Architecture and Key Technologies of Cloud Computing

2013 ◽  
Vol 756-759 ◽  
pp. 1953-1956
Author(s):  
Li Yuan Xiao ◽  
Zheng Wang ◽  
Rui Wang ◽  
Hai Ning Wang
Keyword(s):  
Cloud Computing ◽  
Parallel Computing ◽  
Distributed Computing ◽  
Grid Computing ◽  
The Internet ◽  
Key Technologies ◽  
The Future ◽  
Computing Grid

The Internet has changed the computing world in a drastic way from the advent of the Internet in 1990. The concepts of distributed computing, parallel computing, grid computing and cloud computing have been proposed successively. Although cloud computing is generally recognized as a technology which will has a significant impact on IT in the future. But cloud computing is still in its infancy. In this paper we will discuss the architecture and the key technologies of the cloud computing.

Resource Scheduling for Big Data on Cloud

2016 ◽  
pp. 185-205 ◽  
Author(s):  
K. Indira Suthakar ◽  
M. K. Kavitha Devi
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Distributed Computing ◽  
Grid Computing ◽  
Task Scheduling ◽  
Service Providers ◽  
Maximum Profit ◽  
Cloud Computing Service ◽  
Computing Grid ◽  
Scheduling Strategies

Cloud computing is based on the concepts of distributed computing, grid computing, utility computing and virtualization. It is a virtual pool of resources which are provided to users via Internet. It gives users virtually unlimited pay-per-use computing resources without the burden of managing the underlying infrastructure. Cloud computing service providers' one of the goals is to use the resources efficiently and gain maximum profit. This leads to task scheduling as a core and challenging issue in cloud computing. This paper gives different scheduling strategies and algorithms in cloud computing.

Extending Dynamic Scheduling Policies in WorkflowSim by Using Variance based Approach

2016 ◽  
Vol 8 (2) ◽  
pp. 76-93 ◽  
Author(s):  
Jyoti Thaman ◽  
Manpreet Singh
Keyword(s):  
Cloud Computing ◽  
Performance Analysis ◽  
Grid Computing ◽  
Dynamic Scheduling ◽  
Workflow Scheduling ◽  
Scheduling Policies ◽  
Hierarchical Relationship ◽  
Service Oriented ◽  
Computing Grid ◽  
Task Types

Workflow scheduling has been around for more than two decades. With growing interest in service oriented computing architecture among researchers and corporate users, different platform like clusters computing, grid computing and most recent cloud computing, appeared on computing horizon. Cloud computing has attracted a lot of interest from all types of users. It gave rise to variety of applications and tasks with varied requirements. Heterogeneity in application's requirement catalyzes the provision of customized services for task types. Representation of tasks characteristics and inter-task relationship through workflows is in use since the ages of automation. Scheduling of workflows not only maintain the hierarchical relationship between the tasks but also dictates the requirement of dynamic scheduling. This paper presents a variance based extensions of few promising dynamic scheduling policies supported by WorkflowSim. An exhaustive performance analysis presents strength and weakness of the authors' proposal.

Similarities and Contrast between Grid Computing and Cloud Computing

2011 ◽  
Vol 3 (3) ◽  
pp. 54-56
Author(s):  
Prof. Milan Kantilal Vachhani ◽  
◽  
Dr. Kishor H Atkotiya
Keyword(s):  
Cloud Computing ◽  
Grid Computing

A Review Paper on Cloud Computing

2018 ◽  
Vol 8 (6) ◽  
pp. 17 ◽  
Author(s):  
Priyanshu Srivastava ◽  
Rizwan Khan
Keyword(s):  
Cloud Computing ◽  
Grid Computing ◽  
Review Paper ◽  
Computing Technology ◽  
Internet Infrastructure ◽  
Before And After ◽  
The Face

Today is the era of Cloud Computing Technology in IT Industries. Cloud computing which is based on Internet has the most powerful architecture of computation. It reckons in of a compilation of integrated and networked hardware, software and internet infrastructure. It has various avails atop grid computing and other computing. In this paper, I have given a brief of evaluation of cloud computing by reviewing more than 30 articles on cloud computing. The outcome of this review signalizes the face of the IT industries before and after the cloud computing.

Comparative Study of Cryptography for Cloud Computing for Data Security

2019 ◽  
Vol 13 ◽  
Author(s):  
Priya Mathur ◽  
Amit Kumar Gupta ◽  
Prateek Vashishtha
Keyword(s):  
Cloud Computing ◽  
Data Security ◽  
Elliptic Curve Cryptography ◽  
Plain Text ◽  
Hybrid Encryption ◽  
Cipher Text ◽  
Business Applications ◽  
Computing Grid ◽  
Cloud Servers ◽  
Client Side

Cloud computing is an emerging technique by which anyone can access the applications as utilities over the internet. Cloud computing is the technology which comprises of all the characteristics of the technologies like distributed computing, grid computing, and ubiquitous computing. Cloud computing allows everyone to create, to configure as well as to customize the business applications online. Cryptography is the technique which is use to convert the plain text into cipher text using various encryption techniques. The art and science used to introduce the secrecy in the information security in order to secure the messages is defined as cryptography. In this paper we are going to review few latest Cryptographic algorithms which are used to enhance the security of the data on the cloud servers. We are comparing Short Range Natural Number Modified RSA (SRNN), Elliptic Curve Cryptography Algorithm, Client Side Encryption Technique and Hybrid Encryption Technique to secure the data in cloud.

Probabilistic State Estimation Based Scheduling Approach for Cloud Computing

2011 ◽  
Vol 55-57 ◽  
pp. 1053-1057
Author(s):  
Gui De Zheng ◽  
Ming Chen
Keyword(s):  
Cloud Computing ◽  
Grid Computing ◽  
State Estimation ◽  
Distributed Data ◽  
Scientific Instruments ◽  
Next Generation ◽  
Data Intensive ◽  
Application Model ◽  
Scientific Experiments ◽  
The World

The next generation of scientific experiments and studies are being carried out by large collaborations of researchers distributed around the world engaged in analysis of huge collections of data generated by scientific instruments. Grid computing has emerged as an enabler for such collaborations as it aids communities in sharing resource to achieve common objective. This paper defines the problem of scheduling distributed data-intensive application on to Gird resource and presents a formal resource and application model for the problem.

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