scholarly journals Automatic Backup System for Virtualization Environment

2014 ◽  
Vol 2 (1) ◽  
Author(s):  
Idris Winarno ◽  
Muzaki Nurus Sani
Keyword(s):  
Data Storage ◽  
Virtual Machine ◽  
Data Center ◽  
Virtual Machines ◽  
Test Results ◽  
Web Based ◽  
Scheduling System ◽  
Backup System ◽  
Virtualization Technology ◽  
Server Problem

Virtualization is a technology lately much discussed and considered as the proper way to cut costs in the construction of a data center. One example of the implementation of virtualization technologies is to using VMware. Another tools for virtualization are Xen and OpenVZ, but VMware is more flexible than Xen or OpenVZ because VMware can run a variety of operating systems. Although it has the advantage, virtualization technology also has a vital weakness, virtualization technologies could be analogous by putting all the eggs in a basket. This means that if the master server problem, all systems inside the virtual machine can not be used. However, it can be anticipated by provide backup facilities that run continually and automatically. VMware itself has had an application to backup/replicate virtual machines. However, that application is not free yet.This research has been design and creates a web-based software forbacking up virtual machines on VMware. So it made easier for users and admins to perform periodic backups of virtual machines. From the test results has been done, it can be seen that used disk type thin or zeroed thick make process backup faster, system can’t work well when virtual machine has snapshot, scheduling system and restoring system has worked well, physical ability data storage influence system.Keywords: Virtual machine, virtualization, Vmware, Backup, Data Center.

Virtual Machine Placement in IaaS Cloud

2017 ◽  
pp. 130-158
Author(s):  
Prateek Khandelwal ◽  
Gaurav Somani
Keyword(s):  
Customer Satisfaction ◽  
Virtual Machine ◽  
Data Center ◽  
Virtual Machines ◽  
Virtual Machine Placement ◽  
Attractive Alternative ◽  
Operational Cost ◽  
Trade Offs ◽  
Crucial Component

A crucial component of providing services over virtual machines to users is how the provider places those virtual machines on physical servers. While one strategy can offer an increased performance for the virtual machine, and hence customer satisfaction, another can offer increased savings for the cloud operator. Both have their trade-offs. Also, with increasing costs of electricity, and given the fact that the major component of the operational cost of a data center is that of powering it, green strategies also offer an attractive alternative. In this chapter, the authors will look into what kind of different placement strategies have been developed, and the kind of advantages they purport to offer.

scholarly journals Proposing a load balancing algorithm with an integrative approach to reduce response time and service process time in data centers

2019 ◽  
Vol 16 (4) ◽  
pp. 627-637
Author(s):  
Sanaz Hosseinzadeh Sabeti ◽  
Maryam Mollabgher
Keyword(s):  
Load Balancing ◽  
Data Processing ◽  
Response Time ◽  
Virtual Machine ◽  
Data Center ◽  
Processing Time ◽  
Data Centers ◽  
Virtual Machines ◽  
Overall Response ◽  
Load Balancing Algorithm

Goal: Load balancing policies often map workloads on virtual machines, and are being sought to achieve their goals by creating an almost equal level of workload on any virtual machine. In this research, a hybrid load balancing algorithm is proposed with the aim of reducing response time and processing time. Design / Methodology / Approach: The proposed algorithm performs load balancing using a table including the status indicators of virtual machines and the task list allocated to each virtual machine. The evaluation results of response time and processing time in data centers from four algorithms, ESCE, Throttled, Round Robin and the proposed algorithm is done. Results: The overall response time and data processing time in the proposed algorithm data center are shorter than other algorithms and improve the response time and data processing time in the data center. The results of the overall response time for all algorithms show that the response time of the proposed algorithm is 12.28%, compared to the Round Robin algorithm, 9.1% compared to the Throttled algorithm, and 4.86% of the ESCE algorithm. Limitations of the investigation: Due to time and technical limitations, load balancing has not been achieved with more goals, such as lowering costs and increasing productivity. Practical implications: The implementation of a hybrid load factor policy can improve the response time and processing time. The use of load balancing will cause the traffic load between virtual machines to be properly distributed and prevent bottlenecks. This will be effective in increasing customer responsiveness. And finally, improving response time increases the satisfaction of cloud users and increases the productivity of computing resources. Originality/Value: This research can be effective in optimizing the existing algorithms and will take a step towards further research in this regard.

