A fully security included Cloud Computing Architecture

Many developers have designed their own architecture for installing the cloud computing infrastructure. The existing cloud computing architectures differs in many ways. Security has been the serious issue as client related data and processing is undertaken using the infrastructure provided by third party service providers varies greatly. It is necessary to know the extent of inclusion of security into the cloud computing system and then find the best architecture that includes best and tight security system. In this paper, a comparison of existing architectures from the perspective of inclusion of security infrastructure within cloud computing system is presented along with a comprehensive architecture that is included with every aspect of security taking into account the most of the vulnerabilities.

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Conceptual oriented study on the cloud computing architecture for the full-security

International Journal of Engineering & Technology ◽

10.14419/ijet.v7i4.11654 ◽

2018 ◽

Vol 7 (4) ◽

pp. 2491

Author(s):

Dr. K.Sai Manoj ◽

Ms. K.Mrudula ◽

G Maanasa ◽

K Phani Srinivas

Keyword(s):

Cloud Computing ◽

Service Providers ◽

Computing System ◽

Third Party ◽

Computing Architecture ◽

Related Data ◽

Cloud Computing System ◽

Security Infrastructure ◽

Tight Security ◽

Computing Infrastructure

Many developers have designed their own architecture for installing the cloud computing infrastructure. The existing cloud computing architectures differs in many ways. Security has been the serious issue as client related data and processing is un-dertaken using the infrastructure provided by third party service providers varies greatly. It is necessary to know the extent of inclusion of security into the cloud computing system and then find the best architecture that includes best and tight security system.In this paper, a comparison of existing architectures from the perspective of inclusion of security infrastructure within cloud computing system is presented along with a comprehensive architecture that is included with every aspect of security taking into account the most of the vulnerabilities

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A Cloud Computing System to Quickly Implement New Microarray Data Pre-processing Methods

The Open Bioinformatics Journal ◽

10.2174/1875036201206010037 ◽

2012 ◽

Vol 6 (1) ◽

pp. 37-42 ◽

Cited By ~ 1

Author(s):

Dajie Luo ◽

Prithish Banerjee ◽

E. James Harner ◽

James A. Mobley ◽

Dongquan Chen

Keyword(s):

Cloud Computing ◽

Microarray Data ◽

Software Tool ◽

Computing System ◽

Processing Methods ◽

Exon Arrays ◽

Related Data ◽

Cloud Computing System ◽

R Packages ◽

Programming Knowledge

Background: Pre-processing, including normalization of raw microarray data is crucial to microarray-related data analysis. It takes time and effort to build newly-developed algorithms into commercial software or locally developed systems. While most new algorithms emerge in the form of sharable R packages, it can be difficult for many biologists to apply them as soon as they are available. Currently, we rely on statisticians and experienced programmers to develop and implement code to access those R packages. Therefore, we need a robust procedure to quickly implement pre-processing methods as they appear. The newly emerging cloud computing concept has directed us toward a new way for providing an easily accessible service to the biologists without requiring them to have any programming knowledge in R. Results: Based on our earlier Java-based software tool JavaStat, we developed an internet based application prototype to upload data and carry out pre-processing applications that include normalization, statistical analyses and plots. More im-portantly, R packages, e. g., for newly-developed normalization methods, and GC-robust multichip algorithm (RMA) for exon arrays, can be easily incorporated into the system with limited inputs from a biologist or a programmer. The data are stored in the cloud and the R code runs on server. Conclusion: The newly emerged cloud computing concept provides us a new way to provide an easily accessible and up-to-date service to biologists, as evidenced by our JavaStat system to incorporate new pre-processing package as they ap-pear. Users can access the application with a newly incorporated module through the Web. We expect this and other simi-lar systems greatly decrease turn-around time, improve accessibility of newly developed R model for pre-processing algo-rithms.

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EVALUATION OF CLOUD COMPUTING CLUSTER PERFORMANCE

T-Comm ◽

10.36724/2072-8735-2020-14-12-72-79 ◽

2020 ◽

Vol 14 (12) ◽

pp. 72-79

Author(s):

Aleksandr O. Volkov ◽

Keyword(s):

Cloud Computing ◽

Quality Of Service ◽

Service Providers ◽

Poisson Model ◽

Cloud Service ◽

Computing System ◽

Processor Sharing ◽

Cloud Systems ◽

Cloud Computing System

For cloud service providers, one of the most relevant tasks is to maintain the required quality of service (QoS) at an acceptable level for customers. This condition complicates the work of providers, since now they need to not only manage their resources, but also provide the expected level of QoS for customers. All these factors require an accurate and well-adapted mechanism for analyzing the performance of the service provided. For the reasons stated above, the development of a model and algorithms for estimation the required resource is an urgent task that plays a significant role in cloud systems performance evaluation. In cloud systems, there is a serious variance in the requirements for the provided resource, as well as there is a need to quickly process incoming requests and maintain the proper level of quality of service – all of these factors cause difficulties for cloud providers. The proposed analytical model for processing requests for a cloud computing system in the Processor Sharing (PS) service mode allows us to solve emerging problems. In this work, the flow of service requests is described by the Poisson model, which is a special case of the Engset model. The proposed model and the results of its analysis can be used to evaluate the main characteristics of the performance of cloud systems.

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Opportunity for Realizing Ideal Computing System using Cloud Computing Model

International Journal of Case Studies in Business, IT, and Education ◽

10.47992/ijcsbe.2581.6942.0015 ◽

2017 ◽

pp. 60-71

Author(s):

P. S. Aithal ◽

Vaikunth Pai T

Keyword(s):

Cloud Computing ◽

Scale Up ◽

Computing System ◽

Third Party ◽

Information Communication ◽

Computing Device ◽

Computing Services ◽

Cloud Computing Service ◽

Cloud Computing System ◽

Hypothetical System

An ideal computing system is a computing system with ideal characteristics. The major components and their performance characteristics of such hypothetical system can be studied as a model with predicted input, output, system and environmental characteristics using the identified objectives of computing which can be used in any platform, any type of computing system, and for application automation, without making modifications in the form of structure, hardware, and software coding by an external user. In this paper, we have proposed cloud computing service model to be used as a part of computing processor section enabled through information communication technology concept and discussed how it will support the computing processor part of ideal computing processor section by providing virtual system components with both hardware and software from the cloud to realize ideal computing system model. In this model, the infrastructure required for an ideal computing processor section is owned by a third party vendor and the cloud computing services are delivered to the ideal computing system over the Internet on a leased/wireless basis with the capability to extend up or down their service requirements or needs ubiquitously and almost infinite scale-up capability. A well designed flexible cloud computing system can work and fulfill the requirement of the processing section of an ideal computing device. It also offers an innovative business concept for organizations to adopt ideal computing services without advance investment and enables convenient, on-request network accessibility to a shared pool of IT computing resources like networks, servers, storage, applications, and services

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