Hypervisor virtualization technology is described as computer applications that create a virtual machine and runs it. It is a technology that is commonly used and it has enabled more than one operating system to run on one physical platform. On the other hand, data centers can be described as a facility within an organization that is central, located to carry out IT activities within an organization. These activities may include storage, retrieval and processing of data. Data centers are important to an organization since they promote communication through enhancing data exchange. These technologies have increased communication and business operations in many enterprises. This report describes their characteristics, scalability and their weakness in general.
This is a technology that explains how computers create virtual machines and run them. Operating system designers face serious problems while isolating software and allowing sharing of applications between them [1]. This shows that each application has different layouts but share some objects. Hypervisor strives to provide full separation between virtual machines by providing support in sharing of resources in computers. The technology has made single machines to host multiple software that are unrelated which run independent of the organization. The applications do not need to actually share data, they run on the same kernel as a single operating system. Currently, one can have different types of operating system installed in his machine and use them without facing any problems.
There are many ideas that enhance the use of hypervisor virtualization technology. They include [2].
If the server needs to execute a hypervisor, it loads the technology into a client operating system of the VM. Then the technology provides correct CPU resource to memory bandwidth for the machine. A VM can create requests to the hypervisor using many ways including API calls.
There two kinds of this technology:
Comparison between embedded and native hypervisors
It was difficulty to replicate hypervisors before. Currently they are highly scalable and flexible. This means that they can be changed and moved if it is required. For this to occur, one needs to know about methods that are used in data replication. Volume in machines must be replicated to enable the technology to run more efficiently.
The technology has following features and weakness [3].
Features
Weakness
Technical aspects of the network is that it provides high data security especially when it is used on the server side. It works with high scalability and flexibility.
The growing need of organizations to store and retrieve data for future use has led to development and establishment of data centers. Today data centers contain thousands of computers with appropriate and significant bandwidth requirements. Different organizations will have different layouts of their data centers depending on their requirements and the type of data that is required to be stored for future use [4]. Well-designed data centers meet the following requirements:
Data centers have the following functions in any network [5].
A data center is made up of power, storage and applications that are required to support an organization. The data center’s infrastructure is at the center of the IT from which all the content is passed through. A good model of data center is highly planned and scalable. It has high performance.
The figure below shows a structure of a working model of data center that is linked to the cloud for data backup. This design is called basic layer design.
Figure 1. Basic layer design of a data center as illustrated in [11, fig 1]
A data center should be highly flexible to deploy and support new features. This is because flexible data centers have ability to support new application features. We have different design models of data centers as explained below.
Multi-Tier Model
This is the common model of data center mainly used in Http–based applications. The model includes web, applications and database tiers of servers. It uses a software that runs as a different process on a machine using interposes communication when the process are build such that they run from different machines. It promotes security and resilience of the data centers. The security of the data centers is increased because an attacker can access a web server without breaking into application and database servers [6]. Loading of a balance network traffic promotes resilience between the tiers. Firewalls are placed between the tiers to provide security in the data center. The following diagram shows a multi-tier model of a data center.
Fig 2. Multi-tier model of a data center as illustrated in [11, fig 2]
Server Cluster Model
These data centers are used for many purposes because they are highly available and have increased power. This model enhances high performance of clusters which have many forms. Clusters have common goals of combining multiple CPUS together. This promotes high speed of the network. This kind of data models is mostly used in universities and in military research for unique applications. This kind of data center is also used in weather stations and in seismology for analysis.
Data centers have some scalability issues as explained below [7].
Data center scalability is the ability of data center to keep working even if its volume and size is changed. Data centers increase the speed of data processing if they are increased into a large size. These companies maintain data centers in order to save money. When a company wants to improve their data centers, they determine the extent to which the data center can be improved to. If a data center is over built, then there will be wastage of resources. Although sometimes business organization overbuild data centers because it is not easy to estimate the required size of a data center.
More so, the scalability and the flexibility of a data center enable the organization to build quickly at scale and in the nick of time to meet their client’s expectations. Likewise, the server farm versatility is additionally bringing the advantage of high-thickness, vitality productivity and also the capacity to lessen the expenses over the lifetime of data center speculation.
Moreover, one approach to make an adaptable server farm is by keeping up its area. A few organizations are generally searching for a territory to locate the server farm. Indeed, there is an open door for the future development that can be assume control without having more risky things for its extension, or with no issue of the expensive comforts.
