It also outlines some major cloud platform providers including Eucalyptus, Nimbus, OpenNebula, and the CloudSim simulation framework.
Performance Evaluation and Tuning of Virtual Infrastructure Managers for (Micro) Virtual Network Functions
Virtualized Network Functions (VNFs) are emerging as the keystone of 5G network architectures: flexibility, agility, fast instantiation times, consolidation, Commercial Off The Shelf (COTS) hardware support and significant cost savings are fundamental for meeting the requirements of the new generation of mobile networks. In this paper we deal with the management of the virtual computing resources for the execution of Micro VNFs. This functionality is performed by the Virtual Infrastructure Manager (VIM) in the NFV MANagement and Orchestration (MANO) reference architecture. We discuss the VIM instantiation process and propose a generic reference model, starting from the analysis of two Open Source VIMs, namely OpenStack Nova and Nomad. We implemented a tuned version of the VIMs with the specific goal of reducing the duration of the instantiation process. We realized a performance comparison of the two VIMs, both considering the plain and the tuned versions. The tuned VIMs and the performance evaluation tools that we have employed are provided openly and can be downloaded from our repository.
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Wayland is revolutionizing the way we interact with graphical interfaces, offering a modern alternative to the X Window System. In this webinar, we’ll delve into the architecture and benefits of Wayland, including its streamlined design, enhanced performance, and improved security features.
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AgentExchange is Salesforce’s latest innovation, expanding upon the foundation of AppExchange by offering a centralized marketplace for AI-powered digital labor. Designed for Agentblazers, developers, and Salesforce admins, this platform enables the rapid development and deployment of AI agents across industries.
Email: [email protected]
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Societal challenges of AI: biases, multilinguism and sustainabilityJordi Cabot
Towards a fairer, inclusive and sustainable AI that works for everybody.
Reviewing the state of the art on these challenges and what we're doing at LIST to test current LLMs and help you select the one that works best for you
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Who Watches the Watchmen (SciFiDevCon 2025)Allon Mureinik
Tests, especially unit tests, are the developers’ superheroes. They allow us to mess around with our code and keep us safe.
We often trust them with the safety of our codebase, but how do we know that we should? How do we know that this trust is well-deserved?
Enter mutation testing – by intentionally injecting harmful mutations into our code and seeing if they are caught by the tests, we can evaluate the quality of the safety net they provide. By watching the watchmen, we can make sure our tests really protect us, and we aren’t just green-washing our IDEs to a false sense of security.
Talk from SciFiDevCon 2025
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Adobe Lightroom Classic is a desktop-based software application for editing and managing digital photos. It focuses on providing users with a powerful and comprehensive set of tools for organizing, editing, and processing their images on their computer. Unlike the newer Lightroom, which is cloud-based, Lightroom Classic stores photos locally on your computer and offers a more traditional workflow for professional photographers.
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Organization:
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Editing:
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Storage Location:
Lightroom Classic stores photos locally on your computer, while Lightroom stores them in the cloud.
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Those with extensive photo collections may prefer Lightroom Classic's local storage and robust organization features.
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Users who prefer a more traditional desktop workflow, with their original photos stored on their computer, will find Lightroom Classic a good fit.
Secure Test Infrastructure: The Backbone of Trustworthy Software DevelopmentShubham Joshi
A secure test infrastructure ensures that the testing process doesn’t become a gateway for vulnerabilities. By protecting test environments, data, and access points, organizations can confidently develop and deploy software without compromising user privacy or system integrity.
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Exceptional Behaviors: How Frequently Are They Tested? (AST 2025)Andre Hora
Exceptions allow developers to handle error cases expected to occur infrequently. Ideally, good test suites should test both normal and exceptional behaviors to catch more bugs and avoid regressions. While current research analyzes exceptions that propagate to tests, it does not explore other exceptions that do not reach the tests. In this paper, we provide an empirical study to explore how frequently exceptional behaviors are tested in real-world systems. We consider both exceptions that propagate to tests and the ones that do not reach the tests. For this purpose, we run an instrumented version of test suites, monitor their execution, and collect information about the exceptions raised at runtime. We analyze the test suites of 25 Python systems, covering 5,372 executed methods, 17.9M calls, and 1.4M raised exceptions. We find that 21.4% of the executed methods do raise exceptions at runtime. In methods that raise exceptions, on the median, 1 in 10 calls exercise exceptional behaviors. Close to 80% of the methods that raise exceptions do so infrequently, but about 20% raise exceptions more frequently. Finally, we provide implications for researchers and practitioners. We suggest developing novel tools to support exercising exceptional behaviors and refactoring expensive try/except blocks. We also call attention to the fact that exception-raising behaviors are not necessarily “abnormal” or rare.
