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Journal articles on the topic 'Eucalyptus Private Cloud'

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Published: 3 June 2025

Last updated: 13 July 2025

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Milojicic, Dejan, and Rich Wolski. "Eucalyptus: Delivering a Private Cloud." Computer 44, no. 4 (2011): 102–4. http://dx.doi.org/10.1109/mc.2011.109.

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Kačeniauskas, Arnas, Ruslan Pacevič, Miglė Staškūnienė, et al. "Private Cloud Infrastructure for Applications of Mechanical and Medical Engineering." Information Technology And Control 44, no. 3 (2015): 254–61. http://dx.doi.org/10.5755/j01.itc.44.3.7379.

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The paper presents the development of the private cloud infrastructure providing advanced services for research in mechanical and medical engineering. The cloud services have been developed by using Apache jclouds API and JetS3t Toolkit to enhance management of Eucalyptus cloud infrastructure and to increase accessibility of engineering software. The performance of the developed cloud infrastructure has been assessed testing CPU, memory IO, disk IO, network and the deployed software services. The obtained results have been compared with the performance of the native hardware. The technical implementation of deployed cloud services has been evaluated by the utilising a number of use cases from different research areas of mechanical and medical engineering.DOI: http://dx.doi.org/10.5755/j01.itc.44.3.7379

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PJacob, Jobby, and Anirban Basu. "Performance Analysis of Hadoop Map Reduce on Eucalyptus Private Cloud." International Journal of Computer Applications 79, no. 17 (2013): 10–13. http://dx.doi.org/10.5120/13960-1661.

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S.Patil, Mayur, and Bharati Ainapure. "Intrusion Detection by Forensic Method in Private Cloud using Eucalyptus." International Journal of Computer Applications 85, no. 12 (2014): 50–60. http://dx.doi.org/10.5120/14897-3373.

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Bhagyashri, Pathak Rajesh SR Sankalp Jain Amit Saxena Rashmi Mahajan and Rajendra Joshi*. "PRIVATE CLOUD INITIATIVES USING BIOINFORMATICS RESOURCES AND APPLICATIONS FACILITY (BRAF)." International Journal on Cloud Computing: Services and Architecture (IJCCSA) 2, December (2018): 01–10. https://doi.org/10.5281/zenodo.1435319.

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The bioinformatics research community has a demand of enormous compute resources to run bioinformatics tools. Next generation sequencing technologies have further increased the overall demand for computational analysis. The traditional Cluster and Grid computing are having their own complexities to program and use while there is a silver-line in cloud for on-demand high-performance infrastructures with the advent of cloud computing era and its advantages. We have adopted the technology so that it can prove its mandate with more benefits to the community. We are able to bring out a private cloud using BRAF which is a high end cluster facility dedicated for bioinformatics. Open source equivalents to prominent commercially available solutions are used as the cloud middle-ware stack. In this paper we will summarize our implementation of a virtualized private cloud environment using Eucalyptus

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Hsu, Mon Kyi1 and Thinn Thu Naing2. "STOCHASTIC MARKOV MODEL APPROACH FOR EFFICIENT VIRTUAL MACHINES SCHEDULING ON PRIVATE CLOUD." International Journal on Cloud Computing: Services and Architecture(IJCCSA) 1, November (2018): 01–13. https://doi.org/10.5281/zenodo.1449823.

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Cloud computing is deployed a large set of virtualized computing resources in different infrastructures and various development platforms. One of the significant issues in cloud computing system is the scheduling and allocation of virtual resources and virtual machines (VMs). To address this issue, this paper proposed an efficient approach for virtual machines scheduling in cloud infrastructure resource management and allocation also called EVMSA (Efficient Virtual Machines Scheduling Algorithm) that provides the effective and efficient resource allocation. To analyze the performance of this scheduling and allocation on cloud infrastructure, an analytical performance model approach using Stochastic Markov model is proposed to measure the scalability and tractability for infrastructure resource of private cloud. This model intends to analyze an academic-oriented private cloud system which is implemented using Eucalyptus open source system. According to performance evaluation, the effective mean response time of the system to improve the performance of IaaS services in the system.

