An Efficient Improving Cloud Data Storage Security using Failure Aware Resource Scheduling Algorithm

Cloud computing, provides the delivery of on-demand computing resources, it is displayed as an innovative platform, provides a high-performance computing environment for the user. The need for cloud computing is increasing gradually every day. Cloud computing, data storage security is a big problem...

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Bibliographic Details
Published in:Turkish journal of computer and mathematics education 2021-01, Vol.12 (13), p.237-242
Main Authors: Parkavi, S Surya, Varshini, S, Naresh, R
Format: Article
Language:English
Subjects:
Access control
Algorithms
Cloud computing
Cybersecurity
Data integrity
Data storage
Encryption
Failure rates
Resource scheduling
Scheduling
Task scheduling
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Summary:Cloud computing, provides the delivery of on-demand computing resources, it is displayed as an innovative platform, provides a high-performance computing environment for the user. The need for cloud computing is increasing gradually every day. Cloud computing, data storage security is a big problem since the data in the cloud must be sent via the Internet, data security is a big problem. Integrity, accountability, privacy, access control, authentication, must be to maintain an important mechanism for data protection, such as approval. To overcome this problem, the proposed Failure Aware Resource scheduling (FARS) to reduce the failure leading and reduced system performance tasks. The proposed method is clients send data using encryption for protecting the highly confidential files because the files or data unauthorized persons cannot be stolen or view the files so the files or data protected then generate the One-Time Password (OTP) for decrypting the files. Nodes with relatively low computing power and a low failure rate can provide better performance and reduced resources. The method is based on failure aware scheduling, especially for users who want to move the collective frequently, which can reduce the discovery time of the cloud service rather than the failed resource planning methods. That the crowdsourcing model is an effective way to solve huge co- tasks.
ISSN:1309-4653