scholarly journals Controlling Multiple Virtual Machines in Computer Classrooms

2015 ◽  
Vol 63 (2) ◽  
pp. 683-691
Author(s):  
Petr Zach ◽  
Martin Pokorný ◽  
Jiří Balej ◽  
Michal Šturma
Keyword(s):  
Classroom Management ◽  
Virtual Machine ◽  
Operating Systems ◽  
Virtual Machines ◽  
Process Automation ◽  
Remote Server ◽  
Computer Classroom ◽  
Computer Classrooms ◽  
Software Updates ◽  
Process Diagrams

A management of computer classroom is undoubtedly a difficult task for the administrator which has to prepare virtual operating systems for education. It is quite common that lectors need to edit the particular machine during the semester, and that is the case where the main problems can appear. The process of changes deployment is not just very time-consuming but during it a virtual machine inconsistency can appear. The main part of this paper focuses on system process diagrams and its pseudocode. At first, the machine is created on the remote server by lector or administrator. After a proper approval, the machine is able to be deployed. The lector then specifies the details about date, time and destinations of the virtual machine deployment. Once these details are approved, the virtual machine will be automatically deployed at the specified time. The automatic deployment includes also an initial configuration of the virtual machine at remote desktop and its post-install configuration (hostname, MAC address, etc.). Once all steps are completed, the process will be marked as succeed. We present an automatized solution which provides a possibility how to easily manage computer classroom with virtual operating systems. The proposed solution should deliver a greater flexibility, more reliability and faster deployment in comparison with the current solution used in our computer classroom. The proposal is also able to manipulate with already deployed machines for easy changes (e.g. software updates). The main advantage is the improvement of classroom management process automation.

scholarly journals Virtualized DB Clustering and Server Consolidation: It’s Implementation with a Live Case Study

2010 ◽  
pp. 266-270
Author(s):  
Ram Prasad Patnaik ◽  
Dambaru Dhara Nahak
Keyword(s):  
Operating System ◽  
Virtual Machine ◽  
Operating Systems ◽  
Virtual Machines ◽  
Computer Hardware ◽  
Tool Development ◽  
Single Application ◽  
Server Consolidation ◽  
Independent Operating System

Virtualization is a technology that transforms today’s powerful computer hardware, which was designed to run a single operating system and a single application, to run multiple virtual machine having independent operating system. Many times, we observes that the server resources been underutilized. Virtualization allows us to efficiently utilize the available resources on physical machine. In virtualization environment, different virtualized machines can have different host operating system (i.e. different versions windows, Linux, Solaris etc). The most important concept to understand in virtualization is that, the virtual machines operating systems are independent from physical server operating system. This paper is an attempt to illustrate and appreciate the concept of virtualization and its implementation by using a live case study which we have implemented for one of our leading ETL tool development for a client. Case study elaborates the implementation details about Virtualized DB Clustering and Server Consolidation.

scholarly journals Integration of Linux Containers in OpenStack: An Introspection

2018 ◽  
Vol 12 (3) ◽  
pp. 1094 ◽  
Author(s):  
Ashish Lingayat ◽  
Ranjana R. Badre ◽  
Anil Kumar Gupta
Keyword(s):  
Cloud Computing ◽  
Virtual Machine ◽  
Operating Systems ◽  
Virtual Machines ◽  
Cloud Provider ◽  
Storage Space ◽  
Computational Power ◽  
Management Tools ◽  
Additional Layer ◽  
Linux Containers

<p>In cloud computing, sharing of resources is supported using heavy weighted traditional virtualization techniques. Such techniques involve hypervisors to emulate hardware for creating virtual machines. The inclusion of an additional layer of hypervisor over host operating system depreciates the performance of the virtual machine. Recent evolution is a lightweight alternative to the virtual machine called containers which have gained<br />popularity among developers and administrators. Container Based virtualization has proven very efficient regarding performance, and many industries are now migrating their virtualized environment to run on Linux containers. Containers use host operating systems kernel and isolate each container by encapsulating them with their required services and packages. Linux kernel is very beneficial in implementing containers, which is the reason for the existence of Linux containers. Linux containers utilize less storage space and consume optimal computational power, giving a hike in performance. Having them integrated into the cloud surely benefits consumer and cloud provider. Many projects have extended their support in incorporating containers in the cloud. In this paper, we will discuss various Linux containers and their management tools along with cloud computing software, OpenStack, including projects undertaken by OpenStack for integrating containers in the cloud.</p>

