scholarly journals Research On Enterprise Public and Private Cloud Service

2019 ◽  
Vol 8 (6S4) ◽  
pp. 1453-1459
Keyword(s):  
Large Scale ◽  
Service Providers ◽  
Cloud Service ◽  
Business Organizations ◽  
Public Cloud ◽  
Private Cloud ◽  
Public And Private ◽  
Technology Service ◽  
Platform Independence ◽  
Effective Assessment

In this paper, a generic comparison between the Enterprise Public and Private Cloud is analyzed based on its features and service provided. Cloud computing technology is widely adopted in today's industry where large database applications are deployed. Every organization moving towards cloud will have to consider many factors such as security, portability, database size, platform independence, multi-tenancy, customer requirements and other related resources. The detailed study focuses on essential cloud characteristics, service models, and cloud operation models such as Integrated (Hybrid), Public, Internal (Private) and Community clouds. The outcome is an effective assessment of leading two Enterprise cloud technology service providers – ownCloud© and HP Public Cloud® and its implications on the organizations which used them for cloud based applications. ownCloud© is the preferred open source file system for organizations to access for solutions across the world. HP Cloud offered by Hewlett-Packard (HP) provides public, private, hybrid and community cloud based services for various enterprise and other large-scale business organizations. Both the Private Cloud and Public Cloud can be enhanced to protect the data from intrusion with various security features where multiple users share the same cloud for storing and retrieving data

scholarly journals A Generic Model for Identifying QoS Parameters Interrelations in Cloud Services Selection Ontology during Runtime

Symmetry ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 563
Author(s):  
Babu Rajendiran ◽  
Jayashree Kanniappan
Keyword(s):  
Service Providers ◽  
Cloud Service ◽  
Cloud Services ◽  
Operating Costs ◽  
Generic Model ◽  
Business Organizations ◽  
Cloud Environment ◽  
Cloud Service Provider ◽  
Qos Parameters ◽  
Computer Based

Nowadays, many business organizations are operating on the cloud environment in order to diminish their operating costs and to select the best service from many cloud providers. The increasing number of Cloud Services available on the market encourages the cloud consumer to be conscious in selecting the most apt Cloud Service Provider that satisfies functionality, as well as QoS parameters. Many disciplines of computer-based applications use standardized ontology to represent information in their fields that indicate the necessity of an ontology-based representation. The proposed generic model can help service consumers to identify QoS parameters interrelations in the cloud services selection ontology during run-time, and for service providers to enhance their business by interpreting the various relations. The ontology has been developed using the intended attributes of QoS from various service providers. A generic model has been developed and it is tested with the developed ontology.

GOVERNMENT REGULATIONS OF THE USING CLOUD SERVICES

2022 ◽  
Author(s):  
Olexander Melnikov ◽  
◽  
Konstantin Petrov ◽  
Igor Kobzev ◽  
Viktor Kosenko ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Large Scale ◽  
Service Providers ◽  
Cloud Service ◽  
Cloud Services ◽  
Government Agencies ◽  
Remote Work ◽  
Cloud Infrastructure ◽  
Wide Range ◽  
Technological Base

The article considers the development and implementation of cloud services in the work of government agencies. The classification of the choice of cloud service providers is offered, which can serve as a basis for decision making. The basics of cloud computing technology are analyzed. The COVID-19 pandemic has identified the benefits of cloud services in remote work Government agencies at all levels need to move to cloud infrastructure. Analyze the prospects of cloud computing in Ukraine as the basis of e-governance in development. This is necessary for the rapid provision of quality services, flexible, large-scale and economical technological base. The transfer of electronic information interaction in the cloud makes it possible to attract a wide range of users with relatively low material costs. Automation of processes and their transfer to the cloud environment make it possible to speed up the process of providing services, as well as provide citizens with minimal time to obtain certain information. The article also lists the risks that exist in the transition to cloud services and the shortcomings that may arise in the process of using them.