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Oleksyuk, V. P. "Cloud technologies in the process of higher educational institution IT infrastructure projecting." CTE Workshop Proceedings 2 (March 20, 2014): 25–39. http://dx.doi.org/10.55056/cte.182.

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The article investigated the concept of IT infrastructure of higher educational institution. The article described models of deploying of cloud technologies in IT infrastructure. The hybrid model is most recent for higher educational institution. The unified authentication is an important component of IT infrastructure. The author suggests the public (Google Apps, Office 365) and private (Cloudstack, Eucalyptus, OpenStack) cloud platforms to deploying in IT infrastructure of higher educational institution.The purpose of article is to designing individual components of the IT infrastructure of a higher education institution using cloud technology.Task of the research: to analyze the concept of "IT infrastructure", to determine the characteristics of deployment of the cloud technologies and to offer the some components of the IT infrastructure of universities in the traditional and cloud context aspect.The object of the research is IT infrastructure of higher education.The subject of the research is cloud and traditional services as components of the IT infrastructure of the university.Methods: analysis of literature studying the functioning of the IT infrastructure of the university, modeling and design of IT infrastructure.Results: analyzed the concept of "IT infrastructure", "cloud technology", defined characteristics and models of cloud technology deployment, proposed separate components of the IT infrastructure of higher education institutions in the context of "traditional" and "cloud" aspects.Conclusions. The use of cloud technologies in the design of IT infrastructure of universities is an actual and need of the development. The hybrid model is the most appropriate in the deployment of cloud infrastructure of higher educational institution. It is reasonable to use the public (Google Apps and Microsoft Office 365) and private (Cloudstack, Eucalyptus, OpenStack) cloud platform.

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Dantas, Jamilson, Rubens Matos, Jean Araujo, and Paulo Maciel. "Eucalyptus-based private clouds: availability modeling and comparison to the cost of a public cloud." Computing 97, no. 11 (2015): 1121–40. http://dx.doi.org/10.1007/s00607-015-0447-8.

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Ezugwu, Absalom E., Seyed M. Buhari, and Sahalu B. Junaidu. "Virtual Machine Allocation in Cloud Computing Environment." International Journal of Cloud Applications and Computing 3, no. 2 (2013): 47–60. http://dx.doi.org/10.4018/ijcac.2013040105.

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Virtual machine allocation problem is one of the challenges in cloud computing environments, especially for the private cloud design. In this environment, each virtual machine is mapped unto the physical host in accordance with the available resource on the host machine. Specifically, quantifying the performance of scheduling and allocation policy on a Cloud infrastructure for different application and service models under varying performance metrics and system requirement is an extremely challenging and difficult problem to resolve. In this paper, the authors present a Virtual Computing Laboratory framework model using the concept of private cloud by extending the open source IaaS solution Eucalyptus. A rule based mapping algorithm for Virtual Machines (VMs) which is formulated based on the principles of set theoretic is also presented. The algorithmic design is projected towards being able to automatically adapt the mapping between VMs and physical hosts’ resources. The paper, similarly presents a theoretical study and derivations of some performance evaluation metrics for the chosen mapping policies, these includes determining the context switching, waiting time, turnaround time, and response time for the proposed mapping algorithm.

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Holovnia, Olena S., and Vasyl P. Oleksiuk. "Selecting cloud computing software for a virtual online laboratory supporting the Operating Systems course." CTE Workshop Proceedings 9 (March 21, 2022): 216–27. http://dx.doi.org/10.55056/cte.116.

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The article provides a survey on cloud platforms suitable for a virtual online laboratory, which contains Linux online environments and is intended to support the Operating Systems course.The study justifies the choice of utilizing private cloud as a deployment model and IaaS as a service model and substantiates the decision to create specially tailored cloud environments adapted for educational needs in contrast to applying ready-made IaaS (Infrastructure as a Service) cloud services given by providers. The related works on cloud platforms for teaching operating systems are analyzed. The study also makes a review of the authors' previous research on virtualization tools and environments for the Operating Systems course and Cisco CyberSecurity Operations course. The basic and additional requirements for cloud computing software for virtual online laboratory supporting Operating Systems course have been elaborated. Finally, the work makes the comparison of Eucalyptus, OpenStack, CloudStack and OpenNebula cloud platforms and substantiates the selection among these cloud computing software the platforms of the first and the second choice.