scholarly journals Angleško-slovenski glosar virtualizacijske terminologije: usklajevanje tehničnega, terminološkega in organizacijskega dela

2017 ◽  
Vol 4 (1) ◽  
pp. 97-117
Author(s):  
Marta Štimec ◽  
Matija Cankar
Keyword(s):  
Data Storage ◽  
Virtual Machines ◽  
Rapid Development ◽  
Graphic User Interface ◽  
Translation Memory ◽  
Public And Private ◽  
Virtualization Technology ◽  
Online Encyclopedia ◽  
Resource Consolidation ◽  
Advanced Version

With the growing adoption of using virtual machines over physical hosts as a form of resource consolidation, The English-Slovene Glossary of Virtualization-related Terms encompassing management of virtual machines, cloud orchestration and data storage seemed like the next logical step.The Glossary of Virtualization-related Terms has been translated into Slovene and reviewed by experts in the fields of cloud computing, virtualization technologies and linguists. Close to 6000 terms had been localized for the Slovene market, using the advanced version of Poedit application – the editor for translating apps and websites. PoEdit automatically displays translation equivalents either from its own base (built-in translation memory) or from the base of previously translated words and phrases, which had been created and offered as opensource by other users. Based on these, it makes suggestions and, over time, learns enough to fill in frequently used strings. The translated text was then imported into its original page location – the Graphic User Interface (visible on buttons on the dashboard) of the customized ManageIQ Enterprise Virtualization Manager (EVM) software used by administrators of public and private clouds. Hence the main criterion was brevity and precision in transfering meaning across languages. This is where we encountered most problems – neologisms and existing words that acquire new meaning as a result of rapid development of virtualization technology. To avoid merely adding a suffix while the core of the word remains the same in Slovene (e.g. tenant, tenant-ov) and also to encourage further additions, comments or suggested changes the glossary has been made available on Wikipedia, the online encyclopedia.

scholarly journals LOAD BALANCING IN CLOUD ENVIRONMENT: A REVIEW

2016 ◽  
Vol 15 (8) ◽  
pp. 6986-6990
Author(s):  
Sheenam Kamboj ◽  
Mr. Navtej Singh Ghumman
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Virtual Machine ◽  
Virtual Machines ◽  
Computing Platform ◽  
Side Load ◽  
Virtualization Technology ◽  
Cloud Computing Platform ◽  
Demand Changes

An essential role of cloud computing platform is to dynamically balance the load among the different servers in order to improve resource utilization and to avoid hotspots. Load balancing (LB) is done on both sides i.e. on provider as well as on consumer side. On provider side, load balancing is the problem of allocating virtual machines to servers at runtime. Virtual Machine need to be reassigned so that servers do not get overloaded as demand changes. On consumer side application load can be balanced which provides efficiency to the consumers. On cloud computing platform, load balancing of the entire system can be dynamically handled by  using virtualization technology through which itÂbecomes possible to remap virtual machine and physical resources according to  the change in load. However, in order to improve performance, the virtual machines have to fully utilize its resources and services by adapting to computing environment dynamically. The load balancing with proper allocation of resources must be guaranteed in order to improve resource utility.

