A Dynamic Resource Allocation based on Multi Attributes Scoring in Collaborative Cloud Computing

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Dr. Anirban Basu
Dr. Anirban Basu
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Anitha N
Anitha N
1 EPCET

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GJCST Volume 15 Issue B4

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Collaborative cloud computing involves providing cloud services on globally distributed resources belonging to different organizations in a cooperative manner. Resource management and allocation in Collaborative Cloud is challenging because of the heterogeneity of the resources. The other challenge is guaranteeing the Quality of Service (QOS) and availability of these resources. Users’ resource demands have to be managed properly to ensure acceptable QOS. In this paper, we propose a method for effective management and allocation of resources using machine learning and using multi attribute tuning. The method has been simulated in cloud-sim as well as implemented on Amazon work space and results show that the proposed method performs better than reputation based algorithms.

9 Cites in Articles

References

  1. L Xiong,L Liu (2004). Peertrust: Supporting Reputation-Based Trust for Peer-to-Peer Electronic Communities.
  2. Runfang Zhou,Kai Hwang (2008). PowerTrust: A Robust and Scalable Reputation System for Trusted Peer-to-Peer Computing.
  3. R Zhou,K Hwang (2007). Gossip-Based Reputation Management for Unstructured Peer-to-Peer Networks.
  4. Haiying Shen,; Ieee,Guoxin Liu (2014). An Efficient and Trustworthy Resource Sharing Platform for Collaborative Cloud Computing.
  5. Jianxin Li,Bo Li,Zongxia Du,Linlin Meng (2010). CloudVO: Building a Secure Virtual Organization for Multiple Clouds Collaboration.
  6. Changbin Liu,Boon Loo,Yun Mao (2011). Declarative automated cloud resource orchestration.
  7. Kai Hwang,Sameer Kulkareni,Yue Hu (2009). Cloud Security with Virtualized Defense and Reputation-Based Trust Mangement.
  8. Changbin Liu,Boon Loo,Yun Mao (2011). Declarative automated cloud resource orchestration.
  9. Mudhakar Srivatsa,Li Xiong,Ling Liu (2005). TrustGuard.

Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

Dr. Anirban Basu. 2015. \u201cA Dynamic Resource Allocation based on Multi Attributes Scoring in Collaborative Cloud Computing\u201d. Global Journal of Computer Science and Technology - B: Cloud & Distributed GJCST-B Volume 15 (GJCST Volume 15 Issue B4): .

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

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GJCST-B Classification: C.1.4 H.3.4
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v1.2

Issue date

October 5, 2015

Language

English

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Collaborative cloud computing involves providing cloud services on globally distributed resources belonging to different organizations in a cooperative manner. Resource management and allocation in Collaborative Cloud is challenging because of the heterogeneity of the resources. The other challenge is guaranteeing the Quality of Service (QOS) and availability of these resources. Users’ resource demands have to be managed properly to ensure acceptable QOS. In this paper, we propose a method for effective management and allocation of resources using machine learning and using multi attribute tuning. The method has been simulated in cloud-sim as well as implemented on Amazon work space and results show that the proposed method performs better than reputation based algorithms.

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A Dynamic Resource Allocation based on Multi Attributes Scoring in Collaborative Cloud Computing

Anitha N
Anitha N
Dr. Anirban Basu
Dr. Anirban Basu EPCET

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