scholarly journals Secure mitigation and migration of virtual machines over hybrid cloud hypervisors infrastructure

2021 ◽  
Vol 8 (7) ◽  
pp. 7-13
Author(s):  
Badr Almutairi ◽  

As workloads increase in the industry so does the requirement for IT resources. IT companies are now shifting from in-house data centers to cloud-based IT services such as IAAS, PAAS, and SAAS which can offer flexibility at different levels to the developers of the applications working on different projects. Lots of researchers have contributed to migrating virtual machines migration from one cloud service provider to the other in case of backup as a service and other related services. Some of the previous works by some researchers focus on the migration of SAAS and PAAS onto different cloud service provider platforms. This research work focuses on the mitigation and migration of IAAS, PAAS, and SAAS services of the cloud. My contribution in this research will be in how to avoid loss of data during mitigation and migration of the VM from one Hypervisor environment to the other hypervisor environment on a physical machine infrastructure. This will help SME’s to provide end-user access to their data without worrying about the losses which may have incurred if the Mitigation process was not carried out carefully while migrating VM’s from one bare metal Hypervisor environment to the other bare metal Hypervisor environment.

2018 ◽  
Vol 6 (5) ◽  
pp. 340-345
Author(s):  
Rajat Pugaliya ◽  
Madhu B R

Cloud Computing is an emerging field in the IT industry. Cloud computing provides computing services over the Internet. Cloud Computing demand increasing drastically, which has enforced cloud service provider to ensure proper resource utilization with less cost and less energy consumption. In recent time various consolidation problems found in cloud computing like the task, VM, and server consolidation. These consolidation problems become challenging for resource utilization in cloud computing. We found in the literature review that there is a high level of coupling in resource utilization, cost, and energy consumption. The main challenge for cloud service provider is to maximize the resource utilization, reduce the cost and minimize the energy consumption. The dynamic task consolidation of virtual machines can be a way to solve the problem. This paper presents the comparative study of various task consolidation algorithms.


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].


Author(s):  
Trinathbasu Miriyala ◽  
JKR Sastry

<p><span lang="EN-US">Cloud computing technologies are being used by many who need computing resources such as software, platform and infrastructure as per their business requirements in terms of provisioning and pay for the usage as per actual consumption of the services based on the SLA signed by the user and cloud service provider. Software running on a physical machine is being provided as services to the end users. For the reasons of cost economies access to software that uses a database is being provided to multiple users. The access to the software is provided either directly or through a virtual machine. The software being provided as service uses the same database for many of the users who have requisitioned for the same. As a result, there could be encroachments by the users into the data of others. There is a need to secure the data belonging to several users while all of them access the data using the same application. In this paper an efficient method is presented for securing the data processed by software which is offered as a service to multiple users either directly or through virtual machines.    </span></p>


Author(s):  
Sovban Nisar ◽  
Deepika Arora

A structural design in which virtual machines are implicated and connect to the cloud service provider is called cloud computing. On the behalf of the users, the virtual machines connect to the cloud service provider. The uncertainties overload the virtual machines. The genetic algorithm is implemented for the migration of virtual machine in the earlier study. The genetic algorithm is low depicts latency within the network is high at the time of virtual machine migration. The genetic algorithm is implemented for virtual machine migration in this study. The proposed algorithm is applied in MATLAB in this work. The obtained results are compared with the results of earlier algorithm. Various parameters like latency, bandwidth consumption, and space utilization are used to analyze the achieved results.


2021 ◽  
Vol 17 (4) ◽  
pp. 75-88
Author(s):  
Padmaja Kadiri ◽  
Seshadri Ravala

Security threats are unforeseen attacks to the services provided by the cloud service provider. Depending on the type of attack, the cloud service and its associated features will be unavailable. The mitigation time is an integral part of attack recovery. This research paper explores the different parameters that will aid in predicting the mitigation time after an attack on cloud services. Further, the paper presents machine learning models that can predict the mitigation time. The paper presents the kernel-based machine learning models that can predict the average mitigation time during security attacks. The analysis of the results shows that the kernel-based models show 87% accuracy in predicting the mitigation time. Furthermore, the paper explores the performance of the kernel-based machine learning models based on the regression-based predictive models. The regression model is used as a benchmark model to analyze the performance of the machine learning-based predictive models in the prediction of mitigation time in the wake of an attack.


Author(s):  
Alexander Herzfeldt ◽  
Sebastian Floerecke ◽  
Christoph Ertl ◽  
Helmut Krcmar

With the increasing maturity of cloud technologies and the growing demand from customers, the cloud computing ecosystem has been expanding continuously with both incumbents and new entrants, whereby it has become more distributed and less transparent. For cloud service providers previously focusing on growth strategies, it is now necessary to shift the attention to providing service efficiently, as well as profitably. Based on 14 explorative interviews with cloud service experts, the relationship between cloud service provider profitability and value facilitation, which stands for the capability to build up resources in advance of future customer engagements, is investigated. The results indicate a positive relationship between cloud service profitability and value facilitation and deliver valuable insights for both researchers and practitioners. In particular, guidelines on how to design profitable cloud service offerings are discussed.


2022 ◽  
pp. 205-224
Author(s):  
Dhiviya Ram

One of the most unique forms of contracting is apparent in cloud computing. Cloud computing, unlike other conventional methods, has adopted a different approach in the formation of binding contract that will be used for the governance of the cloud. This method is namely the clickwrap agreement. Click wrap agreement follows a take it or leave it basis in which the end users are provided with limited to no option in terms of having a say on the contract that binds them during the use of cloud services. The terms found in the contract are often cloud service provider friendly and will be less favourable to the end user. In this article, the authors examine the terms that are often found in the cloud computing agreement as well as study the benefit that is entailed in adopting this contracting method. This chapter has undertaken a qualitative study that comprises interviews of cloud service providers in Malaysia. Hence, this study is a novel approach that also provides insight in terms of the cloud service provider perspective regarding the click wrap agreement.


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