A Survey on Comparison of Performance Analysis on a Cloud-Based Big Data Framework

2022 ◽  
pp. 1865-1875
Author(s):  
Krishan Tuli ◽  
Amanpreet Kaur ◽  
Meenakshi Sharma
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
It Services ◽  
Huge Amount ◽  
Data Framework ◽  
Development Tools ◽  
Cloud Framework ◽  
Suitable Framework ◽  
Cloud Applications ◽  
Day By Day

Cloud computing is offering various IT services to many users in the work on the basis of pay-as-you-use model. As the data is increasing day by day, there is a huge requirement for cloud applications that manage such a huge amount of data. Basically, a best solution for analyzing such amounts of data and handles a large dataset. Various companies are providing such framesets for particular applications. A cloud framework is the accruement of different components which is similar to the development tools, various middleware for particular applications and various other database management services that are needed for cloud computing deployment, development and managing the various applications of the cloud. This results in an effective model for scaling such a huge amount of data in dynamically allocated recourses along with solving their complex problems. This article is about the survey on the performance of the big data framework based on a cloud from various endeavors which assists ventures to pick a suitable framework for their work and get a desired outcome.

A Survey on Comparison of Performance Analysis on a Cloud-Based Big Data Framework

2019 ◽  
Vol 11 (2) ◽  
pp. 41-52
Author(s):  
Krishan Tuli ◽  
Amanpreet Kaur ◽  
Meenakshi Sharma
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
It Services ◽  
Huge Amount ◽  
Large Dataset ◽  
Data Framework ◽  
Cloud Framework ◽  
Suitable Framework ◽  
Cloud Applications ◽  
Day By Day

Cloud computing is offering various IT services to many users in the work on the basis of pay-as-you-use model. As the data is increasing day by day, there is a huge requirement for cloud applications that manage such a huge amount of data. Basically, a best solution for analyzing such amounts of data and handles a large dataset. Various companies are providing such framesets for particular applications. A cloud framework is the accruement of different components which is similar to the development tools, various middleware for particular applications and various other database management services that are needed for cloud computing deployment, development and managing the various applications of the cloud. This results in an effective model for scaling such a huge amount of data in dynamically allocated recourses along with solving their complex problems. This article is about the survey on the performance of the big data framework based on a cloud from various endeavors which assists ventures to pick a suitable framework for their work and get a desired outcome.

scholarly journals Measuring the Performance on Load Balancing Algorithms

2019 ◽  
pp. 41-49 ◽  
Author(s):  
Saumendu Roy ◽  
Dr. Md. Alam Hossain ◽  
Sujit Kumar Sen ◽  
Nazmul Hossain ◽  
Md. Rashid Al Asif
Keyword(s):  
Cloud Computing ◽  
Reaction Time ◽  
Load Balancing ◽  
Virtual Machines ◽  
Huge Amount ◽  
Heavy Load ◽  
Cloud Server ◽  
Load Balancing Algorithm ◽  
Day By Day ◽  
Better Than

Load balancing is an integrated aspect of the environment in cloud computing. Cloud computing has lately outgoing technology. It has getting exoteric day by day residence widespread chance in close to posterior. Cloud computing is defined as a massively distributed computing example that is moved by an economic scale in which a repertory of abstracted virtualized energetically. The number of clients in cloud computing is increasing exponentially. The huge amount of user requests attempt to entitle the collection for numerous applications. Which alongside with heavy load not far afield off from cloud server. Whenever particular (Virtual Machine) VMs are overloaded then there are no more duties should be addressed to overloaded VM if under loaded VMs are receivable. For optimizing accomplishment and better response or reaction time the load has to be balanced between overloaded VMs (virtual machines). This Paper describes briefly about the load balancing accession and identifies which is better than others (load balancing algorithm).

The Rise of Big Data, Cloud, and Internet of Things

2018 ◽  
pp. 201-222 ◽  
Author(s):  
Reema Abdulraziq ◽  
Muneer Bani Yassein ◽  
Shadi Aljawarneh
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Internet Of Things ◽  
End Users ◽  
Structured Data ◽  
The Internet ◽  
Huge Amount ◽  
Volume Velocity ◽  
The Cost ◽  
The Internet Of Things

Big data refers to the huge amount of data that is being used in commercial, industrial and economic environments. There are three types of big data; structured, unstructured and semi-structured data. When it comes to discussions on big data, three major aspects that can be considered as its main dimensions are the volume, velocity, and variety of the data. This data is collected, analysed and checked for use by the end users. Cloud computing and the Internet of Things (IoT) are used to enable this huge amount of collected data to be stored and connected to the Internet. The time and the cost are reduced by means of these technologies, and in addition, they are able to accommodate this large amount of data regardless of its size. This chapter focuses on how big data, with the emergence of cloud computing and the Internet of Things (IOT), can be used via several applications and technologies.