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Adobe Illustrator is a powerful, professional-grade vector graphics software used for creating a wide range of designs, including logos, icons, illustrations, and more. Unlike raster graphics (like photos), which are made of pixels, vector graphics in Illustrator are defined by mathematical equations, allowing them to be scaled up or down infinitely without losing quality.
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This presentation explores code comprehension challenges in scientific programming based on a survey of 57 research scientists. It reveals that 57.9% of scientists have no formal training in writing readable code. Key findings highlight a "documentation paradox" where documentation is both the most common readability practice and the biggest challenge scientists face. The study identifies critical issues with naming conventions and code organization, noting that 100% of scientists agree readable code is essential for reproducible research. The research concludes with four key recommendations: expanding programming education for scientists, conducting targeted research on scientific code quality, developing specialized tools, and establishing clearer documentation guidelines for scientific software.
Presented at: The 33rd International Conference on Program Comprehension (ICPC '25)
Date of Conference: April 2025
Conference Location: Ottawa, Ontario, Canada
Preprint: https://arxiv.org/abs/2501.10037
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Adobe Master Collection CC (Creative Cloud) is a comprehensive subscription-based package that bundles virtually all of Adobe's creative software applications. It provides access to a wide range of tools for graphic design, video editing, web development, photography, and more. Essentially, it's a one-stop-shop for creatives needing a broad set of professional tools.
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Explaining GitHub Actions Failures with Large Language Models Challenges, In...ssuserb14185
GitHub Actions (GA) has become the de facto tool that developers use to automate software workflows, seamlessly building, testing, and deploying code. Yet when GA fails, it disrupts development, causing delays and driving up costs. Diagnosing failures becomes especially challenging because error logs are often long, complex and unstructured. Given these difficulties, this study explores the potential of large language models (LLMs) to generate correct, clear, concise, and actionable contextual descriptions (or summaries) for GA failures, focusing on developers’ perceptions of their feasibility and usefulness. Our results show that over 80% of developers rated LLM explanations positively in terms of correctness for simpler/small logs. Overall, our findings suggest that LLMs can feasibly assist developers in understanding common GA errors, thus, potentially reducing manual analysis. However, we also found that improved reasoning abilities are needed to support more complex CI/CD scenarios. For instance, less experienced developers tend to be more positive on the described context, while seasoned developers prefer concise summaries. Overall, our work offers key insights for researchers enhancing LLM reasoning, particularly in adapting explanations to user expertise.
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3. Abstract
• Eucalyptus, Nimbus & OpenNebula are major Open-Source
Cloud-Computing Software Platforms
• Manage the provisioning of virtual machines for a cloud
providing IaaS
• Commercial cloud services charge, by the hour, for CPU time
• It might be more cost effective for the organization to purchase
hardware to create its own private cloud.
• These software products are designed to allow an organization
to set up a private group of machines as their own cloud.
• These three frameworks represent three different points of
interest in the design space of this particular type of open-
source cloud.
4. Analysis
• We will discuss how these software frameworks act as
managers that stand in the middle of a number of other
software components.
• We will analyze how core decisions in the basic architecture and
overall structure of Eucalyptus, Nimbus and OpenNebula impact
the kind of settings and applications for which each framework
is most suitable.
• We will identify several opportunities for improving these
software stacks by identifying some of the challenges that are
common to all three.
5. The Cloud Computing Stack
• A quick overview of entire cloud computing software stack.
• In a generic open-source cloud computing system, we can
identify six basic components.
6. • First, we hardware and operating system that are on the various
physical machines in the system.
• The second component is the network. This includes the DNS,
DHCP and the subnet organization of the physical machines.
• The third component is the virtual machine hypervisor, (also
known as a Virtual Machine Monitor or VMM).
• The fourth component is an archive of VM disk images.
• The fifth component is the front-end for users.
• The last component is the cloud framework itself, where
Eucalyptus, OpenNebula and Nimbus are placed.
7. Eucalyptus
• EUCALYPTUS stands for Elastic Utility Computing Architecture
for Linking Your Program To Useful System.
• It is open source software that was developed by University of
California-Santa Barbara for Cloud Computing to implement
Infrastructure as a Service.
• Eucalyptus provide an EC2 -compatible cloud Computing
Platform and S3- compatible Cloud Storage thus its services are
available through EC2/S3 compatible APIs.
• The Eucalyptus system is composed of a 5 main components
interacting together; Client, Cloud Controller, Storage
Controller (Walrus), Cluster Controller and a Node Controller.
8. • Node Controller
• Is installed in each compute
node to control VM activities,
including the execution, inspe-
ction and termination of VM
instances.
• Cluster Controller
• Runs on 1 machine per cluster &
works as an intermediary betw-
een the cloud & node controller.