Distance Aware VM allocation process to minimize energy consumption in cloud computing

2019 ◽  
Vol 12 ◽  
Author(s):  
Gurpreet Singh ◽  
Manish Mahajan ◽  
Rajni Mohana
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Energy Consumption ◽  
Virtual Machine ◽  
Virtual Machines ◽  
Research Work ◽  
Service Level Agreement ◽  
Service Level ◽  
Physical Machine ◽  
Allocation Process

BACKGROUND: Cloud computing is considered as an on-demand service resource with the applications towards data center on pay per user basis. For allocating the resources appropriately for the satisfaction of user needs, an effective and reliable resource allocation method is required. Because of the enhanced user demand, the allocation of resources has now considered as a complex and challenging task when a physical machine is overloaded, Virtual Machines share its load by utilizing the physical machine resources. Previous studies lack in energy consumption and time management while keeping the Virtual Machine at the different server in turned on state. AIM AND OBJECTIVE: The main aim of this research work is to propose an effective resource allocation scheme for allocating the Virtual Machine from an ad hoc sub server with Virtual Machines. EXECUTION MODEL: The execution of the research has been carried out into two sections, initially, the location of Virtual Machines and Physical Machine with the server has been taken place and subsequently, the cross-validation of allocation is addressed. For the sorting of Virtual Machines, Modified Best Fit Decreasing algorithm is used and Multi-Machine Job Scheduling is used while the placement process of jobs to an appropriate host. Artificial Neural Network as a classifier, has allocated jobs to the hosts. Measures, viz. Service Level Agreement violation and energy consumption are considered and fruitful results have been obtained with a 37.7 of reduction in energy consumption and 15% improvement in Service Level Agreement violation.

A Defense Mechanism Based on Improved Allocation Strategy of VMs Co-Resident Attack in Power Cloud Platform

2020 ◽  
Vol 13 ◽  
Author(s):  
Yuancheng Li ◽  
Pan Zhang ◽  
Daoxing Li ◽  
Jing Zeng
Keyword(s):  
Virtual Machine ◽  
Simulation Experiment ◽  
Virtual Machines ◽  
Defense Mechanism ◽  
Security Threats ◽  
Allocation Strategy ◽  
Cloud Platform ◽  
Deployment Strategy ◽  
Dbscan Algorithm ◽  
Maximum Minimum

Background: Cloud platform is widely used in electric power field. Virtual machine co-resident attack is one of the major security threats to the existing power cloud platform. Objective: This paper proposes a mechanism to defend virtual machine co-resident attack on power cloud platform. Method: Our defense mechanism uses the DBSCAN algorithm to classify and output the classification results through the random forest and uses improved virtual machine deployment strategy which combines the advantages of random round robin strategy and maximum/minimum resource strategy to deploy virtual machines. Results: we made a simulation experiment on power cloud platform of State Grid and verified the effectiveness of proposed defense deployment strategy. Conclusion: After the virtual machine deployment strategy is improved, the coverage of the virtual machine is remarkably reduced which proves that our defense mechanism achieves some effect of defending the virtual machine from virtual machine co-resident attack.

Virtual Machines Scheduling Algorithm Based on Multi-Objective Optimization in Cloud Computing

2014 ◽  
Vol 1046 ◽  
pp. 508-511
Author(s):  
Jian Rong Zhu ◽  
Yi Zhuang ◽  
Jing Li ◽  
Wei Zhu
Keyword(s):  
Cloud Computing ◽  
Energy Consumption ◽  
Virtual Machine ◽  
Virtual Machines ◽  
Scheduling Algorithm ◽  
Machine Scheduling ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Virtual Machine Scheduling ◽  
Set Up

