Efficient data synchronization method on integrated computing environment

Data synchronization of electronic instrument transformer is introduced. Synchronization method commonly used are analyzed in aspects of their advantages and disadvantages, such as interpolation synchronization, impulsive synchronization method; Then, a new approach based on Newton interpolation is presented, and the simulation and error analysis are given. The theoretical analysis results show that this method can reach to the same precision with Lagrange interpolation which is accurate in synchronization of harmonic components and obtain the synchronized data fast. Finally this paper sets equal interval sampling and non-equal interval sampling data, and then calculates maximum error in the case of the steady state and transient state respectively by using Matlab. The simulation results proved the feasibility of this method and its engineering practical value.

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An efficient data security mechanism with data sharing and authentication

ACCENTS Transactions on Information Security ◽

10.19101/tis.2020.517008 ◽

2020 ◽

Vol 5 (19) ◽

pp. 26-31

Author(s):

Md. Farooque ◽

Kailash Patidar ◽

Rishi Kushwah ◽

Gaurav Saxena

Keyword(s):

Cloud Computing ◽

Data Sharing ◽

Data Security ◽

Security Analysis ◽

Key Generation ◽

Security Mechanism ◽

Computing Environment ◽

Cloud Computing Environment ◽

Cloud Data ◽

Efficient Data

In this paper an efficient security mechanism has been adopted for the cloud computing environment. It also provides an extendibility of cloud computing environment with big data and Internet of Things. AES-256 and RC6 with two round key generation have been applied for data and application security. Three-way security mechanism has been adopted and implemented. It is user to user (U to U) for data sharing and inter cloud communication. Then user to cloud (U to C) for data security management for application level hierarchy of cloud. Finally, cloud to user (C to U) for the cloud data protection. The security analysis has been tested with different iterations and rounds and it is found to be satisfactory.

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An efficient data replica placement mechanism using biogeography-based optimization technique in the fog computing environment

Journal of Ambient Intelligence and Humanized Computing ◽

10.1007/s12652-021-03495-0 ◽

2021 ◽

Author(s):

Jaber Taghizadeh ◽

Mostafa Ghobaei-Arani ◽

Ali Shahidinejad

Keyword(s):

Fog Computing ◽

Optimization Technique ◽

Replica Placement ◽

Computing Environment ◽

Efficient Data

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Job submission and monitoring management in integrated computing environment for finite element analysis

The Journal of Supercomputing ◽

10.1007/s11227-018-2590-4 ◽

2018 ◽

Vol 74 (12) ◽

pp. 6960-6975 ◽

Cited By ~ 2

Author(s):

Daeyong Jung ◽

Myungil Kim ◽

Jungha Lee ◽

Han-Yee Kim ◽

Daewon Lee

Keyword(s):

Finite Element Analysis ◽

Finite Element ◽

Computing Environment ◽

Element Analysis ◽

Integrated Computing Environment

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Efficient Data Mining Model Design for a Large Database in the Cloud Computing Environment

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.713-715.2447 ◽

2015 ◽

Vol 713-715 ◽

pp. 2447-2450

Author(s):

Zhan Kun Zhao

Keyword(s):

Data Mining ◽

Cloud Computing ◽

Manifold Learning ◽

Model Design ◽

Large Database ◽

Computing Environment ◽

Cloud Computing Environment ◽

Efficient Data ◽

Computing Environments ◽

Mining Model

Efficient data mining model design for a large database in the cloud computing environment is studied. For large databases efficiently mining problem, an efficient data mining model in the cloud computing environment based on improved manifold learning algorithms is proposed. The use of nonlinear manifold learning algorithms is able to reduce dimensionality of data vector feature in cloud computing environments, through characteristic extraction module to preprocess data, improved classical manifold learning algorithm is adopted to increase the distance between the data of sample spread intensive area and shorten the distance between the data of sample spread sparse area, prompting even overall distribution of sample database under cloud computing environment, so as to achieve accurate mining for efficient data in cloud computing environment. The experimental results show that the proposed method can accurately mine target data under cloud computing environments, with high efficiency and precision.

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