• Storage Controller
• Warlus is a component that provides storage services for storing virtual
machine images and user’s data.
• Cloud Controller
• It is the user’s entry point into the Eucalyptus system and only one instance
is run on the system. It provides users with a way managing the system.
9. • The cloud controller is built using the Enterprise service bus providing
decoupling from the services’ implementation.
• Client
• The client component provides the user with a way to access the
Eucalyptus system (cloud controller).
• Eucalyptus provides two interfaces;
• One is a WDSL which is a SOAP client interface similar to AWS EC2 interface
called euca2ools.
• Another interface is a HTTP query based interface.
10. Constructing a Virtual Machine:
1. A user uses the euca2ools front-end to request a VM.
2. The VM template disk image is pushed
to a compute node
3. This disk image is padded to the correct
size and packaged for use by the
hypervisor on the compute node.
4. The compute node sets up network bridging
to provide a virtual NIC with a virtual MAC.
5. On the head node the dhcp is set up with the
MAC/IP pair
6. VM is spawned on the VMM.
7. The user can now SSH directly into the VM.
11. Nimbus
• Nimbus is another open source IaaS implementation framework
which came online September 2005.
• Nimbus allows a client to lease remote resources by deploying
virtual machines (VMs) on those resources and configuring
them to represent an environment desired by the user.
• It was formerly known as the "Virtual Workspace Service" (VWS)
but the "workspace service" is technically just one the
components in the software collection.
• Nimbus was designed with the goal of turning clusters into
clouds mainly to be used in scientific applications.
12. System Architecture And Design
• The design of Nimbus which consists of a number of components
based on the web service technology:
1. Workspace Service
• Allows clients to manage and administer VMs by providing to two interfaces;
1. One interface is based on the web service resource framework (WSRF)
2. The other is based on EC2 WSDL.
13. 2. Workspace Resource Manager
• Implements VM instance creation on a site and management.
3. Workspace Pilot
• Provides virtualization with significant changes to the site configurations.
4. Workspace Control
• Implements VM instance management such as start, stop and pause VM. It also
provides image management and sets up networks and provides IP assignment.
5. Context Broker
• Allows clients coordinate large virtual cluster launches automatically and repeatedly.
6. Workspace Client
• A complex client that provides full access to the workspace service functionality.
7. Cloud Client
• A simpler client providing access to selected functionalities in the workspace service.
8. Storage Service
• Cumulus is a web service providing users with storage capabilities to store images
and works in conjunction with GridFTP.
14. Constructing A Virtual Machine:
1. A user uses cloud-client to request a VM.
2. Nimbus will SSH into a compute node.
3. The VM template disk image is pushed to the
compute node.
4. On the compute node, the disk image is
padded to the correct size and configured.
5. The compute node sets up network bridging
to provide a virtual NIC with a virtual MAC.
6. A dhcp server on the compute node is
configured with a MAC/IP pair.
7. VM is spawned on the VMM.
8. The user can now SSH directly into the VM.
15. OpenNebula
• OpenNebula tends to a greater level of centralization and
customizability (especially for end-users).
• The idea of OpenNebula is a pure private cloud, in which users
actually log into the head node to access cloud functions.
• OpenNebula, by default, uses a shared file system, typically NFS, for
all disk images files and all files for actually running the OpenNebula
functions.
• In order to spawn a VM, the user provides a configuration file
containing parameters which would be fed into the VMM command
line. This allows for memory, processor, network and disk resources
to be requested for essentially any configuration.
• OpenNebula is also very centralized, especially in its default
16. Constructing A Virtual Machine
1. A user uses ssh to login to the head node.
2. The user uses the onevm command to request a VM.
3. The VM template disk image is copied and a copy
is padded to the correct size and configuration within
the NFS directory on the head node.
4. The one process on the head node uses ssh to log into a
compute node.
5. The compute node sets up network bridging to provide a
virtual NIC with a virtual MAC.
6. Files needed by the VMM on the compute node will be
pulled to the compute node via the NFS.
7. VM is spawned on the VMM.
8. The user can now SSH directly into the VM.
17. SUMMARY
Eucalyptus OpenNebula Nimbus
Philosophy Mimic Amazon EC2 Private, highly
customizable cloud
Cloud resources
tailored to scientific
researchers
Customizability Some for admin,
less for user
Basically everything Many parts except
for image storage
and globus
credentials
DHCP On cluster controller Variable On individual
compute node
Internal Security Tight. Root required
for many things.
Looser, but can be
made more tight if
needed.
Fairly tight, unless
deploying a fully
private cloud.
User Security Users are given
custom credentials
via a web interface
User logs into head Users x509
credential is
registered with
cloud
An Ideal Setting Large group of Smaller group of Deploy for less to