How to reduce energy consumption while improving utility of datacenter is one of the key technologies in the cloud computing environment. In this paper, we use energy consumption and utility of data center as objective functions to set up a virtual machine scheduling model based on multi-objective optimization VMSA-MOP, and design a virtual machine scheduling algorithm based on NSGA-2 to solve the model. Experimental results show that compared with other virtual machine scheduling algorithms, our algorithm can obtain relatively optimal scheduling results.

scholarly journals Virtual Disks Performance Analysis Using Flexible I/O and Powerstat

2021 ◽  
Vol 9 (10) ◽  
pp. 267-296
Author(s):  
Pritam Patange
Keyword(s):  
Cloud Computing ◽  
Virtual Machine ◽  
Virtual Machines ◽  
Disk File ◽  
Virtual Machine Monitor ◽  
Image File ◽  
File Formats ◽  
Physical Infrastructure ◽  
Disk Image ◽  
The Impact

Abstract: Cloud computing has experienced significant growth in the recent years owing to the various advantages it provides such as 24/7 availability, quick provisioning of resources, easy scalability to name a few. Virtualization is the backbone of cloud computing. Virtual Machines (VMs) are created and executed by a software called Virtual Machine Monitor (VMM) or the hypervisor. It separates compute environments from the actual physical infrastructure. A disk image file representing a single virtual machine is created on the hypervisor’s file system. In this paper, we analysed the runtime performance of multiple different disk image file formats. The analysis comprises of four different parameters of performance namely- bandwidth, latency, input-output operations performed per second (IOPS) and power consumption. The impact of the hypervisor’s block and file sizes is also analysed for the different file formats. The paper aims to act as a reference for the reader in choosing the most appropriate disk file image format for their use case based on the performance comparisons made between different disk image file formats on two different hypervisors – KVM and VirtualBox. Keywords: Virtualization, Virtual disk formats, Cloud computing, fio, KVM, virt-manager, powerstat, VirtualBox.

scholarly journals Virtual Machine Selection Algorithm Based on User Requirements in Mobile Cloud Computing Environment

2018 ◽  
Vol 17 (2) ◽  
pp. 7335-7349
Author(s):  
Rashid Alakbarov
Keyword(s):  
Cloud Computing ◽  
Virtual Machine ◽  
Mobile Cloud Computing ◽  
Virtual Machines ◽  
Mobile User ◽  
Base Stations ◽  
Mobile Cloud ◽  
Software Applications ◽  
Wireless Metropolitan Area Networks ◽  
Cloud Technologies

The article analyzes the advantages of mobile cloud technologies and problems emerging during the use of those. The network infrastructure created based on cloudlets at the second level of mobile cloud computing with hierarchical structure is analyzed. At the same time, the article explores the issues of satisfaction of demand of mobile equipment for computing and memory resources by using these technologies. The article presents one solution for the allocation of mobile user requests in virtual machines created in cloudlets located near base stations of wireless metropolitan area networks (WMAN) in a balanced way by considering the technical capacity of those. Alongside, the article considers the solution of user problem during designated time and the issue of determining virtual machines satisfying other requirements. For this purpose, different characteristics of the stated problem, virtual machines, as well as communication channels between a user and virtual machines are considered. By using possible values determining the importance of cloudlets, conditions for loading software applications of a user to a virtual machine are explored and an appropriate method is proposed.

scholarly journals IPV4 and IPV6 based hybrid approach for spam and virus detection

2018 ◽  
Vol 7 (2.4) ◽  
pp. 147
Author(s):  
Swati Hira ◽  
Samir Ajani ◽  
Pratibha Kokardikar ◽  
Shubhangi Neware
Keyword(s):  
Open Source ◽  
Virtual Machine ◽  
Virtual Machines ◽  
Hybrid Approach ◽  
Virus Detection ◽  
Entry Point ◽  
Software Interface ◽  
Established Fact