Data Center Enhancement by Server Resources Utilization

2021 ◽  
Vol 39 (1B) ◽  
pp. 203-208
Author(s):  
Haider A. Ghanem ◽  
Rana F. Ghani ◽  
Maha J. Abbas
Keyword(s):  
Cloud Computing ◽  
Power Consumption ◽  
Resource Utilization ◽  
Virtual Machine ◽  
Data Center ◽  
Data Centers ◽  
Virtual Machines ◽  
The Internet ◽  
Memory Resources

Data centers are the main nerve of the Internet because of its hosting, storage, cloud computing and other services. All these services require a lot of work and resources, such as energy and cooling. The main problem is how to improve the work of data centers through increased resource utilization by using virtual host simulations and exploiting all server resources. In this paper, we have considered memory resources, where Virtual machines were distributed to hosts after comparing the virtual machines with the host from where the memory and putting the virtual machine on the appropriate host, this will reduce the host machines in the data centers and this will improve the performance of the data centers, in terms of power consumption and the number of servers used and cost.

Virtual Machine Migrating Algorithm Based on Genetic Algorithm in Cloud Data Center

2014 ◽  
Vol 513-517 ◽  
pp. 2031-2034
Author(s):  
Hui Zhang ◽  
Yong Liu
Keyword(s):  
Genetic Algorithm ◽  
Resource Utilization ◽  
Virtual Machine ◽  
Data Center ◽  
Virtual Machines ◽  
Heuristic Algorithms ◽  
Optimal Solution ◽  
Virtual Machine Migration ◽  
Cloud Data Center ◽  
Cloud Data

Virtual machine migration is an effective method to improve the resource utilization of cloud data center. The common migration methods use heuristic algorithms to allocation virtual machines, the solution results is easy to fall into local optimal solution. Therefore, an algorithm called Migrating algorithm based on Genetic Algorithm (MGA) is introduced in this paper, which roots from genetic evolution theory to achieve global optimal search in the map of virtual machines to target nodes, and improves the objective function of Genetic Algorithm by setting the resource utilization of virtual machine and target node as an input factor into the calculation process. There is a contrast between MGA, Single Threshold (ST) and Double Threshold (DT) through simulation experiments, the results show that the MGA can effectively reduce migrations times and the number of host machine used.

scholarly journals Optimized Virtual Machine Placement with Traffic-Aware Balancing in Data Center Networks

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Tao Chen ◽  
Xiaofeng Gao ◽  
Guihai Chen
Keyword(s):  
Virtual Machine ◽  
Heuristic Algorithm ◽  
Data Center ◽  
Virtual Machines ◽  
Virtual Machine Placement ◽  
Np Hard ◽  
Data Center Networks ◽  
Placement Problem ◽  
Placement Algorithm ◽  
Communication Locality

Virtualization has been an efficient method to fully utilize computing resources such as servers. The way of placing virtual machines (VMs) among a large pool of servers greatly affects the performance of data center networks (DCNs). As network resources have become a main bottleneck of the performance of DCNs, we concentrate on VM placement with Traffic-Aware Balancing to evenly utilize the links in DCNs. In this paper, we first proposed a Virtual Machine Placement Problem with Traffic-Aware Balancing (VMPPTB) and then proved it to be NP-hard and designed a Longest Processing Time Based Placement algorithm (LPTBP algorithm) to solve it. To take advantage of the communication locality, we proposed Locality-Aware Virtual Machine Placement Problem with Traffic-Aware Balancing (LVMPPTB), which is a multiobjective optimization problem of simultaneously minimizing the maximum number of VM partitions of requests and minimizing the maximum bandwidth occupancy on uplinks of Top of Rack (ToR) switches. We also proved it to be NP-hard and designed a heuristic algorithm (Least-Load First Based Placement algorithm, LLBP algorithm) to solve it. Through extensive simulations, the proposed heuristic algorithm is proven to significantly balance the bandwidth occupancy on uplinks of ToR switches, while keeping the number of VM partitions of each request small enough.

scholarly journals Secure Data Verification and Virtual Machine Monitoring

2018 ◽  
Vol 7 (4.36) ◽  
pp. 574
Author(s):  
P. V. Samuel Blessed Nayagam ◽  
A. Shajin Nargunam
Keyword(s):  
Access Control ◽  
Virtual Machine ◽  
Virtual Machines ◽  
Test Results ◽  
Data Verification ◽  
Machine Monitoring ◽  
Secure Data ◽  
Cloud Condition ◽  
Multi Cloud