System Benchmarking on Public Clouds

2015 ◽  
pp. 37-50
Author(s):  
Sanjay P. Ahuja ◽  
Thomas F. Furman ◽  
Kerwin E. Roslie ◽  
Jared T. Wheeler
Keyword(s):  
Service Providers ◽  
Cluster Formation ◽  
Cloud Service ◽  
Vital Role ◽  
Cloud Services ◽  
System Level ◽  
Public Cloud ◽  
Cloud Providers ◽  
Set Up ◽  
Levels Of Service

There are several public cloud providers that provide service across different cloud models such as IaaS, PaaS, and SaaS. End users require an objective means to assess the performance of the services being offered by the various cloud providers. Benchmarks have typically been used to evaluate the performance of various systems and can play a vital role in assessing performance of the different public cloud platforms in a vendor neutral manner. Amazon's EC2 Service is one of the leading public cloud service providers and offers many different levels of service. The research in this chapter focuses on system level benchmarks and looks into evaluating the memory, CPU, and I/O performance of two different tiers of hardware offered through Amazon's EC2. Using three distinct types of system benchmarks, the performance of the micro spot instance and the M1 small instance are measured and compared. In order to examine the performance and scalability of the hardware, the virtual machines are set up in a cluster formation ranging from two to eight nodes. The results show that the scalability of the cloud is achieved by increasing resources when applicable. This chapter also looks at the economic model and other cloud services offered by Amazon's EC2, Microsoft's Azure, and Google's App Engine.

Securing Business IT on the Cloud

2015 ◽  
pp. 2022-2032
Author(s):  
Bina Ramamurthy
Keyword(s):  
Large Scale ◽  
Service Providers ◽  
Cloud Service ◽  
Access Point ◽  
Cloud Provider ◽  
Service Model ◽  
Platform As A Service ◽  
Security Challenges ◽  
Modern Business ◽  
Amazon Web Services

In this chapter, the author examines the various approaches taken by the popular cloud providers Amazon Web Services (AWS), Google App Engine (GAE), and Windows Azure (Azure) to secure the cloud. AWS offers Infrastructure as a Service model, GAE is representative of the Software as a Service, and Azure represents the Platform as a Service model. Irrespective of the model, a cloud provider offers a variety of services from a simple large-scale storage service to a complete infrastructure for supporting the operations of a modern business. The author discusses some of the security aspects that a cloud customer must be aware of in selecting a cloud service provider for their needs. This discussion includes the major threats posed by multi-tenancy in the cloud. Another important aspect to consider in the security context is machine virtualization. Securing these services involves a whole range of measures from access-point protection at the client end to securing virtual co-tenants on the same physical machine hosted by a cloud. In this chapter, the author highlights the major offerings of the three cloud service providers mentioned above. She discusses the details of some important security challenges and solutions and illustrates them using screen shots of representative security configurations.

Cloud-TM

2015 ◽  
pp. 749-781
Author(s):  
João Barreto ◽  
Pierangelo Di Sanzo ◽  
Roberto Palmieri ◽  
Paolo Romano
Keyword(s):  
Cloud Computing ◽  
Large Scale ◽  
Economies Of Scale ◽  
Service Providers ◽  
Cloud Service ◽  
Capital Investments ◽  
Barriers To Entry ◽  
Capital Costs ◽  
Programming Paradigms ◽  
Pricing Schemes

By shifting data and computation away from local servers towards very large scale, world-wide spread data centers, Cloud Computing promises very compelling benefits for both cloud consumers and cloud service providers: freeing corporations from large IT capital investments via usage-based pricing schemes, drastically lowering barriers to entry and capital costs; leveraging the economies of scale for both services providers and users of the cloud; facilitating deployment of services; attaining unprecedented scalability levels. However, the promise of infinite scalability catalyzing much of the recent hype about Cloud Computing is still menaced by one major pitfall: the lack of programming paradigms and abstractions capable of bringing the power of parallel programming into the hands of ordinary programmers. This chapter describes Cloud-TM, a self-optimizing middleware platform aimed at simplifying the development and administration of applications deployed on large scale Cloud Computing infrastructures.

On the Use of System-Level Benchmarks for Comparing Public Cloud Environments

2019 ◽  
pp. 24-38
Author(s):  
Sanjay P. Ahuja
Keyword(s):  
Cloud Computing ◽  
Service Providers ◽  
Cluster Formation ◽  
Cloud Service ◽  
System Level ◽  
Public Cloud ◽  
Related Information ◽  
Computing Environments ◽  
Set Up ◽  
Levels Of Service

The proliferation of public cloud providers and services offered necessitate that end users have benchmarking-related information that help compare the properties of the cloud computing environment being provided. System-level benchmarks are used to measure the performance of overall system or subsystem. This chapter surveys the system-level benchmarks that are used for traditional computing environments that can also be used to compare cloud computing environments. Amazon's EC2 Service is one of the leading public cloud service providers and offers many different levels of service. The research in this chapter focuses on system-level benchmarks and looks into evaluating the memory, CPU, and I/O performance of two different tiers of hardware offered through Amazon's EC2. Using three distinct types of system benchmarks, the performance of the micro spot instance and the M1 small instance are measured and compared. In order to examine the performance and scalability of the hardware, the virtual machines are set up in a cluster formation ranging from two to eight nodes.