The proposed email setup consist of multiple mail servers distributed at two levels to achieve desirable email access performance. It is a well-established fact that 99% of the emails received over internet are either spam or contained viruses and such emails can be dropped at the first entry point of the Network. Thus, the first level in the proposed architecture has been taken as an email gateway which is equipped with antivirus and anti-spam software. Spam assassion is an open source freeware software for filtering of the spam emails. Perl based spamassassion id to CPU and Memory hungry for heavily loaded server thus this new arrangement would then overcome the Problem of slow Email access for users by detaching spamassassion from email repository servers. The second level of the servers with email repositories for users all the email servers used in this implementation would be Linux X86 servers. Virtualization technique presents a software interface to virtual machines that is similar but not identical to that of the underlying hardware. First level is implemented in Virtual machine. So as to provide scalability, portability, migration and vendor independent. 

scholarly journals Energy Efficient Resource Allocation in Cloud Computing

2019 ◽  
Vol 8 (6S3) ◽  
pp. 2071-2074
Keyword(s):  
Virtual Machine ◽  
Service Provider ◽  
Physical System ◽  
Virtual Machines ◽  
Cloud Service ◽  
Cloud Environment ◽  
Cloud Service Provider ◽  
Host System ◽  
Physical Systems ◽  
Single Host

Cloud service provider in cloud environment will provide or provision resource based on demand from the user. The cloud service provider (CSP) will provide resources as and when required or demanded by the user for execution of the job on the cloud environment. The CSP will perform this in a static and dynamic manner. The CSP should also consider various other factors in order to provide the resources to the user, the prime among that will be the Service Level Agreement (SLA), which is normally signed by the user and cloud service provider during the inception phase of service. There are many algorithm which are used in order to allocate resources to the user in cloud environment. The algorithm which is proposed will be used to reduce the amount of energy utilized in performing various job execution in cloud environment. Here the energy utilized for execution of various jobs are taken into account by increasing the number of virtual machines that are used on a single physical host system. There is no thumb rule to calculate the number of virtual machines to be executed on a single host. The same can be derived by calculating the amount of space, speed required along with the time to execute the job on a virtual machine. Based up on this we can derive the number of Virtual machine on a single host system. There can be 10 virtual machines on a single system or even 20 number of virtual machines on single physical system. But if the same is calculated by the equation then the result will be exactly matching with the threshold capacity of the physical system[1]. If more number of physical systems are used to execute fewer virtual machines on each then the amount of energy consumed will be very high. So in order to reduce the energy consumption , the algorithm can be used will not only will help to calculate the number of virtual machines on single physical system , but also will help to reduce the energy as less number of physical systems will be in need[2].

scholarly journals Using a vision cognitive algorithm to schedule virtual machines

2014 ◽  
Vol 24 (3) ◽  
pp. 535-550 ◽  
Author(s):  
Jiaqi Zhao ◽  
Yousri Mhedheb ◽  
Jie Tao ◽  
Foued Jrad ◽  
Qinghuai Liu ◽  
...  
Keyword(s):  
Global Optimization ◽  
Energy Consumption ◽  
Virtual Machine ◽  
Optimization Problem ◽  
Virtual Machines ◽  
Scheduling Algorithm ◽  
Primary Concern ◽  
Global Optimization Problem ◽  
Vm Scheduling ◽  
Operation Cost

Abstract Scheduling virtual machines is a major research topic for cloud computing, because it directly influences the performance, the operation cost and the quality of services. A large cloud center is normally equipped with several hundred thousand physical machines. The mission of the scheduler is to select the best one to host a virtual machine. This is an NPhard global optimization problem with grand challenges for researchers. This work studies the Virtual Machine (VM) scheduling problem on the cloud. Our primary concern with VM scheduling is the energy consumption, because the largest part of a cloud center operation cost goes to the kilowatts used. We designed a scheduling algorithm that allocates an incoming virtual machine instance on the host machine, which results in the lowest energy consumption of the entire system. More specifically, we developed a new algorithm, called vision cognition, to solve the global optimization problem. This algorithm is inspired by the observation of how human eyes see directly the smallest/largest item without comparing them pairwisely. We theoretically proved that the algorithm works correctly and converges fast. Practically, we validated the novel algorithm, together with the scheduling concept, using a simulation approach. The adopted cloud simulator models different cloud infrastructures with various properties and detailed runtime information that can usually not be acquired from real clouds. The experimental results demonstrate the benefit of our approach in terms of reducing the cloud center energy consumption

Sign in / Sign up

Export Citation Format

Share Document