Cloud Integration for Effective Delivery of IT Services

2016 ◽  
pp. 733-744
Author(s):  
Roma Puri
Keyword(s):  
Cloud Computing ◽  
Enterprise Resource Planning ◽  
Relationship Management ◽  
Resource Planning ◽  
Customer Relationship ◽  
Internet Technology ◽  
It Services ◽  
Data Framework ◽  
Effective Delivery ◽  
The Web

Cloud computing is a state-of-the-art Internet technology being recently adapted by enterprises. The cloud computing models are implemented by business to improve existing practices. With improvement in the standards of the Web and affordability of mobile devises, the customer has accepted the online way of shopping. Cloud computing has been extensively used to deliver e-commerce, Customer Relationship Management (CRM) and Enterprise Resource Planning (ERP). E-commerce models have undergone considerable changes in order to attract customers online. This chapter showcases the requirement of e-commerce model to integrate cloud computing technology. This chapter puts forward cloud computing applications for E-commerce, CRM and ERP by describing the significant characteristics of the cloud. For enterprises to bring into play cloud based e-commerce, CRM and ERP, certain significant issues need to be handled. These issues are the points of discussion in the chapter. In addition, the chapter introduces big data framework for building efficient e-commerce framework.

Cloud Integration for Effective Delivery of IT Services

2015 ◽  
pp. 78-89
Author(s):  
Roma Puri
Keyword(s):  
Cloud Computing ◽  
Enterprise Resource Planning ◽  
Relationship Management ◽  
Resource Planning ◽  
Customer Relationship ◽  
Internet Technology ◽  
It Services ◽  
Data Framework ◽  
Effective Delivery ◽  
The Web

Cloud computing is a state-of-the-art Internet technology being recently adapted by enterprises. The cloud computing models are implemented by business to improve existing practices. With improvement in the standards of the Web and affordability of mobile devises, the customer has accepted the online way of shopping. Cloud computing has been extensively used to deliver e-commerce, Customer Relationship Management (CRM) and Enterprise Resource Planning (ERP). E-commerce models have undergone considerable changes in order to attract customers online. This chapter showcases the requirement of e-commerce model to integrate cloud computing technology. This chapter puts forward cloud computing applications for E-commerce, CRM and ERP by describing the significant characteristics of the cloud. For enterprises to bring into play cloud based e-commerce, CRM and ERP, certain significant issues need to be handled. These issues are the points of discussion in the chapter. In addition, the chapter introduces big data framework for building efficient e-commerce framework.

Big Data in Cloud Computing

2021 ◽  
pp. 77-84
Author(s):  
Jayashree K. ◽  
Swaminathan B.
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Social Network ◽  
High Dimensional Data ◽  
High Dimensional ◽  
Data Sets ◽  
It Services ◽  
Delivery Model ◽  
Research Challenges ◽  
Future Direction

The huge size of data that has been produced by applications that spans from social network to scientific computing is termed big data. Cloud computing as a delivery model for IT services enhances business productivity by reducing cost. It has the intention of achieving solution for managing big data such as high dimensional data sets. Thus, this chapter discusses the background of big data and cloud computing. It also discusses the various application of big data in detail. The various related work, research challenges of big data in cloud computing, and the future direction are addressed in this chapter.

scholarly journals Analysis and visualization of big data in globally distributed cloud computing monitoring systems

2019 ◽  
Author(s):  
Кристина Кучерова ◽  
Kristina Kucherova ◽  
Сергей Мещеряков ◽  
Sergey Mescheryakov ◽  
Дмитрий Щемелинин ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Performance Indicators ◽  
Visual Analytics ◽  
Monitoring Systems ◽  
It Services ◽  
Paper Briefly ◽  
Distributed Cloud ◽  
Globally Distributed

Quality of IT Services (QoS), providing across all globally distributed regions via Internet, use modern cloud computing IT technologies having big data flow and, therefore, is actual. This paper briefly describes the methods of analysis and visualization of monitoring big data based on Key Performance Indicators (KPIs) of a cloud computing IT system using real world example of globally distributed infrastructure of the International IT Company. Implementation of proposed methods of visual analytics in worldwide leading IT companies – RingCentral (USA) and Zabbix (Latvia), – allowed improving of QoS and availability of IT services up to a worldwide level of 99.999% in 24/7 mode. Implementation of new solutions in IT companies is confirmed by corresponding documents and by publications in PhD and DSc thesis of the coauthors.