Client-Centric Cloud Service Composition

2017 ◽  
pp. 144-166
Author(s):  
Vivek Gaur ◽  
Praveen Dhyani ◽  
Om Prakash Rishi
Keyword(s):  
Service Composition ◽  
Large Scale ◽  
Business Processes ◽  
Service Providers ◽  
Service Selection ◽  
Cloud Service ◽  
Quality Parameters ◽  
End User ◽  
Cloud Service Composition ◽  
Tabu Search Methods

Recent computing world has seen rapid growth of the number of middle and large scale enterprises that deploy business processes sharing variety of services available over cloud environment. Due to the advantage of reduced cost and increased availability, the cloud technology has been gaining unbound popularity. However, because of existence of multiple cloud service providers on one hand and varying user requirements on the other hand, the task of appropriate service composition becomes challenging. The conception of this chapter is to consider the fact that different quality parameters related to various services might bear varied importance for different user. This chapter introduces a framework for QoS-based Cloud service selection to satisfy the end user needs. A hybrid algorithm based on genetic algorithm (GA) and Tabu Search methods has been developed, and its efficacy is analysed. Finally, this chapter includes the experimental analysis to present the performance of the algorithm.

scholarly journals A Secure IoT-Based Cloud Platform Selection Using Entropy Distance Approach and Fuzzy Set Theory

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Alakananda Chakraborty ◽  
Muskan Jindal ◽  
Mohammad R. Khosravi ◽  
Prabhishek Singh ◽  
Achyut Shankar ◽  
...  
Keyword(s):  
Set Theory ◽  
Fuzzy Set ◽  
Fuzzy Set Theory ◽  
Large Scale ◽  
Service Providers ◽  
Cost Optimization ◽  
Cloud Service ◽  
Security And Privacy ◽  
Cloud Platform ◽  
Efficiency Cost

With the growing emergence of the Internet connectivity in this era of Gen Z, several IoT solutions have come into existence for exchanging large scale of data securely, backed up by their own unique cloud service providers (CSPs). It has, therefore, generated the need for customers to decide the IoT cloud platform to suit their vivid and volatile demands in terms of attributes like security and privacy of data, performance efficiency, cost optimization, and other individualistic properties as per unique user. In spite of the existence of many software solutions for this decision-making problem, they have been proved to be inadequate considering the distinct attributes unique to individual user. This paper proposes a framework to represent the selection of IoT cloud platform as a MCDM problem, thereby providing a solution of optimal efficacy with a particular focus in user-specific priorities to create a unique solution for volatile user demands and agile market trends and needs using optimized distance-based approach (DBA) aided by Fuzzy Set Theory.

scholarly journals An Inimitable Mechanism and Architecture for Security in Cloud using Multi Cloud

2020 ◽  
Vol 8 (5) ◽  
pp. 1627-1631
Keyword(s):  
Data Security ◽  
Service Providers ◽  
Cloud Service ◽  
Cloud Environment ◽  
Private Cloud ◽  
Cloud Architecture ◽  
Cloud Service Providers ◽  
Lock In ◽  
Cloud Users ◽  
Multi Cloud

Confidentiality, Privacy and Protection of data (CPPD) are the major challenges in the cloud environment for cloud users such as industrials and organizations. Hence major companies are loath to migrate to cloud and also still using the private cloud because of lock in CPPD of cloud. Cloud Service Providers (CSP) are unable to elucidate strength of the storage and services due to lack of data security. To solve the above issue, we trust, algorithms are not the only solution for data security. In this regards, we suggest to change the architecture and develop a new mechanisms. In this paper, we are proposed two thinks. First is move to single cloud architecture to multiple cloud architecture and second is develop an innovative algorithm. And one more think also considered and proposed an inimitable mechanism to use an innovative algorithm in the multi cloud architecture for improving CPPD.

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