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Hiden, Hugo, Simon Woodman, Paul Watson, and Jacek Cala. "Developing cloud applications using the e-Science Central platform." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 371, no. 1983 (2013): 20120085. http://dx.doi.org/10.1098/rsta.2012.0085.

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This paper describes the e-Science Central (e-SC) cloud data processing system and its application to a number of e-Science projects. e-SC provides both software as a service (SaaS) and platform as a service for scientific data management, analysis and collaboration. It is a portable system and can be deployed on both private (e.g. Eucalyptus) and public clouds (Amazon AWS and Microsoft Windows Azure). The SaaS application allows scientists to upload data, edit and run workflows and share results in the cloud, using only a Web browser. It is underpinned by a scalable cloud platform consisting of a set of components designed to support the needs of scientists. The platform is exposed to developers so that they can easily upload their own analysis services into the system and make these available to other users. A representational state transfer-based application programming interface (API) is also provided so that external applications can leverage the platform's functionality, making it easier to build scalable, secure cloud-based applications. This paper describes the design of e-SC, its API and its use in three different case studies: spectral data visualization, medical data capture and analysis, and chemical property prediction.

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Matos, Rubens, Jamilson Dantas, Jean Araujo, Kishor S. Trivedi, and Paulo Maciel. "Redundant Eucalyptus Private Clouds: Availability Modeling and Sensitivity Analysis." Journal of Grid Computing 15, no. 1 (2016): 1–22. http://dx.doi.org/10.1007/s10723-016-9381-z.

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"Research of Eucalyptus, Openstack and Open Nebula." International Journal of Recent Technology and Engineering 8, no. 2S8 (2019): 1532–35. http://dx.doi.org/10.35940/ijrte.b1098.0882s819.

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The quantity of cloud the executives programming identified with a private foundation as-an administration cloud is expanding step by step. The highlights of the cloud the board programming shift altogether and this makes a trouble for the cloud customers to pick the product dependent on their business prerequisites. With the growing amounts of cloud service providers and the transfer of grids to the noisy worldview, the choice to use these new assets is essential. In addition, an enormous High Performance Computing (HPC) category of apps can operate these advantages without (or with minor) modifications .In this work we present the structure of a HPC middleware that can utilize assets originating from a situation that make out of numerous Clouds just as old style HPC assets. Utilizing the Diet middleware, we can convey an enormous scale, disseminated HPC stage that ranges over a huge pool of assets accumulated from various suppliers. At last, we approve the engineering idea through cosmological re-enactment Ramses.

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"Does Selection of Open Source Cloud Computing Platforms is a Confusing Task?" International Journal of Recent Technology and Engineering 9, no. 1 (2020): 829–33. http://dx.doi.org/10.35940/ijrte.a1978.059120.

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Over the last few years the majority of small and large companies moving to cloud computing to develop IT solutions for businesses. It is technology which provides distributed and dynamically shared computing resources using certain operating techniques. In the revolution of information technology, cloud computing is becoming a key paradigm. Cloud computing further classified as Public, Private and Hybrid Cloud. It provides three services which are categorized as Infrastructure-as-Service, Platform-as-Service and Software-as-Service. Open source cloud management platforms providing Infrastructure-as-a-service are now commonly used because of the fastest growth of cloud. Many open source softwares are available for deploying public or private cloud. This paper provides a brief review and comparison of five well-known open source cloud software i.e. OpenNebula, Eucalyptus, OpenStack, Nimbus and CloudStack providing IaaS on the basis of their similar features and technology used. After reviewing the importance and features, we have found OpenStack Cloud Platform is more reliable and useful for the enterprises and organization because of its feature and rapid improvements in its features. The distinction in this paper is believed to help people to choose the suitable open source software according to their need.

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M.Ali, Mumtaz, and Asraa Abdulrazak. "Performance Evaluation of Private Clouds Eucalyptus versus CloudStack." International Journal of Advanced Computer Science and Applications 5, no. 5 (2014). http://dx.doi.org/10.14569/ijacsa.2014.050516.

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