Cloud Hypervisor Research Articles

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

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.

Assessment of Network & Processor Virtualization in Cloud Computing

Cloud Computing is an emerging field in applied computer science. Cloud computing depends on virtualization, where a sole physical resource is virtualized into numerous virtual resources. Resources that are being virtualized include physical storage, processing units, volatile memories, network, and further physical resources. Processor and network virtualization offer several advantages like lessening hardware cost, energy consumption, and the human struggle for administration and management of resources. In this article, the primary concentration was on the evaluation and assessment of network virtualization between different cloud computing hypervisors and to contrast their evaluated results. This comparison is based on a few experiments performed on Citrix XenServer, Microsoft Hyper-V, and VMware vSphere hypervisors. XenServer uses Open vSwitch for its network virtualization whereas Hyper-V and vSphere use Microsoft network virtualization and vSphere switch for managing their network virtualization respectively. We have found that virtual networks are further scalable and secure than physical networks. We can assign multiple virtual interfaces or connections to a single virtual machine. In light of various experiments, in which we have compared non-virtualized with virtualized scenarios, for all these above-mentioned hypervisors, we found out that we can use virtual networks with and without VLAN Tags or VLAN Ids. Hyper-V provides further flexibility and options regarding VLAN Tag in comparison with XenServer or vSphere. We have also found that XenServer and vSphere give us extra network throughput in comparison with Hyper-V in terms of TCP and UDP whereas Round Trip Time (RTT) in the virtual network of all hypervisors are high in comparison with the non-virtual environment. Network CPU usage is also measured and found that vSphere and XenServer together consume more CPU during network activity in comparison with Hyper-V. We also found that processor virtualization did not majorly result from the average schedule time in comparison with a non-virtualized machine. We consequently conclude that in general a small reduction in the performance, in the case of virtualization is insignificant as compared with the advantages we get from virtualization when using cloud hypervisors. For the application of virtualization, this work will motivate to set up of data centers using a virtualized environment.

Hypervisor Vulnerabilities and Some Defense Mechanisms, in Cloud Computing Environment

Cloud computing is the most important technology at the present time, in terms of reducing applications costs and makes them more scalable and flexible. As the cloud currency is based on building virtualization technology, so it can secure a large-scale environment with limited security capacity such as the cloud. Where, Malicious activities lead the attackers to penetrate virtualization technologies that endanger the infrastructure, and then enabling attacker access to other virtual machines which running on the same vulnerable device. The proposed work in this paper is to review and discuss the attacks and intrusions that allow a malicious virtual machine (VM) to penetrate hypervisor, especially the technologies that malicious virtual machines work on, to steal more than their allocated quota from material resources, and the use of side channels to steal data and Passing buffer barriers between virtual machines. This paper is based on the Security Study of Cloud Hypervisors and classification of vulnerabilities, security issues, and possible solutions that virtual machines are exposed to. Therefore, we aim to provide researchers, academics, and industry with a better understanding of all attacks and defense mechanisms to protect cloud security. and work on building a new security architecture in a virtual technology based on hypervisor to protect and ensure the security of the cloud.

Securing Cloud Hypervisors: A Survey of the Threats, Vulnerabilities, and Countermeasures

The exponential rise of the cloud computing paradigm has led to the cybersecurity concerns, taking into account the fact that the resources are shared and mediated by a ‘hypervisor’ that may be attacked and user data can be compromised or hacked. In order to better define these threats to which a cloud hypervisor is exposed, we conducted an in-depth analysis and highlighted the security concerns of the cloud. We basically focused on the two particular issues, i.e., (a) data breaches and (b) weak authentication. For in-depth analysis, we have successfully demonstrated a fully functional private cloud infrastructure running on CloudStack for the software management and orchestrated a valid hack. We analyzed the popular open-source hypervisors, followed by an extensive study of the vulnerability reports associated with them. Based on our findings, we propose the characterization and countermeasures of hypervisor’s vulnerabilities. These investigations can be used to understand the potential attack paths on cloud computing and Cloud-of-Things (CoT) applications and identify the vulnerabilities that enabled them.