The development of informal communication and thriving utilization of cell phones is the undeniable reason of the need of scalability. Data centers adaptability itself likewise expands the high security for records that the organizations keep. It influences the organizations to end up more dependable and trust-commendable. It is additionally about the requirement for speed. As the outcome to be focused, the organizations ought to have a focused on approach for server farm flexibility and versatility.
Features
Weakness
The purpose for the Data Center and Server Room Standards is to describe the base prerequisites for outlining, introducing, anchoring, checking, keeping up, securing, and decommissioning a server farm
Data centers in Australia
Also called operating system virtualization is where the layer being virtualize is running as application within an operating system. The operating system runs on the kernel and the hardware node is isolated. The isolated hardware is called the container [8].
This technology works by sharing the host kernel with its contents e.g. Containers and hosts.
Fig 3. The Container technology architecture [8, fig 2]
Containers provide necessary conditions for applications to run on the host operating system. Applications like servers which require direct access to hardware components will directly affect the functioning of the system. Container helps bypassing the emulation layers.
Scalability issues
Containers tend to have high scalability and adaptability but they are not perfect for every workload that they handle. Containers have received high virtualization technology that has great impact on its scalability [10]. It supports cloud computing and application development
Features
Weakness
The reason for the container virtualization technology is to portray the base requirements for sketching out, presenting, tying down, checking, keeping up, anchoring and decommissioning the kernel.
Conclusion
Data centers should be highly protected since they store very important information of an organizations. Other technologies like hypervisor technology are of much significant to the society since they allow two different operating systems to run on the same machine. This has made life much simpler since individuals can now purchase only one PC and use different operating systems on the same laptop.
References
[1]Hwang, J.Y., Suh, S.B., Hoe, S.K., Park, C.J., Ryun, J.M., Park, S.Y. and Kim, C.R. Xin on ARM: System virtualization using Xin hypervisor for ARM-based secure mobile phones. In Consumer Communications and Networking Conference, 2008. CCNC 2008. 5th IEEE (pp. 257-261). IEEE, 2016
[2] Younge, A.J., Henschel, R., Brown, J.T., Von Laszewski, G., Qiu, J. and Fox, G.C. Analysis of virtualization technologies for high performance computing environments. In Cloud Computing (CLOUD), 2011 IEEE International Conference on (pp. 9-16). IEEE, 2010
[3] Abramson, D., Jackson, J., Muthrasanallur, S., Neiger, G., Regnier, G., Sankaran, R., Schoinas, I., Uhlig, R., Vembu, B. and Wiegert, J. Intel Virtualization Technology for Directed I/O. Intel technology journal, 10(3).,2016
[4]Al-Fares, M., Loukissas, A. and Vahdat, A, August. A scalable, commodity data center network architecture. In ACM SIGCOMM Computer Communication Review (Vol. 38, No. 4, pp. 63-74). ACM, 2008
[5] Koomey, J. Growth in data center electricity use 2005 to 2010. A report by Analytical Press, completed at the request of The New York Times, 9, 2013
[6] Al-Fares, M., Radhakrishnan, S., Raghavan, B., Huang, N. and Vahdat, A. Hedera: dynamic flow scheduling for data center networks. In Nsdi (Vol. 10, No. 8, pp. 89-92). 2009.
[7] Meng, X., Pappas, V. and Zhang, L., Improving the scalability of data center networks with traffic-aware virtual machine placement. In INFOCOM, 2010 Proceedings IEEE (pp. 1-9). IEEE, 2017.
[8] Xavier, M.G., Neves, M.V., Rossi, F.D., Ferreto, T.C., Lange, T. and De Rose, C.A, Performance evaluation of container-based virtualization for high performance computing environments. In Parallel, Distributed and Network-Based Processing (PDP), 2013 21st Euromicro International Conference on (pp. 233-240). IEEE, 2010.
[9] Adufu, T., Choi, J. and Kim, Y. Is container-based technology a winner for high performance scientific applications? In Network Operations and Management Symposium (APNOMS), 2015 17th Asia-Pacific (pp. 507-510). IEEE, 2015.
[10]. Gerlach, W., Tang, W., Keegan, K., Harrison, T., Wilke, A., Bishop, J., D’Souza, M., Devoid, S., Murphy-Olson, D., Desai, N. and Meyer, F. Skyport: container-based execution environment management for multi-cloud scientific workflows. In Proceedings of the 5th International Workshop on Data-Intensive Computing in the Clouds (pp. 25-32). IEEE Press, 2014.
[11] Barroso, L.A., Clidaras, J. and Hölzle, U. The datacenter as a computer: An introduction to the design of warehouse-scale machines. Synthesis lectures on computer architecture, 8(3), pp.1-154. 2013.
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