Powerfully configurable virtualized assets make the physical area of the information and process autonomous of its portrayal and the clients have no influence over the physical arrangement of information and running procedure. In a multi-cloud condition the layer of deliberation between the physical equipment and virtualized frameworks gives a great way to convey cost reserve funds through server union and also expanded operational productivity and adaptability. This additional usefulness presents a virtualization layer that it turns into a chance of assault for the facilitated virtual administrations. The proposed access control show ensures virtual machines by receiving access control at various layers. The information shading plan help to secure the virtualized information utilized in the virtual machines. The information confirmation structure, which gives a grouping of trust wipes out the untrusted special virtual machines, and additionally utilize the confided in processing standards to guarantee the respectability of the checking condition. Safeguarding security plot ceaselessly screens the working and trade of information between the virtual machine. The test results demonstrate that this plan can viably counteract virtual machine escape without influencing the general productivity of the framework. 

scholarly journals Role of Data Hiding Techniques for Detection of Virtual Disks in Cloud Environment

2020 ◽  
Vol 8 (5) ◽  
pp. 151-156
Keyword(s):  
Cloud Computing ◽  
Virtual Machine ◽  
Data Hiding ◽  
Service Provider ◽  
Data Center ◽  
Virtual Machines ◽  
Cloud Service ◽  
Cloud Environment ◽  
Complete Control ◽  
Public Data

In today's era, cloud computing is very popular and the most widly used technique to store the data. As we know more than 75% of the data that is used in internet services and applications is being stored on the maximum cloud only. Where our data is stored in the cloud, it is called data center, there are two important roles in cloud computing technology, one is cloud customer and the other is cloud service provider. The complete control and monitoring at the public data center is of the service provider itself, the user is kept away from the information of the location of the data center and its access credentials. This means that the user has absolutely no information about the virtual machine hard disk, and their access locations. Whenever any forensic inquiry comes in the cloud environment, the Investigator and forensic expert first have to find out about the virtual machine disk and its location in the cloud, which is a very challenging and difficult task in the cloud environment. In this paper we have developed a new process that detects virtual machines using data hiding techniques. To prove this new algorithm, we have performed an experiment using Oracle VirtualBox 6.0 on OpenSUSE virtual machine.

scholarly journals EeadSelfCloud: Energy Efficient Adaptive Depth Self Cloud Mechanism for VM Migration in Data Centers

2019 ◽  
Vol 8 (10) ◽  
pp. 2236-2244
Keyword(s):  
Cloud Computing ◽  
Virtual Machine ◽  
Data Center ◽  
Data Centers ◽  
Virtual Machines ◽  
Power Saving ◽  
Human Beings ◽  
Hop Count ◽  
Vm Migration ◽  
Self Organizing

Cloud computing, with its great potential in low cost and demanding services, is a good computing platform. Modern data centers for cloud computing are facing the difficulty of consistently increasing complexity because of the expanding quantity of clients and their enlarging resource demands. A great deal of efforts are currently focused on giving the cloud framework with autonomic behavior , so it can take decision about virtual machine (VM) management over the datacenter without intervention of human beings. Most of the self-organizing solutions results in eager migration, which attempts to diminish the amount of working servers virtual machines. These self-organizing resolution produce needless migration due to unpredictable workload. So also it consume huge amounts of electrical energy during unnecessary migration process. To overcome this issue, this project develop one novel VM migration scheme called eeadSelfCloud. The proposed schema is used to change the virtual machine in a cloud center that requires a lot of factors, such as basic requirements for resources during virtual machine setup, dynamic resource allocation, top software loading, software execution, and power saving at the Data Center. Data Center Utilization, Average Node Utilization, Request Rejection Ration, Number of Hop Count and Power Consumption are taken as constraint for measuring the proposed approach. The analysis report depicted that the proposed approach performs best than the other existing approaches.

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