Practice on Detecting Malware in Virtualized Environment of Cloud

Virtual machines are expanding in notoriety and are being broadly received. The idea of a virtual machine is however not new. As per the cloud hypervisor is one of the major component of security. This paper consist of survey of various research paper in this domain. First we discussed about the functionality of the hypervisor form the research paper. Next, Paper discussed about various malware which has effect on hypervisor and the functionality or feature of that malware which make them to effect the hypervisor in virtualized environment. At long last, late research in the territory of hypervisor security is dissected. Research into the security of hypervisors is constrained. Most security examine is gathered in the cloud stage where hypervisors plays a noticeable part. As an assessment of security, some security bugs announced for the Hypervisor framework and the comparing relief methodologies utilized are likewise talked about.

A Secured Real Time Scheduling Model for Cloud Hypervisor

Virtualization is critical to cloud computing and is possible through hypervisors, which maps the Virtual machines((VMs) to physical resources but poses security concerns as users relinquish physical possession of their computation and data. Good amount of research is initiated for resource provisioning on hypervisors, still many issues need to be addressed for security demanding and real time VMs. First work SRT-CreditScheduler (Secured and Real-time), maximizes the success rate by dynamically prioritizing the urgency and the workload of VMs but ensures highest security for all. Another work, SA-RT-CreditScheduler (Security-aware and Real-time) is a dual objective scheduler, which maximizes the success rate of VMs in best possible security range as specified by the VM owner. Though the algorithms can be used by any hypervisor, for the current work they have been implemented on Xen hypervisor. Their effectiveness is validated by comparing it with Xen's, Credit and SEDF scheduler, for security demanding tasks with stringent deadline constraints.

Multicast and customized deployment of large-scale operating systems

With the recent paradigm shift of cloud computing, deployment of operating systems (OSs) onto a large-scale computer network is becoming necessary. Note that there are usually numerous nodes with various functions in a cloud computing system. Thus, it is usually required to deploy different operating systems onto different nodes. In such a customized setting, conventional techniques of using unicast deployment to distribute a massive cloud OS onto thousands of nodes is time consuming and bandwidth-intensive. In this work, we thus propose a multicast deployment approach so as to significantly improve deployment efficiency. Furthermore, our multicast deployment approach can leverage existing configurations of the unicast counterpart. Specifically, the advantageous features of the proposed approach include the support of a reliable multicast protocol, a heterogeneous infrastructure, and cloud hypervisor environments. To evaluate the feasibility of the proposed approach in practical applications, CentOS and Ubuntu are used when implementing our deployment approach on several tens of nodes. Empirical studies show that both the required time for the entire distribution process, i.e., from starting delivery until the OS is ready, and the network bandwidth consumption are significantly reduced as compared with conventional unicast approaches. Consequently, less effort is required on monitoring and maintenance for system administrators.

The Study on Cloud Computing Resource Allocation Method

Resource allocation and scheduling problems in the field of cloud computing can be classified into two major groups. The first one is in the area of MapReduce task scheduling. The default scheduler is the FIFO one. Two other schedulers that are available as plug-in for Hadoop: Fair scheduler and Capacity scheduler. We presented recent research in this area to enhance performance or to better suit a specific application. MapReduce scheduling research involves introducing alternative schedulers, or proposing enhancements for existing schedulers such as streaming and input format specification. The second problem is the provisioning of virtual machines and processes to the physical machines and its different resources. We presented the major cloud hypervisors available today. We described the different methods used to solve the resource allocation problem including optimization, simulation, distributed multi-agent systems and SoA. Finally, we presented the related topic of connecting clouds which uses similar resource provisioning methods. The above two scheduling problems are often mixed up, yet they are related. For example, MapReduce benchmarks can be used to evaluate VM provisioning methods. Enhancing the solution to one problem can affect the other. Similar methods can be used in solving both problems, such as optimization methods. Cloud computing is a platform that hosts applications and services for businesses and users to accesses computing as a service. In this paper, we identify two scheduling and resource allocation problems in cloud computing.