Data Intensive Cloud Computing

Big Data ◽  
2016 ◽  
pp. 639-654
Author(s):  
Jayalakshmi D. S. ◽  
R. Srinivasan ◽  
K. G. Srinivasa
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Cluster Computing ◽  
Resource Provisioning ◽  
Data Intensive ◽  
Scientific Value ◽  
Data Intensive Applications ◽  
Cloud Applications ◽  
Problem Data ◽  
Huge Challenge

Processing Big Data is a huge challenge for today's technology. There is a need to find, apply and analyze new ways of computing to make use of the Big Data so as to derive business and scientific value from it. Cloud computing with its promise of seemingly infinite computing resources is seen as the solution to this problem. Data Intensive computing on cloud builds upon the already mature parallel and distributed computing technologies such HPC, grid and cluster computing. However, handling Big Data in the cloud presents its own challenges. In this chapter, we analyze issues specific to data intensive cloud computing and provides a study on available solutions in programming models, data distribution and replication, resource provisioning and scheduling with reference to data intensive applications in cloud. Future directions for further research enabling data intensive cloud applications in cloud environment are identified.

scholarly journals Enabling the Big Earth Observation Data via Cloud Computing and DGGS: Opportunities and Challenges

2019 ◽  
Vol 12 (1) ◽  
pp. 62 ◽  
Author(s):  
Xiaochuang Yao ◽  
Guoqing Li ◽  
Junshi Xia ◽  
Jin Ben ◽  
Qianqian Cao ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Earth Observation ◽  
Current Status ◽  
Observation Data ◽  
Computing Technology ◽  
Grid Systems ◽  
Data Framework ◽  
Earth Observation Data ◽  
Global Grid

In the era of big data, the explosive growth of Earth observation data and the rapid advancement in cloud computing technology make the global-oriented spatiotemporal data simulation possible. These dual developments also provide advantageous conditions for discrete global grid systems (DGGS). DGGS are designed to portray real-world phenomena by providing a spatiotemporal unified framework on a standard discrete geospatial data structure and theoretical support to address the challenges from big data storage, processing, and analysis to visualization and data sharing. In this paper, the trinity of big Earth observation data (BEOD), cloud computing, and DGGS is proposed, and based on this trinity theory, we explore the opportunities and challenges to handle BEOD from two aspects, namely, information technology and unified data framework. Our focus is on how cloud computing and DGGS can provide an excellent solution to enable big Earth observation data. Firstly, we describe the current status and data characteristics of Earth observation data, which indicate the arrival of the era of big data in the Earth observation domain. Subsequently, we review the cloud computing technology and DGGS framework, especially the works and contributions made in the field of BEOD, including spatial cloud computing, mainstream big data platform, DGGS standards, data models, and applications. From the aforementioned views of the general introduction, the research opportunities and challenges are enumerated and discussed, including EO data management, data fusion, and grid encoding, which are concerned with analysis models and processing performance of big Earth observation data with discrete global grid systems in the cloud environment.

How does cloud computing help businesses to manage big data issues

Kybernetes ◽  
2022 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ahmad Latifian
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Data Management ◽  
Data Storage ◽  
Data Privacy ◽  
High Efficiency ◽  
Future Research ◽  
It Services ◽  
Computing Technology ◽  
Content Type

PurposeBig data has posed problems for businesses, the Information Technology (IT) sector and the science community. The problems posed by big data can be effectively addressed using cloud computing and associated distributed computing technology. Cloud computing and big data are two significant past-year problems that allow high-efficiency and competitive computing tools to be delivered as IT services. The paper aims to examine the role of the cloud as a tool for managing big data in various aspects to help businesses.Design/methodology/approachThis paper delivers solutions in the cloud for storing, compressing, analyzing and processing big data. Hence, articles were divided into four categories: articles on big data storage, articles on big data processing, articles on analyzing and finally, articles on data compression in cloud computing. This article is based on a systematic literature review. Also, it is based on a review of 19 published papers on big data.FindingsFrom the results, it can be inferred that cloud computing technology has features that can be useful for big data management. Challenging issues are raised in each section. For example, in storing big data, privacy and security issues are challenging.Research limitations/implicationsThere were limitations to this systematic review. The first limitation is that only English articles were reviewed. Also, articles that matched the keywords were used. Finally, in this review, authoritative articles were reviewed, and slides and tutorials were avoided.Practical implicationsThe research presents new insight into the business value of cloud computing in interfirm collaborations.Originality/valuePrevious research has often examined other aspects of big data in the cloud. This article takes a new approach to the subject. It allows big data researchers to comprehend the various aspects of big data management in the cloud. In addition, setting an agenda for future research saves time and effort for readers searching for topics within big data.

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